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Sample records for regression examined associations

  1. Exploring factors associated with traumatic dental injuries in preschool children: a Poisson regression analysis.

    Science.gov (United States)

    Feldens, Carlos Alberto; Kramer, Paulo Floriani; Ferreira, Simone Helena; Spiguel, Mônica Hermann; Marquezan, Marcela

    2010-04-01

    This cross-sectional study aimed to investigate the factors associated with dental trauma in preschool children using Poisson regression analysis with robust variance. The study population comprised 888 children aged 3- to 5-year-old attending public nurseries in Canoas, southern Brazil. Questionnaires assessing information related to the independent variables (age, gender, race, mother's educational level and family income) were completed by the parents. Clinical examinations were carried out by five trained examiners in order to assess traumatic dental injuries (TDI) according to Andreasen's classification. One of the five examiners was calibrated to assess orthodontic characteristics (open bite and overjet). Multivariable Poisson regression analysis with robust variance was used to determine the factors associated with dental trauma as well as the strengths of association. Traditional logistic regression was also performed in order to compare the estimates obtained by both methods of statistical analysis. 36.4% (323/888) of the children suffered dental trauma and there was no difference in prevalence rates from 3 to 5 years of age. Poisson regression analysis showed that the probability of the outcome was almost 30% higher for children whose mothers had more than 8 years of education (Prevalence Ratio = 1.28; 95% CI = 1.03-1.60) and 63% higher for children with an overjet greater than 2 mm (Prevalence Ratio = 1.63; 95% CI = 1.31-2.03). Odds ratios clearly overestimated the size of the effect when compared with prevalence ratios. These findings indicate the need for preventive orientation regarding TDI, in order to educate parents and caregivers about supervising infants, particularly those with increased overjet and whose mothers have a higher level of education. Poisson regression with robust variance represents a better alternative than logistic regression to estimate the risk of dental trauma in preschool children.

  2. Using quantile regression to examine health care expenditures during the Great Recession.

    Science.gov (United States)

    Chen, Jie; Vargas-Bustamante, Arturo; Mortensen, Karoline; Thomas, Stephen B

    2014-04-01

    To examine the association between the Great Recession of 2007-2009 and health care expenditures along the health care spending distribution, with a focus on racial/ethnic disparities. Secondary data analyses of the Medical Expenditure Panel Survey (2005-2006 and 2008-2009). Quantile multivariate regressions are employed to measure the different associations between the economic recession of 2007-2009 and health care spending. Race/ethnicity and interaction terms between race/ethnicity and a recession indicator are controlled to examine whether minorities encountered disproportionately lower health spending during the economic recession. The Great Recession was significantly associated with reductions in health care expenditures at the 10th-50th percentiles of the distribution, but not at the 75th-90th percentiles. Racial and ethnic disparities were more substantial at the lower end of the health expenditure distribution; however, on average the reduction in expenditures was similar for all race/ethnic groups. The Great Recession was also positively associated with spending on emergency department visits. This study shows that the relationship between the Great Recession and health care spending varied along the health expenditure distribution. More variability was observed in the lower end of the health spending distribution compared to the higher end. © Health Research and Educational Trust.

  3. Healthcare Expenditures Associated with Depression Among Individuals with Osteoarthritis: Post-Regression Linear Decomposition Approach.

    Science.gov (United States)

    Agarwal, Parul; Sambamoorthi, Usha

    2015-12-01

    Depression is common among individuals with osteoarthritis and leads to increased healthcare burden. The objective of this study was to examine excess total healthcare expenditures associated with depression among individuals with osteoarthritis in the US. Adults with self-reported osteoarthritis (n = 1881) were identified using data from the 2010 Medical Expenditure Panel Survey (MEPS). Among those with osteoarthritis, chi-square tests and ordinary least square regressions (OLS) were used to examine differences in healthcare expenditures between those with and without depression. Post-regression linear decomposition technique was used to estimate the relative contribution of different constructs of the Anderson's behavioral model, i.e., predisposing, enabling, need, personal healthcare practices, and external environment factors, to the excess expenditures associated with depression among individuals with osteoarthritis. All analysis accounted for the complex survey design of MEPS. Depression coexisted among 20.6 % of adults with osteoarthritis. The average total healthcare expenditures were $13,684 among adults with depression compared to $9284 among those without depression. Multivariable OLS regression revealed that adults with depression had 38.8 % higher healthcare expenditures (p regression linear decomposition analysis indicated that 50 % of differences in expenditures among adults with and without depression can be explained by differences in need factors. Among individuals with coexisting osteoarthritis and depression, excess healthcare expenditures associated with depression were mainly due to comorbid anxiety, chronic conditions and poor health status. These expenditures may potentially be reduced by providing timely intervention for need factors or by providing care under a collaborative care model.

  4. Associations between United States Medical Licensing Examination (USMLE) and Internal Medicine In-Training Examination (IM-ITE) scores.

    Science.gov (United States)

    McDonald, Furman S; Zeger, Scott L; Kolars, Joseph C

    2008-07-01

    Little is known about the associations of previous standardized examination scores with scores on subsequent standardized examinations used to assess medical knowledge in internal medicine residencies. To examine associations of previous standardized test scores on subsequent standardized test scores. Retrospective cohort study. One hundred ninety-five internal medicine residents. Bivariate associations of United States Medical Licensing Examination (USMLE) Steps and Internal Medicine In-Training Examination (IM-ITE) scores were determined. Random effects analysis adjusting for repeated administrations of the IM-ITE and other variables known or hypothesized to affect IM-ITE score allowed for discrimination of associations of individual USMLE Step scores on IM-ITE scores. In bivariate associations, USMLE scores explained 17% to 27% of the variance in IME-ITE scores, and previous IM-ITE scores explained 66% of the variance in subsequent IM-ITE scores. Regression coefficients (95% CI) for adjusted associations of each USMLE Step with IM-ITE scores were USMLE-1 0.19 (0.12, 0.27), USMLE-2 0.23 (0.17, 0.30), and USMLE-3 0.19 (0.09, 0.29). No single USMLE Step is more strongly associated with IM-ITE scores than the others. Because previous IM-ITE scores are strongly associated with subsequent IM-ITE scores, appropriate modeling, such as random effects methods, should be used to account for previous IM-ITE administrations in studies for which IM-ITE score is an outcome.

  5. Misery loves company? A meta-regression examining aggregate unemployment rates and the unemployment-mortality association.

    Science.gov (United States)

    Roelfs, David J; Shor, Eran; Blank, Aharon; Schwartz, Joseph E

    2015-05-01

    Individual-level unemployment has been consistently linked to poor health and higher mortality, but some scholars have suggested that the negative effect of job loss may be lower during times and in places where aggregate unemployment rates are high. We review three logics associated with this moderation hypothesis: health selection, social isolation, and unemployment stigma. We then test whether aggregate unemployment rates moderate the individual-level association between unemployment and all-cause mortality. We use six meta-regression models (each using a different measure of the aggregate unemployment rate) based on 62 relative all-cause mortality risk estimates from 36 studies (from 15 nations). We find that the magnitude of the individual-level unemployment-mortality association is approximately the same during periods of high and low aggregate-level unemployment. Model coefficients (exponentiated) were 1.01 for the crude unemployment rate (P = .27), 0.94 for the change in unemployment rate from the previous year (P = .46), 1.01 for the deviation of the unemployment rate from the 5-year running average (P = .87), 1.01 for the deviation of the unemployment rate from the 10-year running average (P = .73), 1.01 for the deviation of the unemployment rate from the overall average (measured as a continuous variable; P = .61), and showed no variation across unemployment levels when the deviation of the unemployment rate from the overall average was measured categorically. Heterogeneity between studies was significant (P unemployment experiences change when macroeconomic conditions change. Efforts to ameliorate the negative social and economic consequences of unemployment should continue to focus on the individual and should be maintained regardless of periodic changes in macroeconomic conditions. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. A multiple regression method for genomewide association studies ...

    Indian Academy of Sciences (India)

    Bujun Mei

    2018-06-07

    Jun 7, 2018 ... Similar to the typical genomewide association tests using LD ... new approach performed validly when the multiple regression based on linkage method was employed. .... the model, two groups of scenarios were simulated.

  7. Examination of influential observations in penalized spline regression

    Science.gov (United States)

    Türkan, Semra

    2013-10-01

    In parametric or nonparametric regression models, the results of regression analysis are affected by some anomalous observations in the data set. Thus, detection of these observations is one of the major steps in regression analysis. These observations are precisely detected by well-known influence measures. Pena's statistic is one of them. In this study, Pena's approach is formulated for penalized spline regression in terms of ordinary residuals and leverages. The real data and artificial data are used to see illustrate the effectiveness of Pena's statistic as to Cook's distance on detecting influential observations. The results of the study clearly reveal that the proposed measure is superior to Cook's Distance to detect these observations in large data set.

  8. Bias due to two-stage residual-outcome regression analysis in genetic association studies.

    Science.gov (United States)

    Demissie, Serkalem; Cupples, L Adrienne

    2011-11-01

    Association studies of risk factors and complex diseases require careful assessment of potential confounding factors. Two-stage regression analysis, sometimes referred to as residual- or adjusted-outcome analysis, has been increasingly used in association studies of single nucleotide polymorphisms (SNPs) and quantitative traits. In this analysis, first, a residual-outcome is calculated from a regression of the outcome variable on covariates and then the relationship between the adjusted-outcome and the SNP is evaluated by a simple linear regression of the adjusted-outcome on the SNP. In this article, we examine the performance of this two-stage analysis as compared with multiple linear regression (MLR) analysis. Our findings show that when a SNP and a covariate are correlated, the two-stage approach results in biased genotypic effect and loss of power. Bias is always toward the null and increases with the squared-correlation between the SNP and the covariate (). For example, for , 0.1, and 0.5, two-stage analysis results in, respectively, 0, 10, and 50% attenuation in the SNP effect. As expected, MLR was always unbiased. Since individual SNPs often show little or no correlation with covariates, a two-stage analysis is expected to perform as well as MLR in many genetic studies; however, it produces considerably different results from MLR and may lead to incorrect conclusions when independent variables are highly correlated. While a useful alternative to MLR under , the two -stage approach has serious limitations. Its use as a simple substitute for MLR should be avoided. © 2011 Wiley Periodicals, Inc.

  9. Visual grading characteristics and ordinal regression analysis during optimisation of CT head examinations.

    Science.gov (United States)

    Zarb, Francis; McEntee, Mark F; Rainford, Louise

    2015-06-01

    To evaluate visual grading characteristics (VGC) and ordinal regression analysis during head CT optimisation as a potential alternative to visual grading assessment (VGA), traditionally employed to score anatomical visualisation. Patient images (n = 66) were obtained using current and optimised imaging protocols from two CT suites: a 16-slice scanner at the national Maltese centre for trauma and a 64-slice scanner in a private centre. Local resident radiologists (n = 6) performed VGA followed by VGC and ordinal regression analysis. VGC alone indicated that optimised protocols had similar image quality as current protocols. Ordinal logistic regression analysis provided an in-depth evaluation, criterion by criterion allowing the selective implementation of the protocols. The local radiology review panel supported the implementation of optimised protocols for brain CT examinations (including trauma) in one centre, achieving radiation dose reductions ranging from 24 % to 36 %. In the second centre a 29 % reduction in radiation dose was achieved for follow-up cases. The combined use of VGC and ordinal logistic regression analysis led to clinical decisions being taken on the implementation of the optimised protocols. This improved method of image quality analysis provided the evidence to support imaging protocol optimisation, resulting in significant radiation dose savings. • There is need for scientifically based image quality evaluation during CT optimisation. • VGC and ordinal regression analysis in combination led to better informed clinical decisions. • VGC and ordinal regression analysis led to dose reductions without compromising diagnostic efficacy.

  10. Parameter Estimation for Improving Association Indicators in Binary Logistic Regression

    Directory of Open Access Journals (Sweden)

    Mahdi Bashiri

    2012-02-01

    Full Text Available The aim of this paper is estimation of Binary logistic regression parameters for maximizing the log-likelihood function with improved association indicators. In this paper the parameter estimation steps have been explained and then measures of association have been introduced and their calculations have been analyzed. Moreover a new related indicators based on membership degree level have been expressed. Indeed association measures demonstrate the number of success responses occurred in front of failure in certain number of Bernoulli independent experiments. In parameter estimation, existing indicators values is not sensitive to the parameter values, whereas the proposed indicators are sensitive to the estimated parameters during the iterative procedure. Therefore, proposing a new association indicator of binary logistic regression with more sensitivity to the estimated parameters in maximizing the log- likelihood in iterative procedure is innovation of this study.

  11. Association Between National Board Dental Examination Part II Scores and Comprehensive Examinations at Harvard School of Dental Medicine.

    Science.gov (United States)

    Lee, Min Kyeong; Allareddy, Veerasathpurush; Howell, T Howard; Karimbux, Nadeem Y

    2011-01-01

    Harvard School of Dental Medicine (HSDM) uses a hybrid problem-based approach to teaching in the predoctoral program. The objective structured clinical examination (OSCE) is a formative examination designed to assess the performance of students in the problem-based learning (PBL) curriculum. At HSDM three comprehensive examinations with OSCE components are administered during the third and fourth years of clinical training. The National Board Dental Examination (NBDE) Part II is taken in the final year of the predoctoral program. This study examines the association between the NBDE Part II and the comprehensive exams held at HSDM. Predoctoral students from the HSDM classes of 2005 and 2006 were included in this study. The outcome variable of interest was the scores obtained by students in the NBDE Part II, and the main independent variable of interest was the performance of students in the comprehensive exams (honors, pass, make-up exam to pass). The Mann-Whitney U-test was used to examine the association between the grades obtained in the each of the three comprehensive exams and the NBDE Part II scores. Multivariable linear regression analysis was also used to examine the association between the NBDE Part II scores and the comprehensive exam grades. The effect of potential confounding factors including age, sex, and race/ethnicity was adjusted. The results suggest that students who performed well in the comprehensive exams performed better on the NBDE Part II, even after adjusting for confounding factors. Future studies will examine the long-term impact of PBL on postdoctoral plans and career choices.

  12. Ordinary least square regression, orthogonal regression, geometric mean regression and their applications in aerosol science

    International Nuclear Information System (INIS)

    Leng Ling; Zhang Tianyi; Kleinman, Lawrence; Zhu Wei

    2007-01-01

    Regression analysis, especially the ordinary least squares method which assumes that errors are confined to the dependent variable, has seen a fair share of its applications in aerosol science. The ordinary least squares approach, however, could be problematic due to the fact that atmospheric data often does not lend itself to calling one variable independent and the other dependent. Errors often exist for both measurements. In this work, we examine two regression approaches available to accommodate this situation. They are orthogonal regression and geometric mean regression. Comparisons are made theoretically as well as numerically through an aerosol study examining whether the ratio of organic aerosol to CO would change with age

  13. Integration of association statistics over genomic regions using Bayesian adaptive regression splines

    Directory of Open Access Journals (Sweden)

    Zhang Xiaohua

    2003-11-01

    Full Text Available Abstract In the search for genetic determinants of complex disease, two approaches to association analysis are most often employed, testing single loci or testing a small group of loci jointly via haplotypes for their relationship to disease status. It is still debatable which of these approaches is more favourable, and under what conditions. The former has the advantage of simplicity but suffers severely when alleles at the tested loci are not in linkage disequilibrium (LD with liability alleles; the latter should capture more of the signal encoded in LD, but is far from simple. The complexity of haplotype analysis could be especially troublesome for association scans over large genomic regions, which, in fact, is becoming the standard design. For these reasons, the authors have been evaluating statistical methods that bridge the gap between single-locus and haplotype-based tests. In this article, they present one such method, which uses non-parametric regression techniques embodied by Bayesian adaptive regression splines (BARS. For a set of markers falling within a common genomic region and a corresponding set of single-locus association statistics, the BARS procedure integrates these results into a single test by examining the class of smooth curves consistent with the data. The non-parametric BARS procedure generally finds no signal when no liability allele exists in the tested region (ie it achieves the specified size of the test and it is sensitive enough to pick up signals when a liability allele is present. The BARS procedure provides a robust and potentially powerful alternative to classical tests of association, diminishes the multiple testing problem inherent in those tests and can be applied to a wide range of data types, including genotype frequencies estimated from pooled samples.

  14. Retro-regression--another important multivariate regression improvement.

    Science.gov (United States)

    Randić, M

    2001-01-01

    We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

  15. Examining associations between adolescent binge eating and binge eating in parents and friends.

    Science.gov (United States)

    Goldschmidt, Andrea B; Wall, Melanie M; Choo, Tse-Hwei J; Bruening, Meg; Eisenberg, Marla E; Neumark-Sztainer, Dianne

    2014-04-01

    Binge eating is prevalent among adolescents, but little is known about how parents and friends may influence such behaviors. This study examined associations between adolescent binge eating behaviors, and similar behaviors in their parents and friends. Participants were 2,770 target adolescent boys and girls who had at least one friend and/or parent who also participated. Logistic regression, stratified by gender, examined associations between parents' and friends' self-reported binge eating, and similar behaviors in target adolescents. Girls' binge eating was associated with their male friends' (odds ratio = 2.33; p = 0.03) and fathers' binge eating (odds ratio = 3.38; p = 0.02), but not with their female friends' or mothers' binge eating (p > 0.05). For boys, binge eating was not associated with parents' or friends' behavior. Adolescent girls' binge eating is associated with similar behaviors in their other-sex parents and friends. Results should be replicated, and mechanisms explaining this relation should be further explored. Copyright © 2013 Wiley Periodicals, Inc.

  16. Logistic regression analysis to predict Medical Licensing Examination of Thailand (MLET) Step1 success or failure.

    Science.gov (United States)

    Wanvarie, Samkaew; Sathapatayavongs, Boonmee

    2007-09-01

    The aim of this paper was to assess factors that predict students' performance in the Medical Licensing Examination of Thailand (MLET) Step1 examination. The hypothesis was that demographic factors and academic records would predict the students' performance in the Step1 Licensing Examination. A logistic regression analysis of demographic factors (age, sex and residence) and academic records [high school grade point average (GPA), National University Entrance Examination Score and GPAs of the pre-clinical years] with the MLET Step1 outcome was accomplished using the data of 117 third-year Ramathibodi medical students. Twenty-three (19.7%) students failed the MLET Step1 examination. Stepwise logistic regression analysis showed that the significant predictors of MLET Step1 success/failure were residence background and GPAs of the second and third preclinical years. For students whose sophomore and third-year GPAs increased by an average of 1 point, the odds of passing the MLET Step1 examination increased by a factor of 16.3 and 12.8 respectively. The minimum GPAs for students from urban and rural backgrounds to pass the examination were estimated from the equation (2.35 vs 2.65 from 4.00 scale). Students from rural backgrounds and/or low-grade point averages in their second and third preclinical years of medical school are at risk of failing the MLET Step1 examination. They should be given intensive tutorials during the second and third pre-clinical years.

  17. Statistical associations between radiation exposure and the clinical examination data of Japanese radiology technicians

    International Nuclear Information System (INIS)

    Kondo, Hisayoshi; Okumura, Yutaka; Aoyama, Takashi; Sugahara, Tsutomu; Hashimoto, Tetsuaki; Yamamoto, Yoichi.

    1995-01-01

    The associations between occupational irradiation, cigarette smoking, alcohol drinking and clinical examination data were investigated in Japanese male radiology technicians. The number of investigated examination items was 35, including 29 biochemical serum test, four hematological tests and systolic and diastolic blood pressure. The associations with each factor were evaluated using the multiple linear regression model. As single factors, radiation associated with urea nitrogen, alkaline phosphatase, monoamine oxidase and leukocyte count (four items), smoking associated with albumin-globulin index, zinc sulfate turbidity test, urea nitrogen, creatinine, neutral fat, amylase, serum iron, leukocyte count, hemoglobin and hematocrit (10 items), and drinking associated with creatinine, uric acid, glutamate oxaloacetate transaminase, leucine aminopeptidase, alkaline phosphatase and erythrocyte count (six items). As synergistic factors, the combination of radiation and smoking associated with nine items, radiation and drinking 10 items, smoking and drinking four items, and radiation, smoking and drinking two items. These results suggested that the number of items which radiation associated as single-factor were less than that of smoking and of drinking, however suggested that associations between radiation and examination data was synergistic when combined with smoking or drinking. (author)

  18. Statistical associations between radiation exposure and the clinical examination data of Japanese radiology technicians

    Energy Technology Data Exchange (ETDEWEB)

    Kondo, Hisayoshi; Okumura, Yutaka [Nagasaki Univ. (Japan). School of Medicine; Aoyama, Takashi; Sugahara, Tsutomu; Hashimoto, Tetsuaki; Yamamoto, Yoichi

    1995-06-01

    The associations between occupational irradiation, cigarette smoking, alcohol drinking and clinical examination data were investigated in Japanese male radiology technicians. The number of investigated examination items was 35, including 29 biochemical serum test, four hematological tests and systolic and diastolic blood pressure. The associations with each factor were evaluated using the multiple linear regression model. As single factors, radiation associated with urea nitrogen, alkaline phosphatase, monoamine oxidase and leukocyte count (four items), smoking associated with albumin-globulin index, zinc sulfate turbidity test, urea nitrogen, creatinine, neutral fat, amylase, serum iron, leukocyte count, hemoglobin and hematocrit (10 items), and drinking associated with creatinine, uric acid, glutamate oxaloacetate transaminase, leucine aminopeptidase, alkaline phosphatase and erythrocyte count (six items). As synergistic factors, the combination of radiation and smoking associated with nine items, radiation and drinking 10 items, smoking and drinking four items, and radiation, smoking and drinking two items. These results suggested that the number of items which radiation associated as single-factor were less than that of smoking and of drinking, however suggested that associations between radiation and examination data was synergistic when combined with smoking or drinking. (author).

  19. Regression of uveal malignant melanomas following cobalt-60 plaque. Correlates between acoustic spectrum analysis and tumor regression

    International Nuclear Information System (INIS)

    Coleman, D.J.; Lizzi, F.L.; Silverman, R.H.; Ellsworth, R.M.; Haik, B.G.; Abramson, D.H.; Smith, M.E.; Rondeau, M.J.

    1985-01-01

    Parameters derived from computer analysis of digital radio-frequency (rf) ultrasound scan data of untreated uveal malignant melanomas were examined for correlations with tumor regression following cobalt-60 plaque. Parameters included tumor height, normalized power spectrum and acoustic tissue type (ATT). Acoustic tissue type was based upon discriminant analysis of tumor power spectra, with spectra of tumors of known pathology serving as a model. Results showed ATT to be correlated with tumor regression during the first 18 months following treatment. Tumors with ATT associated with spindle cell malignant melanoma showed over twice the percentage reduction in height as those with ATT associated with mixed/epithelioid melanomas. Pre-treatment height was only weakly correlated with regression. Additionally, significant spectral changes were observed following treatment. Ultrasonic spectrum analysis thus provides a noninvasive tool for classification, prediction and monitoring of tumor response to cobalt-60 plaque

  20. Differentiating regressed melanoma from regressed lichenoid keratosis.

    Science.gov (United States)

    Chan, Aegean H; Shulman, Kenneth J; Lee, Bonnie A

    2017-04-01

    Distinguishing regressed lichen planus-like keratosis (LPLK) from regressed melanoma can be difficult on histopathologic examination, potentially resulting in mismanagement of patients. We aimed to identify histopathologic features by which regressed melanoma can be differentiated from regressed LPLK. Twenty actively inflamed LPLK, 12 LPLK with regression and 15 melanomas with regression were compared and evaluated by hematoxylin and eosin staining as well as Melan-A, microphthalmia transcription factor (MiTF) and cytokeratin (AE1/AE3) immunostaining. (1) A total of 40% of regressed melanomas showed complete or near complete loss of melanocytes within the epidermis with Melan-A and MiTF immunostaining, while 8% of regressed LPLK exhibited this finding. (2) Necrotic keratinocytes were seen in the epidermis in 33% regressed melanomas as opposed to all of the regressed LPLK. (3) A dense infiltrate of melanophages in the papillary dermis was seen in 40% of regressed melanomas, a feature not seen in regressed LPLK. In summary, our findings suggest that a complete or near complete loss of melanocytes within the epidermis strongly favors a regressed melanoma over a regressed LPLK. In addition, necrotic epidermal keratinocytes and the presence of a dense band-like distribution of dermal melanophages can be helpful in differentiating these lesions. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  1. Association between biomarkers and clinical characteristics in chronic subdural hematoma patients assessed with lasso regression.

    Directory of Open Access Journals (Sweden)

    Are Hugo Pripp

    Full Text Available Chronic subdural hematoma (CSDH is characterized by an "old" encapsulated collection of blood and blood breakdown products between the brain and its outermost covering (the dura. Recognized risk factors for development of CSDH are head injury, old age and using anticoagulation medication, but its underlying pathophysiological processes are still unclear. It is assumed that a complex local process of interrelated mechanisms including inflammation, neomembrane formation, angiogenesis and fibrinolysis could be related to its development and propagation. However, the association between the biomarkers of inflammation and angiogenesis, and the clinical and radiological characteristics of CSDH patients, need further investigation. The high number of biomarkers compared to the number of observations, the correlation between biomarkers, missing data and skewed distributions may limit the usefulness of classical statistical methods. We therefore explored lasso regression to assess the association between 30 biomarkers of inflammation and angiogenesis at the site of lesions, and selected clinical and radiological characteristics in a cohort of 93 patients. Lasso regression performs both variable selection and regularization to improve the predictive accuracy and interpretability of the statistical model. The results from the lasso regression showed analysis exhibited lack of robust statistical association between the biomarkers in hematoma fluid with age, gender, brain infarct, neurological deficiencies and volume of hematoma. However, there were associations between several of the biomarkers with postoperative recurrence requiring reoperation. The statistical analysis with lasso regression supported previous findings that the immunological characteristics of CSDH are local. The relationship between biomarkers, the radiological appearance of lesions and recurrence requiring reoperation have been inclusive using classical statistical methods on these data

  2. [Factors Associated with Stress Check Attendance: Possible Effect of Timing of Annual Health Examination].

    Science.gov (United States)

    Ishimaru, Tomohiro; Hattori, Michihiro; Nagata, Masako; Kuwahara, Keisuke; Watanabe, Seiji; Mori, Koji

    2018-01-01

    The stress check program has been part of annual employees' health screening since 2015. Employees are recommended, but not obliged, to undergo the stress check offered. This study was designed to examine the factors associated with stress check attendance. A total of 31,156 Japanese employees who underwent an annual health examination and a stress check service at an Occupational Health Service Center in 2016 participated in this study. Data from the annual health examination and stress check service included stress check attendance, date of attendance (if implemented), gender, age, workplace industry, number of employees at the workplace, and tobacco and alcohol consumption. Data were analyzed using multiple logistic regression. The mean rate of stress check attendance was 90.8%. A higher rate of stress check attendance was associated with a lower duration from the annual health examination, age ≥30 years, construction and transport industry, and 50-999 employees at the workplace. A lower rate of stress check attendance was associated with medical and welfare industry and ≥1,000 employees at the workplace. These findings provide insights into developing strategies for improving the rate of stress check attendance. In particular, stress check attendance may improve if the stress check service and annual health examination are conducted simultaneously.

  3. A comparison of Cox and logistic regression for use in genome-wide association studies of cohort and case-cohort design.

    Science.gov (United States)

    Staley, James R; Jones, Edmund; Kaptoge, Stephen; Butterworth, Adam S; Sweeting, Michael J; Wood, Angela M; Howson, Joanna M M

    2017-06-01

    Logistic regression is often used instead of Cox regression to analyse genome-wide association studies (GWAS) of single-nucleotide polymorphisms (SNPs) and disease outcomes with cohort and case-cohort designs, as it is less computationally expensive. Although Cox and logistic regression models have been compared previously in cohort studies, this work does not completely cover the GWAS setting nor extend to the case-cohort study design. Here, we evaluated Cox and logistic regression applied to cohort and case-cohort genetic association studies using simulated data and genetic data from the EPIC-CVD study. In the cohort setting, there was a modest improvement in power to detect SNP-disease associations using Cox regression compared with logistic regression, which increased as the disease incidence increased. In contrast, logistic regression had more power than (Prentice weighted) Cox regression in the case-cohort setting. Logistic regression yielded inflated effect estimates (assuming the hazard ratio is the underlying measure of association) for both study designs, especially for SNPs with greater effect on disease. Given logistic regression is substantially more computationally efficient than Cox regression in both settings, we propose a two-step approach to GWAS in cohort and case-cohort studies. First to analyse all SNPs with logistic regression to identify associated variants below a pre-defined P-value threshold, and second to fit Cox regression (appropriately weighted in case-cohort studies) to those identified SNPs to ensure accurate estimation of association with disease.

  4. Factors Associated with Hemorrhoids in Korean Adults: Korean National Health and Nutrition Examination Survey

    OpenAIRE

    Lee, Jong-Hyun; Kim, Hyo-Eun; Kang, Ji-Hun; Shin, Jin-Young; Song, Yun-Mi

    2014-01-01

    Background Although hemorrhoids are one of the most common anal diseases among Koreans, risk factors for hemorrhoids have not been well identified. Methods We analyzed the data from the 4th Korean National Health and Nutrition Examination Survey (KNHANES) between 2007 and 2009. Study subjects were 17,228 participants of KNHANES who were aged 19 years or older. Logistic regression analysis was conducted to evaluate associations between hemorrhoids and probable risk factors. Results Overall pre...

  5. Multivariate and semiparametric kernel regression

    OpenAIRE

    Härdle, Wolfgang; Müller, Marlene

    1997-01-01

    The paper gives an introduction to theory and application of multivariate and semiparametric kernel smoothing. Multivariate nonparametric density estimation is an often used pilot tool for examining the structure of data. Regression smoothing helps in investigating the association between covariates and responses. We concentrate on kernel smoothing using local polynomial fitting which includes the Nadaraya-Watson estimator. Some theory on the asymptotic behavior and bandwidth selection is pro...

  6. Alternative regression models to assess increase in childhood BMI.

    Science.gov (United States)

    Beyerlein, Andreas; Fahrmeir, Ludwig; Mansmann, Ulrich; Toschke, André M

    2008-09-08

    Body mass index (BMI) data usually have skewed distributions, for which common statistical modeling approaches such as simple linear or logistic regression have limitations. Different regression approaches to predict childhood BMI by goodness-of-fit measures and means of interpretation were compared including generalized linear models (GLMs), quantile regression and Generalized Additive Models for Location, Scale and Shape (GAMLSS). We analyzed data of 4967 children participating in the school entry health examination in Bavaria, Germany, from 2001 to 2002. TV watching, meal frequency, breastfeeding, smoking in pregnancy, maternal obesity, parental social class and weight gain in the first 2 years of life were considered as risk factors for obesity. GAMLSS showed a much better fit regarding the estimation of risk factors effects on transformed and untransformed BMI data than common GLMs with respect to the generalized Akaike information criterion. In comparison with GAMLSS, quantile regression allowed for additional interpretation of prespecified distribution quantiles, such as quantiles referring to overweight or obesity. The variables TV watching, maternal BMI and weight gain in the first 2 years were directly, and meal frequency was inversely significantly associated with body composition in any model type examined. In contrast, smoking in pregnancy was not directly, and breastfeeding and parental social class were not inversely significantly associated with body composition in GLM models, but in GAMLSS and partly in quantile regression models. Risk factor specific BMI percentile curves could be estimated from GAMLSS and quantile regression models. GAMLSS and quantile regression seem to be more appropriate than common GLMs for risk factor modeling of BMI data.

  7. Genomic regression of claw keratin, taste receptor and light-associated genes provides insights into biology and evolutionary origins of snakes.

    Science.gov (United States)

    Emerling, Christopher A

    2017-10-01

    Regressive evolution of anatomical traits often corresponds with the regression of genomic loci underlying such characters. As such, studying patterns of gene loss can be instrumental in addressing questions of gene function, resolving conflicting results from anatomical studies, and understanding the evolutionary history of clades. The evolutionary origins of snakes involved the regression of a number of anatomical traits, including limbs, taste buds and the visual system, and by analyzing serpent genomes, I was able to test three hypotheses associated with the regression of these features. The first concerns two keratins that are putatively specific to claws. Both genes that encode these keratins are pseudogenized/deleted in snake genomes, providing additional evidence of claw-specificity. The second hypothesis is that snakes lack taste buds, an issue complicated by conflicting results in the literature. I found evidence that different snakes have lost one or more taste receptors, but all snakes examined retained at least one gustatory channel. The final hypothesis addressed is that the earliest snakes were adapted to a dim light niche. I found evidence of deleted and pseudogenized genes with light-associated functions in snakes, demonstrating a pattern of gene loss similar to other dim light-adapted clades. Molecular dating estimates suggest that dim light adaptation preceded the loss of limbs, providing some bearing on interpretations of the ecological origins of snakes. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Identifying Dietary Patterns Associated with Mild Cognitive Impairment in Older Korean Adults Using Reduced Rank Regression

    Directory of Open Access Journals (Sweden)

    Dayeon Shin

    2018-01-01

    Full Text Available Diet plays a crucial role in cognitive function. Few studies have examined the relationship between dietary patterns and cognitive functions of older adults in the Korean population. This study aimed to identify the effect of dietary patterns on the risk of mild cognitive impairment. A total of 239 participants, including 88 men and 151 women, aged 65 years and older were selected from health centers in the district of Seoul, Gyeonggi province, and Incheon, in Korea. Dietary patterns were determined using Reduced Rank Regression (RRR methods with responses regarding vitamin B6, vitamin C, and iron intakes, based on both a one-day 24-h recall and a food frequency questionnaire. Cognitive function was assessed using the Korean-Mini Mental State Examination (K-MMSE. Multivariable logistic regression models were used to estimate the association between dietary pattern score and the risk of mild cognitive impairment. A total of 20 (8% out of the 239 participants had mild cognitive impairment. Three dietary patterns were identified: seafood and vegetables, high meat, and bread, ham, and alcohol. Among the three dietary patterns, the older adult population who adhered to the seafood and vegetables pattern, characterized by high intake of seafood, vegetables, fruits, bread, snacks, soy products, beans, chicken, pork, ham, egg, and milk had a decreased risk of mild cognitive impairment compared to those who did not (adjusted odds ratios 0.06, 95% confidence interval 0.01–0.72 after controlling for gender, supplementation, education, history of dementia, physical activity, body mass index (BMI, and duration of sleep. The other two dietary patterns were not significantly associated with the risk of mild cognitive impairment. In conclusion, high consumption of fruits, vegetables, seafood, and protein foods was significantly associated with reduced mild cognitive impairment in older Korean adults. These results can contribute to the establishment of

  9. Drusen regression is associated with local changes in fundus autofluorescence in intermediate age-related macular degeneration.

    Science.gov (United States)

    Toy, Brian C; Krishnadev, Nupura; Indaram, Maanasa; Cunningham, Denise; Cukras, Catherine A; Chew, Emily Y; Wong, Wai T

    2013-09-01

    To investigate the association of spontaneous drusen regression in intermediate age-related macular degeneration (AMD) with changes on fundus photography and fundus autofluorescence (FAF) imaging. Prospective observational case series. Fundus images from 58 eyes (in 58 patients) with intermediate AMD and large drusen were assessed over 2 years for areas of drusen regression that exceeded the area of circle C1 (diameter 125 μm; Age-Related Eye Disease Study grading protocol). Manual segmentation and computer-based image analysis were used to detect and delineate areas of drusen regression. Delineated regions were graded as to their appearance on fundus photographs and FAF images, and changes in FAF signal were graded manually and quantitated using automated image analysis. Drusen regression was detected in approximately half of study eyes using manual (48%) and computer-assisted (50%) techniques. At year-2, the clinical appearance of areas of drusen regression on fundus photography was mostly unremarkable, with a majority of eyes (71%) demonstrating no detectable clinical abnormalities, and the remainder (29%) showing minor pigmentary changes. However, drusen regression areas were associated with local changes in FAF that were significantly more prominent than changes on fundus photography. A majority of eyes (64%-66%) demonstrated a predominant decrease in overall FAF signal, while 14%-21% of eyes demonstrated a predominant increase in overall FAF signal. FAF imaging demonstrated that drusen regression in intermediate AMD was often accompanied by changes in local autofluorescence signal. Drusen regression may be associated with concurrent structural and physiologic changes in the outer retina. Published by Elsevier Inc.

  10. Weighted functional linear regression models for gene-based association analysis.

    Science.gov (United States)

    Belonogova, Nadezhda M; Svishcheva, Gulnara R; Wilson, James F; Campbell, Harry; Axenovich, Tatiana I

    2018-01-01

    Functional linear regression models are effectively used in gene-based association analysis of complex traits. These models combine information about individual genetic variants, taking into account their positions and reducing the influence of noise and/or observation errors. To increase the power of methods, where several differently informative components are combined, weights are introduced to give the advantage to more informative components. Allele-specific weights have been introduced to collapsing and kernel-based approaches to gene-based association analysis. Here we have for the first time introduced weights to functional linear regression models adapted for both independent and family samples. Using data simulated on the basis of GAW17 genotypes and weights defined by allele frequencies via the beta distribution, we demonstrated that type I errors correspond to declared values and that increasing the weights of causal variants allows the power of functional linear models to be increased. We applied the new method to real data on blood pressure from the ORCADES sample. Five of the six known genes with P models. Moreover, we found an association between diastolic blood pressure and the VMP1 gene (P = 8.18×10-6), when we used a weighted functional model. For this gene, the unweighted functional and weighted kernel-based models had P = 0.004 and 0.006, respectively. The new method has been implemented in the program package FREGAT, which is freely available at https://cran.r-project.org/web/packages/FREGAT/index.html.

  11. Comparing lagged linear correlation, lagged regression, Granger causality, and vector autoregression for uncovering associations in EHR data.

    Science.gov (United States)

    Levine, Matthew E; Albers, David J; Hripcsak, George

    2016-01-01

    Time series analysis methods have been shown to reveal clinical and biological associations in data collected in the electronic health record. We wish to develop reliable high-throughput methods for identifying adverse drug effects that are easy to implement and produce readily interpretable results. To move toward this goal, we used univariate and multivariate lagged regression models to investigate associations between twenty pairs of drug orders and laboratory measurements. Multivariate lagged regression models exhibited higher sensitivity and specificity than univariate lagged regression in the 20 examples, and incorporating autoregressive terms for labs and drugs produced more robust signals in cases of known associations among the 20 example pairings. Moreover, including inpatient admission terms in the model attenuated the signals for some cases of unlikely associations, demonstrating how multivariate lagged regression models' explicit handling of context-based variables can provide a simple way to probe for health-care processes that confound analyses of EHR data.

  12. Alternative regression models to assess increase in childhood BMI

    Directory of Open Access Journals (Sweden)

    Mansmann Ulrich

    2008-09-01

    Full Text Available Abstract Background Body mass index (BMI data usually have skewed distributions, for which common statistical modeling approaches such as simple linear or logistic regression have limitations. Methods Different regression approaches to predict childhood BMI by goodness-of-fit measures and means of interpretation were compared including generalized linear models (GLMs, quantile regression and Generalized Additive Models for Location, Scale and Shape (GAMLSS. We analyzed data of 4967 children participating in the school entry health examination in Bavaria, Germany, from 2001 to 2002. TV watching, meal frequency, breastfeeding, smoking in pregnancy, maternal obesity, parental social class and weight gain in the first 2 years of life were considered as risk factors for obesity. Results GAMLSS showed a much better fit regarding the estimation of risk factors effects on transformed and untransformed BMI data than common GLMs with respect to the generalized Akaike information criterion. In comparison with GAMLSS, quantile regression allowed for additional interpretation of prespecified distribution quantiles, such as quantiles referring to overweight or obesity. The variables TV watching, maternal BMI and weight gain in the first 2 years were directly, and meal frequency was inversely significantly associated with body composition in any model type examined. In contrast, smoking in pregnancy was not directly, and breastfeeding and parental social class were not inversely significantly associated with body composition in GLM models, but in GAMLSS and partly in quantile regression models. Risk factor specific BMI percentile curves could be estimated from GAMLSS and quantile regression models. Conclusion GAMLSS and quantile regression seem to be more appropriate than common GLMs for risk factor modeling of BMI data.

  13. Association between physical activity and kidney function: National Health and Nutrition Examination Survey.

    Science.gov (United States)

    Hawkins, Marquis S; Sevick, Mary Ann; Richardson, Caroline R; Fried, Linda F; Arena, Vincent C; Kriska, Andrea M

    2011-08-01

    Chronic kidney disease is a condition characterized by the deterioration of the kidney's ability to remove waste products from the body. Although treatments to slow the progression of the disease are available, chronic kidney disease may eventually lead to a complete loss of kidney function. Previous studies have shown that physical activities of moderate intensity may have renal benefits. Few studies have examined the effects of total movement on kidney function. The purpose of this study was to determine the association between time spent at all levels of physical activity intensity and sedentary behavior and kidney function. Data were obtained from the 2003-2004 and 2005-2006 National Health and Nutrition Examination Survey, a cross-sectional study of a complex, multistage probability sample of the US population. Physical activity was assessed using an accelerometer and questionnaire. Glomerular filtration rate (eGFR) was estimated using the Modification of Diet in Renal Disease study formula. To assess linear associations between levels of physical activity and sedentary behavior with log-transformed estimated GFR (eGFR), linear regression was used. In general, physical activity (light and total) was related to log eGFR in females and males. For females, the association between light and total physical activity with log eGFR was consistent regardless of diabetes status. For males, the association between light and total physical activity and log eGFR was only significant in males without diabetes. When examining the association between physical activity, measured objectively with an accelerometer, and kidney function, total and light physical activities were found to be positively associated with kidney function.

  14. Logistic regression analysis of psychosocial correlates associated with recovery from schizophrenia in a Chinese community.

    Science.gov (United States)

    Tse, Samson; Davidson, Larry; Chung, Ka-Fai; Yu, Chong Ho; Ng, King Lam; Tsoi, Emily

    2015-02-01

    More mental health services are adopting the recovery paradigm. This study adds to prior research by (a) using measures of stages of recovery and elements of recovery that were designed and validated in a non-Western, Chinese culture and (b) testing which demographic factors predict advanced recovery and whether placing importance on certain elements predicts advanced recovery. We examined recovery and factors associated with recovery among 75 Hong Kong adults who were diagnosed with schizophrenia and assessed to be in clinical remission. Data were collected on socio-demographic factors, recovery stages and elements associated with recovery. Logistic regression analysis was used to identify variables that could best predict stages of recovery. Receiver operating characteristic curves were used to detect the classification accuracy of the model (i.e. rates of correct classification of stages of recovery). Logistic regression results indicated that stages of recovery could be distinguished with reasonable accuracy for Stage 3 ('living with disability', classification accuracy = 75.45%) and Stage 4 ('living beyond disability', classification accuracy = 75.50%). However, there was no sufficient information to predict Combined Stages 1 and 2 ('overwhelmed by disability' and 'struggling with disability'). It was found that having a meaningful role and age were the most important differentiators of recovery stage. Preliminary findings suggest that adopting salient life roles personally is important to recovery and that this component should be incorporated into mental health services. © The Author(s) 2014.

  15. Early regression of severe left ventricular hypertrophy after transcatheter aortic valve replacement is associated with decreased hospitalizations.

    Science.gov (United States)

    Lindman, Brian R; Stewart, William J; Pibarot, Philippe; Hahn, Rebecca T; Otto, Catherine M; Xu, Ke; Devereux, Richard B; Weissman, Neil J; Enriquez-Sarano, Maurice; Szeto, Wilson Y; Makkar, Raj; Miller, D Craig; Lerakis, Stamatios; Kapadia, Samir; Bowers, Bruce; Greason, Kevin L; McAndrew, Thomas C; Lei, Yang; Leon, Martin B; Douglas, Pamela S

    2014-06-01

    This study sought to examine the relationship between left ventricular mass (LVM) regression and clinical outcomes after transcatheter aortic valve replacement (TAVR). LVM regression after valve replacement for aortic stenosis is assumed to be a favorable effect of LV unloading, but its relationship to improved clinical outcomes is unclear. Of 2,115 patients with symptomatic aortic stenosis at high surgical risk receiving TAVR in the PARTNER (Placement of Aortic Transcatheter Valves) randomized trial or continued access registry, 690 had both severe LV hypertrophy (left ventricular mass index [LVMi] ≥ 149 g/m(2) men, ≥ 122 g/m(2) women) at baseline and an LVMi measurement at 30-day post-TAVR follow-up. Clinical outcomes were compared for patients with greater than versus lesser than median percentage change in LVMi between baseline and 30 days using Cox proportional hazard models to evaluate event rates from 30 to 365 days. Compared with patients with lesser regression, patients with greater LVMi regression had a similar rate of all-cause mortality (14.1% vs. 14.3%, p = 0.99), but a lower rate of rehospitalization (9.5% vs. 18.5%, hazard ratio [HR]: 0.50, 95% confidence interval [CI]: 0.32 to 0.78; p = 0.002) and a lower rate of rehospitalization specifically for heart failure (7.3% vs. 13.6%, p = 0.01). The association with a lower rate of rehospitalization was consistent across subgroups and remained significant after multivariable adjustment (HR: 0.53, 95% CI: 0.34 to 0.84; p = 0.007). Patients with greater LVMi regression had lower B-type natriuretic peptide (p = 0.002) and a trend toward better quality of life (p = 0.06) at 1-year follow-up than did those with lesser regression. In high-risk patients with severe aortic stenosis and severe LV hypertrophy undergoing TAVR, those with greater early LVM regression had one-half the rate of rehospitalization over the subsequent year compared to those with lesser regression. Copyright © 2014 American College of

  16. Normalization Ridge Regression in Practice I: Comparisons Between Ordinary Least Squares, Ridge Regression and Normalization Ridge Regression.

    Science.gov (United States)

    Bulcock, J. W.

    The problem of model estimation when the data are collinear was examined. Though the ridge regression (RR) outperforms ordinary least squares (OLS) regression in the presence of acute multicollinearity, it is not a problem free technique for reducing the variance of the estimates. It is a stochastic procedure when it should be nonstochastic and it…

  17. Examining the association between oral health and oral HPV infection.

    Science.gov (United States)

    Bui, Thanh Cong; Markham, Christine M; Ross, Michael Wallis; Mullen, Patricia Dolan

    2013-09-01

    Oral human papillomavirus (HPV) infection is the cause of 40% to 80% of oropharyngeal cancers; yet, no published study has examined the role of oral health in oral HPV infection, either independently or in conjunction with other risk factors. This study examined the relation between oral health and oral HPV infection and the interactive effects of oral health, smoking, and oral sex on oral HPV infection. Our analyses comprised 3,439 participants ages 30 to 69 years for whom data on oral HPV and oral health were available from the nationally representative 2009-2010 National Health and Nutrition Examination Survey. Results showed that higher unadjusted prevalence of oral HPV infection was associated with four measures of oral health, including self-rated oral health as poor-to-fair [prevalence ratio (PR) = 1.56; 95% confidence interval (CI), 1.25-1.95], indicated the possibility of gum disease (PR = 1.51; 95% CI, 1.13-2.01), reported use of mouthwash to treat dental problems in the past week (PR = 1.28; 95% CI, 1.07-1.52), and higher number of teeth lost (Ptrend = 0.035). In multivariable logistic regression models, oral HPV infection had a statistically significant association with self-rated overall oral health (OR = 1.55; 95% CI, 1.15-2.09), independent of smoking and oral sex. In conclusion, poor oral health was an independent risk factor of oral HPV infection, irrespective of smoking and oral sex practices. Public health interventions may aim to promote oral hygiene and oral health as an additional measure to prevent HPV-related oral cancers.

  18. Multiple Regression Analysis of mRNA-miRNA Associations in Colorectal Cancer Pathway

    Science.gov (United States)

    Wang, Fengfeng; Wong, S. C. Cesar; Chan, Lawrence W. C.; Cho, William C. S.; Yip, S. P.; Yung, Benjamin Y. M.

    2014-01-01

    Background. MicroRNA (miRNA) is a short and endogenous RNA molecule that regulates posttranscriptional gene expression. It is an important factor for tumorigenesis of colorectal cancer (CRC), and a potential biomarker for diagnosis, prognosis, and therapy of CRC. Our objective is to identify the related miRNAs and their associations with genes frequently involved in CRC microsatellite instability (MSI) and chromosomal instability (CIN) signaling pathways. Results. A regression model was adopted to identify the significantly associated miRNAs targeting a set of candidate genes frequently involved in colorectal cancer MSI and CIN pathways. Multiple linear regression analysis was used to construct the model and find the significant mRNA-miRNA associations. We identified three significantly associated mRNA-miRNA pairs: BCL2 was positively associated with miR-16 and SMAD4 was positively associated with miR-567 in the CRC tissue, while MSH6 was positively associated with miR-142-5p in the normal tissue. As for the whole model, BCL2 and SMAD4 models were not significant, and MSH6 model was significant. The significant associations were different in the normal and the CRC tissues. Conclusion. Our results have laid down a solid foundation in exploration of novel CRC mechanisms, and identification of miRNA roles as oncomirs or tumor suppressor mirs in CRC. PMID:24895601

  19. Auto-associative Kernel Regression Model with Weighted Distance Metric for Instrument Drift Monitoring

    International Nuclear Information System (INIS)

    Shin, Ho Cheol; Park, Moon Ghu; You, Skin

    2006-01-01

    Recently, many on-line approaches to instrument channel surveillance (drift monitoring and fault detection) have been reported worldwide. On-line monitoring (OLM) method evaluates instrument channel performance by assessing its consistency with other plant indications through parametric or non-parametric models. The heart of an OLM system is the model giving an estimate of the true process parameter value against individual measurements. This model gives process parameter estimate calculated as a function of other plant measurements which can be used to identify small sensor drifts that would require the sensor to be manually calibrated or replaced. This paper describes an improvement of auto associative kernel regression (AAKR) by introducing a correlation coefficient weighting on kernel distances. The prediction performance of the developed method is compared with conventional auto-associative kernel regression

  20. Assessing the reliability of the borderline regression method as a standard setting procedure for objective structured clinical examination

    Directory of Open Access Journals (Sweden)

    Sara Mortaz Hejri

    2013-01-01

    Full Text Available Background: One of the methods used for standard setting is the borderline regression method (BRM. This study aims to assess the reliability of BRM when the pass-fail standard in an objective structured clinical examination (OSCE was calculated by averaging the BRM standards obtained for each station separately. Materials and Methods: In nine stations of the OSCE with direct observation the examiners gave each student a checklist score and a global score. Using a linear regression model for each station, we calculated the checklist score cut-off on the regression equation for the global scale cut-off set at 2. The OSCE pass-fail standard was defined as the average of all station′s standard. To determine the reliability, the root mean square error (RMSE was calculated. The R2 coefficient and the inter-grade discrimination were calculated to assess the quality of OSCE. Results: The mean total test score was 60.78. The OSCE pass-fail standard and its RMSE were 47.37 and 0.55, respectively. The R2 coefficients ranged from 0.44 to 0.79. The inter-grade discrimination score varied greatly among stations. Conclusion: The RMSE of the standard was very small indicating that BRM is a reliable method of setting standard for OSCE, which has the advantage of providing data for quality assurance.

  1. Isolating and Examining Sources of Suppression and Multicollinearity in Multiple Linear Regression

    Science.gov (United States)

    Beckstead, Jason W.

    2012-01-01

    The presence of suppression (and multicollinearity) in multiple regression analysis complicates interpretation of predictor-criterion relationships. The mathematical conditions that produce suppression in regression analysis have received considerable attention in the methodological literature but until now nothing in the way of an analytic…

  2. Applied logistic regression

    CERN Document Server

    Hosmer, David W; Sturdivant, Rodney X

    2013-01-01

     A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-

  3. Extralobar pulmonary sequestration in neonates: The natural course and predictive factors associated with spontaneous regression

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Hee Mang; Jung, Ah Young; Cho, Young Ah; Yoon, Chong Hyun; Lee, Jin Seong [Asan Medical Center Children' s Hospital, University of Ulsan College of Medicine, Department of Radiology and Research Institute of Radiology, Songpa-gu, Seoul (Korea, Republic of); Kim, Ellen Ai-Rhan [University of Ulsan College of Medicine, Division of Neonatology, Asan Medical Center Children' s Hospital, Seoul (Korea, Republic of); Chung, Sung-Hoon [Kyung Hee University School of Medicine, Department of Pediatrics, Seoul (Korea, Republic of); Kim, Seon-Ok [Asan Medical Center, Department of Clinical Epidemiology and Biostatistics, Seoul (Korea, Republic of)

    2017-06-15

    To describe the natural course of extralobar pulmonary sequestration (EPS) and identify factors associated with spontaneous regression of EPS. We retrospectively searched for patients diagnosed with EPS on initial contrast CT scan within 1 month after birth and had a follow-up CT scan without treatment. Spontaneous regression of EPS was assessed by percentage decrease in volume (PDV) and percentage decrease in sum of the diameter of systemic feeding arteries (PDD) by comparing initial and follow-up CT scans. Clinical and CT features were analysed to determine factors associated with PDV and PDD rates. Fifty-one neonates were included. The cumulative proportions of patients reaching PDV > 50 % and PDD > 50 % were 93.0 % and 73.3 % at 4 years, respectively. Tissue attenuation was significantly associated with PDV rate (B = -21.78, P <.001). The tissue attenuation (B = -22.62, P =.001) and diameter of the largest systemic feeding arteries (B = -48.31, P =.011) were significant factors associated with PDD rate. The volume and diameter of systemic feeding arteries of EPS spontaneously decreased within 4 years without treatment. EPSs showing a low tissue attenuation and small diameter of the largest systemic feeding arteries on initial contrast-enhanced CT scans were likely to regress spontaneously. (orig.)

  4. Associations of neighborhood disorganization and maternal spanking with children's aggression: A fixed-effects regression analysis.

    Science.gov (United States)

    Ma, Julie; Grogan-Kaylor, Andrew; Lee, Shawna J

    2018-02-01

    This study employed fixed effects regression that controls for selection bias, omitted variables bias, and all time-invariant aspects of parent and child characteristics to examine the simultaneous associations between neighborhood disorganization, maternal spanking, and aggressive behavior in early childhood using data from the Fragile Families and Child Wellbeing Study (FFCWS). Analysis was based on 2,472 children and their mothers who participated in Wave 3 (2001-2003; child age 3) and Wave 4 (2003-2006; child age 5) of the FFCWS. Results indicated that higher rates of neighborhood crime and violence predicted higher levels of child aggression. Maternal spanking in the past year, whether frequent or infrequent, was also associated with increases in aggressive behavior. This study contributes statistically rigorous evidence that exposure to violence in the neighborhood as well as the family context are predictors of child aggression. We conclude with a discussion for the need for multilevel prevention and intervention approaches that target both community and parenting factors. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  5. Association between sleep quality and C-reactive protein: results from national health and nutrition examination survey, 2005-2008.

    Directory of Open Access Journals (Sweden)

    Rong Liu

    Full Text Available OBJECTIVE: Our objective was to explore the association between poor sleep quality and hs_CRP in an adult U.S. population. METHODS: This study focused on 9,317 participants in the National Health and Nutrition Examination Survey (NHANES from 2005-2008 who were aged 20-85 years, completed a sleep disorder questionnaire, and had available information on serum hs_CRP. Sleep quality was classified into three categories (good, moderate, poor based on the responses of participants to the NHANES sleep disorder questionnaire. High CRP was defined as hs-CRP >1 md/dL. Linear regression model was applied to investigate the association between poor sleep quality and log-transformed hs_CRP. And logistic regression model was fitted to evaluate the association between sleep quality and the risk of high CRP. RESULTS: Females were more likely to report poor sleep quality than males (26% vs. 19%, p<0.0001. Each sleep disorder was significantly associated with increased hs_CRP and correlative to other sleep disorders. In fully-adjusted linear regression model, poor sleep quality was significantly associated with elevated hs_CRP (log transformed among the overall sample and in females only (β = 0.10, se = 0.03, p<0.01 and β = 0.13, se = 0.04, p<0.01, respectively. In fully-adjusted logistics regression model, poor sleep quality was linked with risk of high CRP(OR: 1.42, 95%CI: 1.15-1.76 in overall sample and OR: 1.59, 95%CI: 1.18-2.14 in females, respectively. CONCLUSION: We found that poor sleep quality was independently associated with elevated hs_CRP in females but not in males in a U.S. adult population.

  6. Neighborhood social capital and crime victimization: comparison of spatial regression analysis and hierarchical regression analysis.

    Science.gov (United States)

    Takagi, Daisuke; Ikeda, Ken'ichi; Kawachi, Ichiro

    2012-11-01

    Crime is an important determinant of public health outcomes, including quality of life, mental well-being, and health behavior. A body of research has documented the association between community social capital and crime victimization. The association between social capital and crime victimization has been examined at multiple levels of spatial aggregation, ranging from entire countries, to states, metropolitan areas, counties, and neighborhoods. In multilevel analysis, the spatial boundaries at level 2 are most often drawn from administrative boundaries (e.g., Census tracts in the U.S.). One problem with adopting administrative definitions of neighborhoods is that it ignores spatial spillover. We conducted a study of social capital and crime victimization in one ward of Tokyo city, using a spatial Durbin model with an inverse-distance weighting matrix that assigned each respondent a unique level of "exposure" to social capital based on all other residents' perceptions. The study is based on a postal questionnaire sent to 20-69 years old residents of Arakawa Ward, Tokyo. The response rate was 43.7%. We examined the contextual influence of generalized trust, perceptions of reciprocity, two types of social network variables, as well as two principal components of social capital (constructed from the above four variables). Our outcome measure was self-reported crime victimization in the last five years. In the spatial Durbin model, we found that neighborhood generalized trust, reciprocity, supportive networks and two principal components of social capital were each inversely associated with crime victimization. By contrast, a multilevel regression performed with the same data (using administrative neighborhood boundaries) found generally null associations between neighborhood social capital and crime. Spatial regression methods may be more appropriate for investigating the contextual influence of social capital in homogeneous cultural settings such as Japan. Copyright

  7. Sequential Participation in a Multi-Institutional Mock Oral Examination Is Associated With Improved American Board of Surgery Certifying Examination First-Time Pass Rate.

    Science.gov (United States)

    Fingeret, Abbey L; Arnell, Tracey; McNelis, John; Statter, Mindy; Dresner, Lisa; Widmann, Warren

    We sought to determine whether sequential participation in a multi-institutional mock oral examination affected the likelihood of passing the American Board of Surgery Certifying Examination (ABSCE) in first attempt. Residents from 3 academic medical centers were able to participate in a regional mock oral examination in the fall and spring of their fourth and fifth postgraduate year from 2011 to 2014. Candidate׳s highest composite score of all mock orals attempts was classified as risk for failure, intermediate, or likely to pass. Factors including United States Medical Licensing Examination steps 1, 2, and 3, number of cases logged, American Board of Surgery In-Training Examination performance, American Board of Surgery Qualifying Examination (ABSQE) performance, number of attempts, and performance in the mock orals were assessed to determine factors predictive of passing the ABSCE. A total of 128 mock oral examinations were administered to 88 (71%) of 124 eligible residents. The overall first-time pass rate for the ABSCE was 82%. There was no difference in pass rates between participants and nonparticipants. Of them, 16 (18%) residents were classified as at risk, 47 (53%) as intermediate, and 25 (29%) as likely to pass. ABSCE pass rate for each group was as follows: 36% for at risk, 84% for intermediate, and 96% for likely pass. The following 4 factors were associated with first-time passing of ABSCE on bivariate analysis: mock orals participation in postgraduate year 4 (p = 0.05), sequential participation in mock orals (p = 0.03), ABSQE performance (p = 0.01), and best performance on mock orals (p = 0.001). In multivariable logistic regression, the following 3 factors remained associated with ABSCE passing: ABSQE performance, odds ratio (OR) = 2.9 (95% CI: 1.3-6.1); mock orals best performance, OR = 1.7 (1.2-2.4); and participation in multiple mock oral examinations, OR = 1.4 (1.1-2.7). Performance on a multi-institutional mock oral examination can identify

  8. The Overall Odds Ratio as an Intuitive Effect Size Index for Multiple Logistic Regression: Examination of Further Refinements

    Science.gov (United States)

    Le, Huy; Marcus, Justin

    2012-01-01

    This study used Monte Carlo simulation to examine the properties of the overall odds ratio (OOR), which was recently introduced as an index for overall effect size in multiple logistic regression. It was found that the OOR was relatively independent of study base rate and performed better than most commonly used R-square analogs in indexing model…

  9. Integration of least angle regression with empirical Bayes for multi-locus genome-wide association studies

    Science.gov (United States)

    Multi-locus genome-wide association studies has become the state-of-the-art procedure to identify quantitative trait loci (QTL) associated with traits simultaneously. However, implementation of multi-locus model is still difficult. In this study, we integrated least angle regression with empirical B...

  10. Regression analysis by example

    CERN Document Server

    Chatterjee, Samprit

    2012-01-01

    Praise for the Fourth Edition: ""This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."" -Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded

  11. Using reduced rank regression methods to identify dietary patterns associated with obesity: a cross-country study among European and Australian adolescents.

    Science.gov (United States)

    Huybrechts, Inge; Lioret, Sandrine; Mouratidou, Theodora; Gunter, Marc J; Manios, Yannis; Kersting, Mathilde; Gottrand, Frederic; Kafatos, Anthony; De Henauw, Stefaan; Cuenca-García, Magdalena; Widhalm, Kurt; Gonzales-Gross, Marcela; Molnar, Denes; Moreno, Luis A; McNaughton, Sarah A

    2017-01-01

    This study aims to examine repeatability of reduced rank regression (RRR) methods in calculating dietary patterns (DP) and cross-sectional associations with overweight (OW)/obesity across European and Australian samples of adolescents. Data from two cross-sectional surveys in Europe (2006/2007 Healthy Lifestyle in Europe by Nutrition in Adolescence study, including 1954 adolescents, 12-17 years) and Australia (2007 National Children's Nutrition and Physical Activity Survey, including 1498 adolescents, 12-16 years) were used. Dietary intake was measured using two non-consecutive, 24-h recalls. RRR was used to identify DP using dietary energy density, fibre density and percentage of energy intake from fat as the intermediate variables. Associations between DP scores and body mass/fat were examined using multivariable linear and logistic regression as appropriate, stratified by sex. The first DP extracted (labelled 'energy dense, high fat, low fibre') explained 47 and 31 % of the response variation in Australian and European adolescents, respectively. It was similar for European and Australian adolescents and characterised by higher consumption of biscuits/cakes, chocolate/confectionery, crisps/savoury snacks, sugar-sweetened beverages, and lower consumption of yogurt, high-fibre bread, vegetables and fresh fruit. DP scores were inversely associated with BMI z-scores in Australian adolescent boys and borderline inverse in European adolescent boys (so as with %BF). Similarly, a lower likelihood for OW in boys was observed with higher DP scores in both surveys. No such relationships were observed in adolescent girls. In conclusion, the DP identified in this cross-country study was comparable for European and Australian adolescents, demonstrating robustness of the RRR method in calculating DP among populations. However, longitudinal designs are more relevant when studying diet-obesity associations, to prevent reverse causality.

  12. Logic regression and its extensions.

    Science.gov (United States)

    Schwender, Holger; Ruczinski, Ingo

    2010-01-01

    Logic regression is an adaptive classification and regression procedure, initially developed to reveal interacting single nucleotide polymorphisms (SNPs) in genetic association studies. In general, this approach can be used in any setting with binary predictors, when the interaction of these covariates is of primary interest. Logic regression searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome variable, and thus, reveals variables and interactions that are associated with the response and/or have predictive capabilities. The logic expressions are embedded in a generalized linear regression framework, and thus, logic regression can handle a variety of outcome types, such as binary responses in case-control studies, numeric responses, and time-to-event data. In this chapter, we provide an introduction to the logic regression methodology, list some applications in public health and medicine, and summarize some of the direct extensions and modifications of logic regression that have been proposed in the literature. Copyright © 2010 Elsevier Inc. All rights reserved.

  13. Regression Association Analysis of Yield-Related Traits with RAPD Molecular Markers in Pistachio (Pistacia vera L.

    Directory of Open Access Journals (Sweden)

    Saeid Mirzaei

    2017-10-01

    Full Text Available Introduction: The pistachio (Pistacia vera, a member of the cashew family, is a small tree originating from Central Asia and the Middle East. The tree produces seeds that are widely consumed as food. Pistacia vera often is confused with other species in the genus Pistacia that are also known as pistachio. These other species can be distinguished by their geographic distributions and their seeds which are much smaller and have a soft shell. Continual advances in crop improvement through plant breeding are driven by the available genetic diversity. Therefore, the recognition and measurement of such diversity is crucial to breeding programs. In the past 20 years, the major effort in plant breeding has changed from quantitative to molecular genetics with emphasis on quantitative trait loci (QTL identification and marker assisted selection (MAS. The germplasm-regression-combined association studies not only allow mapping of genes/QTLs with higher level of confidence, but also allow detection of genes/QTLs, which will otherwise escape detection in linkage-based QTL studies based on the planned populations. The development of the marker-based technology offers a fast, reliable, and easy way to perform multiple regression analysis and comprise an alternative approach to breeding in diverse species of plants. The availability of many makers and morphological traits can help to regression analysis between these markers and morphological traits. Materials and Methods: In this study, 20 genotypes of Pistachio were studied and yield related traits were measured. Young well-expanded leaves were collected for DNA extraction and total genomic DNA was extracted. Genotyping was performed using 15 RAPD primers and PCR amplification products were visualized by gel electrophoresis. The reproducible RAPD fragments were scored on the basis of present (1 or absent (0 bands and a binary matrix constructed using each molecular marker. Association analysis between

  14. Return-Volatility Relationship: Insights from Linear and Non-Linear Quantile Regression

    NARCIS (Netherlands)

    D.E. Allen (David); A.K. Singh (Abhay); R.J. Powell (Robert); M.J. McAleer (Michael); J. Taylor (James); L. Thomas (Lyn)

    2013-01-01

    textabstractThe purpose of this paper is to examine the asymmetric relationship between price and implied volatility and the associated extreme quantile dependence using linear and non linear quantile regression approach. Our goal in this paper is to demonstrate that the relationship between the

  15. Using Gamma and Quantile Regressions to Explore the Association between Job Strain and Adiposity in the ELSA-Brasil Study: Does Gender Matter?

    Science.gov (United States)

    Fonseca, Maria de Jesus Mendes da; Juvanhol, Leidjaira Lopes; Rotenberg, Lúcia; Nobre, Aline Araújo; Griep, Rosane Härter; Alves, Márcia Guimarães de Mello; Cardoso, Letícia de Oliveira; Giatti, Luana; Nunes, Maria Angélica; Aquino, Estela M L; Chor, Dóra

    2017-11-17

    This paper explores the association between job strain and adiposity, using two statistical analysis approaches and considering the role of gender. The research evaluated 11,960 active baseline participants (2008-2010) in the ELSA-Brasil study. Job strain was evaluated through a demand-control questionnaire, while body mass index (BMI) and waist circumference (WC) were evaluated in continuous form. The associations were estimated using gamma regression models with an identity link function. Quantile regression models were also estimated from the final set of co-variables established by gamma regression. The relationship that was found varied by analytical approach and gender. Among the women, no association was observed between job strain and adiposity in the fitted gamma models. In the quantile models, a pattern of increasing effects of high strain was observed at higher BMI and WC distribution quantiles. Among the men, high strain was associated with adiposity in the gamma regression models. However, when quantile regression was used, that association was found not to be homogeneous across outcome distributions. In addition, in the quantile models an association was observed between active jobs and BMI. Our results point to an association between job strain and adiposity, which follows a heterogeneous pattern. Modelling strategies can produce different results and should, accordingly, be used to complement one another.

  16. Understanding logistic regression analysis

    OpenAIRE

    Sperandei, Sandro

    2014-01-01

    Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using ex...

  17. Examining the associations between emotion regulation difficulties, anxiety, and eating disorder severity among inpatients with anorexia nervosa.

    Science.gov (United States)

    Haynos, Ann F; Roberto, Christina A; Attia, Evelyn

    2015-07-01

    There is growing interest in the role of emotion regulation in anorexia nervosa (AN). Although anxiety is also hypothesized to impact symptoms of AN, little is known about how emotion regulation, anxiety, and eating disorder symptoms interact in AN. In this study, we examined the associations between emotion regulation, anxiety, and eating disorder symptom severity in AN. Questionnaires and interviews assessing emotion regulation difficulties, anxiety, eating disorder symptoms, and eating disorder-related clinical impairment were collected from group of underweight individuals with AN (n=59) at admission to inpatient treatment. Hierarchical linear regressions were used to examine the associations of emotion regulation difficulties, anxiety, and the interaction of these constructs with eating disorder symptoms and eating disorder-related clinical impairment. Emotion regulation difficulties were significantly positively associated with eating disorder symptoms and related clinical impairment only when anxiety levels were low and anxiety was significantly positively associated with eating disorder symptoms and related clinical impairment only when emotion regulation problems were not elevated. This study adds to a growing literature suggesting that emotion regulation deficits are associated with eating disorder symptoms in AN. Certain individuals with AN may especially benefit from a focus on developing emotion regulation skills in the acute stages of illness. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. No rationale for 1 variable per 10 events criterion for binary logistic regression analysis.

    Science.gov (United States)

    van Smeden, Maarten; de Groot, Joris A H; Moons, Karel G M; Collins, Gary S; Altman, Douglas G; Eijkemans, Marinus J C; Reitsma, Johannes B

    2016-11-24

    Ten events per variable (EPV) is a widely advocated minimal criterion for sample size considerations in logistic regression analysis. Of three previous simulation studies that examined this minimal EPV criterion only one supports the use of a minimum of 10 EPV. In this paper, we examine the reasons for substantial differences between these extensive simulation studies. The current study uses Monte Carlo simulations to evaluate small sample bias, coverage of confidence intervals and mean square error of logit coefficients. Logistic regression models fitted by maximum likelihood and a modified estimation procedure, known as Firth's correction, are compared. The results show that besides EPV, the problems associated with low EPV depend on other factors such as the total sample size. It is also demonstrated that simulation results can be dominated by even a few simulated data sets for which the prediction of the outcome by the covariates is perfect ('separation'). We reveal that different approaches for identifying and handling separation leads to substantially different simulation results. We further show that Firth's correction can be used to improve the accuracy of regression coefficients and alleviate the problems associated with separation. The current evidence supporting EPV rules for binary logistic regression is weak. Given our findings, there is an urgent need for new research to provide guidance for supporting sample size considerations for binary logistic regression analysis.

  19. Is frequency of family meals associated with fruit and vegetable intake among preschoolers? A logistic regression analysis.

    Science.gov (United States)

    Caldwell, A R; Terhorst, L; Skidmore, E R; Bendixen, R M

    2018-01-23

    The present study aimed to examine the associations between frequency of family meals and low fruit and vegetable intake in preschool children. Promoting healthy nutrition early in life is recommended for combating childhood obesity. Frequency of family meals is associated with fruit and vegetable intake in school-age children and adolescents; the relationship in young children is less clear. We completed a secondary analysis using data from the Early Childhood Longitudinal Study-Birth Cohort. Participants included children, born in the year 2001, to mothers who were >15 years old (n = 8 950). Data were extracted from structured parent interviews during the year prior to kindergarten. We used hierarchical logistic regression to describe the relationships between frequency of family meals and low fruit and vegetable intake. Frequency of family meals was associated with low fruit and vegetable intake. The odds of low fruit and vegetable intake were greater for preschoolers who shared less than three evening family meals per week (odds ratio = 1.5, β = 0.376, P meal with family every night. Fruit and vegetable intake is related to frequency of family meals in preschool-age children. Educating parents about the potential benefits of frequent shared meals may lead to a higher fruit and vegetable consumption among preschoolers. Future studies should address other factors that likely contribute to eating patterns during the preschool years. © 2018 The British Dietetic Association Ltd.

  20. Examining the Association Between School Vending Machines and Children's Body Mass Index by Socioeconomic Status.

    Science.gov (United States)

    O'Hara, Jeffrey K; Haynes-Maslow, Lindsey

    2015-01-01

    To examine the association between vending machine availability in schools and body mass index (BMI) among subgroups of children based on gender, race/ethnicity, and socioeconomic status classifications. First-difference multivariate regressions were estimated using longitudinal fifth- and eighth-grade data from the Early Childhood Longitudinal Study. The specifications were disaggregated by gender, race/ethnicity, and family socioeconomic status classifications. Vending machine availability had a positive association (P < .10) with BMI among Hispanic male children and low-income Hispanic children. Living in an urban location (P < .05) and hours watching television (P < .05) were also positively associated with BMI for these subgroups. Supplemental Nutrition Assistance Program enrollment was negatively associated with BMI for low-income Hispanic students (P < .05). These findings were not statistically significant when using Bonferroni adjusted critical values. The results suggest that the school food environment could reinforce health disparities that exist for Hispanic male children and low-income Hispanic children. Copyright © 2015 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

  1. [Logistic regression model of noninvasive prediction for portal hypertensive gastropathy in patients with hepatitis B associated cirrhosis].

    Science.gov (United States)

    Wang, Qingliang; Li, Xiaojie; Hu, Kunpeng; Zhao, Kun; Yang, Peisheng; Liu, Bo

    2015-05-12

    To explore the risk factors of portal hypertensive gastropathy (PHG) in patients with hepatitis B associated cirrhosis and establish a Logistic regression model of noninvasive prediction. The clinical data of 234 hospitalized patients with hepatitis B associated cirrhosis from March 2012 to March 2014 were analyzed retrospectively. The dependent variable was the occurrence of PHG while the independent variables were screened by binary Logistic analysis. Multivariate Logistic regression was used for further analysis of significant noninvasive independent variables. Logistic regression model was established and odds ratio was calculated for each factor. The accuracy, sensitivity and specificity of model were evaluated by the curve of receiver operating characteristic (ROC). According to univariate Logistic regression, the risk factors included hepatic dysfunction, albumin (ALB), bilirubin (TB), prothrombin time (PT), platelet (PLT), white blood cell (WBC), portal vein diameter, spleen index, splenic vein diameter, diameter ratio, PLT to spleen volume ratio, esophageal varices (EV) and gastric varices (GV). Multivariate analysis showed that hepatic dysfunction (X1), TB (X2), PLT (X3) and splenic vein diameter (X4) were the major occurring factors for PHG. The established regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4. The accuracy of model for PHG was 79.1% with a sensitivity of 77.2% and a specificity of 80.8%. Hepatic dysfunction, TB, PLT and splenic vein diameter are risk factors for PHG and the noninvasive predicted Logistic regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4.

  2. Spontaneous Regression of Choroidal Neovascularization in a Patient with Pattern Dystrophy

    Directory of Open Access Journals (Sweden)

    Anastasios Anastasakis

    2016-01-01

    Full Text Available Purpose. To present a case of a patient with pattern dystrophy (PD associated choroidal neovascularization (CNV that resolved spontaneously without treatment. Methods. A 69-year-old male patient was referred to our unit, for evaluation of a recent visual loss (metamorphopsias in his left eye. Fundus examination, fundus autofluorescence imaging, and fluorescein angiography showed a choroidal neovascular membrane in his left eye. Since visual acuity was satisfactory the patient elected observation. Clinical examination and OCT testing were repeated at 6 and 12 months after presentation. Results. Visual acuity remained stable at the level of 0.9 (baseline BCVA during the follow-up period (12 months. Repeat OCT testing showed complete spontaneous regression of the choroidal neovascular membrane without evidence of intra- or subretinal fluid in both follow-up visits. Conclusions. Spontaneous regression of choroidal neovascularization can occur in patients with retinal dystrophies and associated choroidal neovascular membranes. The decision to treat or observe these patients relies strongly on the presenting visual acuity, since, in isolated instances, spontaneous resolution of choroidal neovascularization may occur.

  3. Spontaneous regression of a congenital melanocytic nevus

    Directory of Open Access Journals (Sweden)

    Amiya Kumar Nath

    2011-01-01

    Full Text Available Congenital melanocytic nevus (CMN may rarely regress which may also be associated with a halo or vitiligo. We describe a 10-year-old girl who presented with CMN on the left leg since birth, which recently started to regress spontaneously with associated depigmentation in the lesion and at a distant site. Dermoscopy performed at different sites of the regressing lesion demonstrated loss of epidermal pigments first followed by loss of dermal pigments. Histopathology and Masson-Fontana stain demonstrated lymphocytic infiltration and loss of pigment production in the regressing area. Immunohistochemistry staining (S100 and HMB-45, however, showed that nevus cells were present in the regressing areas.

  4. Bayesian logistic regression in detection of gene-steroid interaction for cancer at PDLIM5 locus.

    Science.gov (United States)

    Wang, Ke-Sheng; Owusu, Daniel; Pan, Yue; Xie, Changchun

    2016-06-01

    The PDZ and LIM domain 5 (PDLIM5) gene may play a role in cancer, bipolar disorder, major depression, alcohol dependence and schizophrenia; however, little is known about the interaction effect of steroid and PDLIM5 gene on cancer. This study examined 47 single-nucleotide polymorphisms (SNPs) within the PDLIM5 gene in the Marshfield sample with 716 cancer patients (any diagnosed cancer, excluding minor skin cancer) and 2848 noncancer controls. Multiple logistic regression model in PLINK software was used to examine the association of each SNP with cancer. Bayesian logistic regression in PROC GENMOD in SAS statistical software, ver. 9.4 was used to detect gene- steroid interactions influencing cancer. Single marker analysis using PLINK identified 12 SNPs associated with cancer (Plogistic regression in PROC GENMOD showed that both rs6532496 and rs951613 revealed strong gene-steroid interaction effects (OR=2.18, 95% CI=1.31-3.63 with P = 2.9 × 10⁻³ for rs6532496 and OR=2.07, 95% CI=1.24-3.45 with P = 5.43 × 10⁻³ for rs951613, respectively). Results from Bayesian logistic regression showed stronger interaction effects (OR=2.26, 95% CI=1.2-3.38 for rs6532496 and OR=2.14, 95% CI=1.14-3.2 for rs951613, respectively). All the 12 SNPs associated with cancer revealed significant gene-steroid interaction effects (P logistic regression and OR=2.59, 95% CI=1.4-3.97 from Bayesian logistic regression; respectively). This study provides evidence of common genetic variants within the PDLIM5 gene and interactions between PLDIM5 gene polymorphisms and steroid use influencing cancer.

  5. Examining the Associations Among Home-School Dissonance, Amotivation, and Classroom Disruptive Behavior for Urban High School Students.

    Science.gov (United States)

    Brown-Wright, Lynda; Tyler, Kenneth M; Graves, Scott L; Thomas, Deneia; Stevens-Watkins, Danelle; Mulder, Shambra

    2013-01-01

    The current study examined the association among home-school dissonance, amotivation, and classroom disruptive behavior among 309 high school juniors and seniors at two urban high schools in the Southern region of the country. Students completed two subscales of the Patterns of Learning Activities Scales (PALS) and one subscale of the Academic Motivation Scale (AMS). ANCOVA analyses revealed significant differences in classroom disruptive behaviors for the gender independent variable. Controlling for gender in the multiple hierarchical regression analyses, it was revealed that home-school dissonance significantly predicted both amotivation and classroom disruptive behavior. In addition, a Sobel mediation analysis showed that amotivation was a significant mediator of the association between home-school dissonance and classroom disruptive behavior. Findings and limitations are discussed.

  6. Examining the Associations Among Home–School Dissonance, Amotivation, and Classroom Disruptive Behavior for Urban High School Students

    Science.gov (United States)

    Brown-Wright, Lynda; Tyler, Kenneth M.; Graves, Scott L.; Thomas, Deneia; Stevens-Watkins, Danelle; Mulder, Shambra

    2015-01-01

    The current study examined the association among home–school dissonance, amotivation, and classroom disruptive behavior among 309 high school juniors and seniors at two urban high schools in the Southern region of the country. Students completed two subscales of the Patterns of Learning Activities Scales (PALS) and one subscale of the Academic Motivation Scale (AMS). ANCOVA analyses revealed significant differences in classroom disruptive behaviors for the gender independent variable. Controlling for gender in the multiple hierarchical regression analyses, it was revealed that home–school dissonance significantly predicted both amotivation and classroom disruptive behavior. In addition, a Sobel mediation analysis showed that amotivation was a significant mediator of the association between home–school dissonance and classroom disruptive behavior. Findings and limitations are discussed. PMID:27081213

  7. Family characteristics and parents' and children's health behaviour are associated with public health nurses' concerns at children's health examinations.

    Science.gov (United States)

    Poutiainen, Hannele; Hakulinen, Tuovi; Mäki, Päivi; Laatikainen, Tiina

    2016-12-01

    The study aimed to establish whether family characteristics and the health behaviour and illnesses of parents and children are associated with public health nurses' (PHNs') concerns about children's physical health and psychosocial development in the context of health examinations. Factors affecting children's health and well-being should be identified as early as possible to provide children and families appropriate support. In 2007-2009, a cross-sectional study in Finland collected information about PHNs' concerns, children's health and well-being as well as the background factors affecting them during health examinations of preschool-age children and school-aged children (n = 4795). Associations between family characteristics, parents' and children's behaviour and diseases, and PHNs' concerns were assessed using logistic regression analysis. Overweight in children, the long-term illnesses of both children and parents, and parental smoking were the factors most strongly associated with PHNs' concerns about a child's physical health whereas non-nuclear family types, the father's low educational level and unemployment, the child's lack of sleep, and bullying were associated with concerns about the child's psychosocial development. The connections found demonstrate that health examinations should address factors that affect the whole family's well-being so as to comprehensively promote children's health, growth and development. © 2016 John Wiley & Sons Australia, Ltd.

  8. Regression: The Apple Does Not Fall Far From the Tree.

    Science.gov (United States)

    Vetter, Thomas R; Schober, Patrick

    2018-05-15

    Researchers and clinicians are frequently interested in either: (1) assessing whether there is a relationship or association between 2 or more variables and quantifying this association; or (2) determining whether 1 or more variables can predict another variable. The strength of such an association is mainly described by the correlation. However, regression analysis and regression models can be used not only to identify whether there is a significant relationship or association between variables but also to generate estimations of such a predictive relationship between variables. This basic statistical tutorial discusses the fundamental concepts and techniques related to the most common types of regression analysis and modeling, including simple linear regression, multiple regression, logistic regression, ordinal regression, and Poisson regression, as well as the common yet often underrecognized phenomenon of regression toward the mean. The various types of regression analysis are powerful statistical techniques, which when appropriately applied, can allow for the valid interpretation of complex, multifactorial data. Regression analysis and models can assess whether there is a relationship or association between 2 or more observed variables and estimate the strength of this association, as well as determine whether 1 or more variables can predict another variable. Regression is thus being applied more commonly in anesthesia, perioperative, critical care, and pain research. However, it is crucial to note that regression can identify plausible risk factors; it does not prove causation (a definitive cause and effect relationship). The results of a regression analysis instead identify independent (predictor) variable(s) associated with the dependent (outcome) variable. As with other statistical methods, applying regression requires that certain assumptions be met, which can be tested with specific diagnostics.

  9. Sociodemographic Differences in the Association Between Obesity and Stress: A Propensity Score-Matched Analysis from the Korean National Health and Nutrition Examination Survey (KNHANES).

    Science.gov (United States)

    Mak, Kwok-Kei; Kim, Dae-Hwan; Leigh, J Paul

    2015-01-01

    Few population-based studies have used an econometric approach to understand the association between two cancer risk factors, obesity and stress. This study investigated sociodemographic differences in the association between obesity and stress among Korean adults (6,546 men and 8,473 women). Data were drawn from the Korean National Health and Nutrition Examination Survey for 2008, 2009, and 2010. Ordered logistic regression models and propensity score matching methods were used to examine the associations between obesity and stress, stratified by gender and age groups. In women, the stress level of the obese group was found to be 27.6% higher than the nonobese group in the ordered logistic regression; the obesity effect on stress was statistically significant in the propensity score-matched analysis. Corresponding evidence for the effect of obesity on stress was lacking among men. Participants who were young, well-educated, and working were more likely to report stress. In Korea, obesity causes stress in women but not in men. Young women are susceptible to a disproportionate level of stress. More cancer prevention programs targeting young and obese women are encouraged in developed Asian countries.

  10. Association between response rates and survival outcomes in patients with newly diagnosed multiple myeloma. A systematic review and meta-regression analysis.

    Science.gov (United States)

    Mainou, Maria; Madenidou, Anastasia-Vasiliki; Liakos, Aris; Paschos, Paschalis; Karagiannis, Thomas; Bekiari, Eleni; Vlachaki, Efthymia; Wang, Zhen; Murad, Mohammad Hassan; Kumar, Shaji; Tsapas, Apostolos

    2017-06-01

    We performed a systematic review and meta-regression analysis of randomized control trials to investigate the association between response to initial treatment and survival outcomes in patients with newly diagnosed multiple myeloma (MM). Response outcomes included complete response (CR) and the combined outcome of CR or very good partial response (VGPR), while survival outcomes were overall survival (OS) and progression-free survival (PFS). We used random-effect meta-regression models and conducted sensitivity analyses based on definition of CR and study quality. Seventy-two trials were included in the systematic review, 63 of which contributed data in meta-regression analyses. There was no association between OS and CR in patients without autologous stem cell transplant (ASCT) (regression coefficient: .02, 95% confidence interval [CI] -0.06, 0.10), in patients undergoing ASCT (-.11, 95% CI -0.44, 0.22) and in trials comparing ASCT with non-ASCT patients (.04, 95% CI -0.29, 0.38). Similarly, OS did not correlate with the combined metric of CR or VGPR, and no association was evident between response outcomes and PFS. Sensitivity analyses yielded similar results. This meta-regression analysis suggests that there is no association between conventional response outcomes and survival in patients with newly diagnosed MM. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  11. Gibrat’s law and quantile regressions

    DEFF Research Database (Denmark)

    Distante, Roberta; Petrella, Ivan; Santoro, Emiliano

    2017-01-01

    The nexus between firm growth, size and age in U.S. manufacturing is examined through the lens of quantile regression models. This methodology allows us to overcome serious shortcomings entailed by linear regression models employed by much of the existing literature, unveiling a number of important...

  12. A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection.

    Science.gov (United States)

    Kwan, Johnny S H; Kung, Annie W C; Sham, Pak C

    2011-09-01

    Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias.

  13. A Monte Carlo simulation study comparing linear regression, beta regression, variable-dispersion beta regression and fractional logit regression at recovering average difference measures in a two sample design.

    Science.gov (United States)

    Meaney, Christopher; Moineddin, Rahim

    2014-01-24

    In biomedical research, response variables are often encountered which have bounded support on the open unit interval--(0,1). Traditionally, researchers have attempted to estimate covariate effects on these types of response data using linear regression. Alternative modelling strategies may include: beta regression, variable-dispersion beta regression, and fractional logit regression models. This study employs a Monte Carlo simulation design to compare the statistical properties of the linear regression model to that of the more novel beta regression, variable-dispersion beta regression, and fractional logit regression models. In the Monte Carlo experiment we assume a simple two sample design. We assume observations are realizations of independent draws from their respective probability models. The randomly simulated draws from the various probability models are chosen to emulate average proportion/percentage/rate differences of pre-specified magnitudes. Following simulation of the experimental data we estimate average proportion/percentage/rate differences. We compare the estimators in terms of bias, variance, type-1 error and power. Estimates of Monte Carlo error associated with these quantities are provided. If response data are beta distributed with constant dispersion parameters across the two samples, then all models are unbiased and have reasonable type-1 error rates and power profiles. If the response data in the two samples have different dispersion parameters, then the simple beta regression model is biased. When the sample size is small (N0 = N1 = 25) linear regression has superior type-1 error rates compared to the other models. Small sample type-1 error rates can be improved in beta regression models using bias correction/reduction methods. In the power experiments, variable-dispersion beta regression and fractional logit regression models have slightly elevated power compared to linear regression models. Similar results were observed if the

  14. No rationale for 1 variable per 10 events criterion for binary logistic regression analysis

    Directory of Open Access Journals (Sweden)

    Maarten van Smeden

    2016-11-01

    Full Text Available Abstract Background Ten events per variable (EPV is a widely advocated minimal criterion for sample size considerations in logistic regression analysis. Of three previous simulation studies that examined this minimal EPV criterion only one supports the use of a minimum of 10 EPV. In this paper, we examine the reasons for substantial differences between these extensive simulation studies. Methods The current study uses Monte Carlo simulations to evaluate small sample bias, coverage of confidence intervals and mean square error of logit coefficients. Logistic regression models fitted by maximum likelihood and a modified estimation procedure, known as Firth’s correction, are compared. Results The results show that besides EPV, the problems associated with low EPV depend on other factors such as the total sample size. It is also demonstrated that simulation results can be dominated by even a few simulated data sets for which the prediction of the outcome by the covariates is perfect (‘separation’. We reveal that different approaches for identifying and handling separation leads to substantially different simulation results. We further show that Firth’s correction can be used to improve the accuracy of regression coefficients and alleviate the problems associated with separation. Conclusions The current evidence supporting EPV rules for binary logistic regression is weak. Given our findings, there is an urgent need for new research to provide guidance for supporting sample size considerations for binary logistic regression analysis.

  15. Suppression Situations in Multiple Linear Regression

    Science.gov (United States)

    Shieh, Gwowen

    2006-01-01

    This article proposes alternative expressions for the two most prevailing definitions of suppression without resorting to the standardized regression modeling. The formulation provides a simple basis for the examination of their relationship. For the two-predictor regression, the author demonstrates that the previous results in the literature are…

  16. Association between large strongyle genera in larval cultures--using rare-event poisson regression.

    Science.gov (United States)

    Cao, X; Vidyashankar, A N; Nielsen, M K

    2013-09-01

    Decades of intensive anthelmintic treatment has caused equine large strongyles to become quite rare, while the cyathostomins have developed resistance to several drug classes. The larval culture has been associated with low to moderate negative predictive values for detecting Strongylus vulgaris infection. It is unknown whether detection of other large strongyle species can be statistically associated with presence of S. vulgaris. This remains a statistical challenge because of the rare occurrence of large strongyle species. This study used a modified Poisson regression to analyse a dataset for associations between S. vulgaris infection and simultaneous occurrence of Strongylus edentatus and Triodontophorus spp. In 663 horses on 42 Danish farms, the individual prevalences of S. vulgaris, S. edentatus and Triodontophorus spp. were 12%, 3% and 12%, respectively. Both S. edentatus and Triodontophorus spp. were significantly associated with S. vulgaris infection with relative risks above 1. Further, S. edentatus was associated with use of selective therapy on the farms, as well as negatively associated with anthelmintic treatment carried out within 6 months prior to the study. The findings illustrate that occurrence of S. vulgaris in larval cultures can be interpreted as indicative of other large strongyles being likely to be present.

  17. Canonical variate regression.

    Science.gov (United States)

    Luo, Chongliang; Liu, Jin; Dey, Dipak K; Chen, Kun

    2016-07-01

    In many fields, multi-view datasets, measuring multiple distinct but interrelated sets of characteristics on the same set of subjects, together with data on certain outcomes or phenotypes, are routinely collected. The objective in such a problem is often two-fold: both to explore the association structures of multiple sets of measurements and to develop a parsimonious model for predicting the future outcomes. We study a unified canonical variate regression framework to tackle the two problems simultaneously. The proposed criterion integrates multiple canonical correlation analysis with predictive modeling, balancing between the association strength of the canonical variates and their joint predictive power on the outcomes. Moreover, the proposed criterion seeks multiple sets of canonical variates simultaneously to enable the examination of their joint effects on the outcomes, and is able to handle multivariate and non-Gaussian outcomes. An efficient algorithm based on variable splitting and Lagrangian multipliers is proposed. Simulation studies show the superior performance of the proposed approach. We demonstrate the effectiveness of the proposed approach in an [Formula: see text] intercross mice study and an alcohol dependence study. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  18. A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection

    OpenAIRE

    Kwan, Johnny S. H.; Kung, Annie W. C.; Sham, Pak C.

    2011-01-01

    Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias. © The Author(s) 2011.

  19. A Dietary Pattern Derived by Reduced Rank Regression is Associated with Type 2 Diabetes in An Urban Ghanaian Population

    Directory of Open Access Journals (Sweden)

    Laura K. Frank

    2015-07-01

    Full Text Available Reduced rank regression (RRR is an innovative technique to establish dietary patterns related to biochemical risk factors for type 2 diabetes, but has not been applied in sub-Saharan Africa. In a hospital-based case-control study for type 2 diabetes in Kumasi (diabetes cases, 538; controls, 668 dietary intake was assessed by a specific food frequency questionnaire. After random split of our study population, we derived a dietary pattern in the training set using RRR with adiponectin, HDL-cholesterol and triglycerides as responses and 35 food items as predictors. This pattern score was applied to the validation set, and its association with type 2 diabetes was examined by logistic regression. The dietary pattern was characterized by a high consumption of plantain, cassava, and garden egg, and a low intake of rice, juice, vegetable oil, eggs, chocolate drink, sweets, and red meat; the score correlated positively with serum triglycerides and negatively with adiponectin. The multivariate-adjusted odds ratio of type 2 diabetes for the highest quintile compared to the lowest was 4.43 (95% confidence interval: 1.87–10.50, p for trend < 0.001. The identified dietary pattern increases the odds of type 2 diabetes in urban Ghanaians, which is mainly attributed to increased serum triglycerides.

  20. An Examination of the Association between Seeing Smoking in Films and Tobacco Use in Young Adults in the West of Scotland: Cross-Sectional Study

    Science.gov (United States)

    Hunt, Kate; Sweeting, Helen; Sargent, James; Lewars, Heather; Cin, Sonya Dal; Worth, Keilah

    2009-01-01

    The objective is to examine the association between the amount of smoking seen in films and current smoking in young adults living in the west of Scotland in the UK. Cross-sectional analyses (using multivariable logistic regression) of data collected at age 19 (2002-04) from a longitudinal cohort originally surveyed at age 11 (1994-95) were…

  1. Understanding logistic regression analysis.

    Science.gov (United States)

    Sperandei, Sandro

    2014-01-01

    Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using examples to make it as simple as possible. After definition of the technique, the basic interpretation of the results is highlighted and then some special issues are discussed.

  2. The digital divide: Examining socio-demographic factors associated with health literacy, access and use of internet to seek health information.

    Science.gov (United States)

    Estacio, Emee Vida; Whittle, Rebecca; Protheroe, Joanne

    2017-02-01

    This article aims to examine the socio-demographic characteristics associated with access and use of Internet for health-related purposes and its relationship with health literacy. Data were drawn from a health literacy survey ( N = 1046) and analysed using logistic regression. Results show a strong association between health literacy, internet access and use. Socio-demographic characteristics particularly age, education, income, perceived health and social isolation also predict internet access. Thus, in addition to widening access, the movement towards digitisation of health information and services should also consider digital skills development to enable people to utilise digital technology more effectively, especially among traditionally hard-to-reach communities.

  3. Association of footprint measurements with plantar kinetics: a linear regression model.

    Science.gov (United States)

    Fascione, Jeanna M; Crews, Ryan T; Wrobel, James S

    2014-03-01

    The use of foot measurements to classify morphology and interpret foot function remains one of the focal concepts of lower-extremity biomechanics. However, only 27% to 55% of midfoot variance in foot pressures has been determined in the most comprehensive models. We investigated whether dynamic walking footprint measurements are associated with inter-individual foot loading variability. Thirty individuals (15 men and 15 women; mean ± SD age, 27.17 ± 2.21 years) walked at a self-selected speed over an electronic pedography platform using the midgait technique. Kinetic variables (contact time, peak pressure, pressure-time integral, and force-time integral) were collected for six masked regions. Footprints were digitized for area and linear boundaries using digital photo planimetry software. Six footprint measurements were determined: contact area, footprint index, arch index, truncated arch index, Chippaux-Smirak index, and Staheli index. Linear regression analysis with a Bonferroni adjustment was performed to determine the association between the footprint measurements and each of the kinetic variables. The findings demonstrate that a relationship exists between increased midfoot contact and increased kinetic values in respective locations. Many of these variables produced large effect sizes while describing 38% to 71% of the common variance of select plantar kinetic variables in the medial midfoot region. In addition, larger footprints were associated with larger kinetic values at the medial heel region and both masked forefoot regions. Dynamic footprint measurements are associated with dynamic plantar loading kinetics, with emphasis on the midfoot region.

  4. Shigella mediated depletion of macrophages in a murine breast cancer model is associated with tumor regression.

    Directory of Open Access Journals (Sweden)

    Katharina Galmbacher

    Full Text Available A tumor promoting role of macrophages has been described for a transgenic murine breast cancer model. In this model tumor-associated macrophages (TAMs represent a major component of the leukocytic infiltrate and are associated with tumor progression. Shigella flexneri is a bacterial pathogen known to specificly induce apotosis in macrophages. To evaluate whether Shigella-induced removal of macrophages may be sufficient for achieving tumor regression we have developed an attenuated strain of S. flexneri (M90TDeltaaroA and infected tumor bearing mice. Two mouse models were employed, xenotransplantation of a murine breast cancer cell line and spontanous breast cancer development in MMTV-HER2 transgenic mice. Quantitative analysis of bacterial tumor targeting demonstrated that attenuated, invasive Shigella flexneri primarily infected TAMs after systemic administration. A single i.v. injection of invasive M90TDeltaaroA resulted in caspase-1 dependent apoptosis of TAMs followed by a 74% reduction in tumors of transgenic MMTV-HER-2 mice 7 days post infection. TAM depletion was sustained and associated with complete tumor regression.These data support TAMs as useful targets for antitumor therapy and highlight attenuated bacterial pathogens as potential tools.

  5. The MIDAS Touch: Mixed Data Sampling Regression Models

    OpenAIRE

    Ghysels, Eric; Santa-Clara, Pedro; Valkanov, Rossen

    2004-01-01

    We introduce Mixed Data Sampling (henceforth MIDAS) regression models. The regressions involve time series data sampled at different frequencies. Technically speaking MIDAS models specify conditional expectations as a distributed lag of regressors recorded at some higher sampling frequencies. We examine the asymptotic properties of MIDAS regression estimation and compare it with traditional distributed lag models. MIDAS regressions have wide applicability in macroeconomics and �nance.

  6. Forecasting with Dynamic Regression Models

    CERN Document Server

    Pankratz, Alan

    2012-01-01

    One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.

  7. Examining Predictive Validity of Oral Reading Fluency Slope in Upper Elementary Grades Using Quantile Regression.

    Science.gov (United States)

    Cho, Eunsoo; Capin, Philip; Roberts, Greg; Vaughn, Sharon

    2017-07-01

    Within multitiered instructional delivery models, progress monitoring is a key mechanism for determining whether a child demonstrates an adequate response to instruction. One measure commonly used to monitor the reading progress of students is oral reading fluency (ORF). This study examined the extent to which ORF slope predicts reading comprehension outcomes for fifth-grade struggling readers ( n = 102) participating in an intensive reading intervention. Quantile regression models showed that ORF slope significantly predicted performance on a sentence-level fluency and comprehension assessment, regardless of the students' reading skills, controlling for initial ORF performance. However, ORF slope was differentially predictive of a passage-level comprehension assessment based on students' reading skills when controlling for initial ORF status. Results showed that ORF explained unique variance for struggling readers whose posttest performance was at the upper quantiles at the end of the reading intervention, but slope was not a significant predictor of passage-level comprehension for students whose reading problems were the most difficult to remediate.

  8. Examination of Parameters Affecting the House Prices by Multiple Regression Analysis and its Contributions to Earthquake-Based Urban Transformation

    Science.gov (United States)

    Denli, H. H.; Durmus, B.

    2016-12-01

    The purpose of this study is to examine the factors which may affect the apartment prices with multiple linear regression analysis models and visualize the results by value maps. The study is focused on a county of Istanbul - Turkey. Totally 390 apartments around the county Umraniye are evaluated due to their physical and locational conditions. The identification of factors affecting the price of apartments in the county with a population of approximately 600k is expected to provide a significant contribution to the apartment market.Physical factors are selected as the age, number of rooms, size, floor numbers of the building and the floor that the apartment is positioned in. Positional factors are selected as the distances to the nearest hospital, school, park and police station. Totally ten physical and locational parameters are examined by regression analysis.After the regression analysis has been performed, value maps are composed from the parameters age, price and price per square meters. The most significant of the composed maps is the price per square meters map. Results show that the location of the apartment has the most influence to the square meter price information of the apartment. A different practice is developed from the composed maps by searching the ability of using price per square meters map in urban transformation practices. By marking the buildings older than 15 years in the price per square meters map, a different and new interpretation has been made to determine the buildings, to which should be given priority during an urban transformation in the county.This county is very close to the North Anatolian Fault zone and is under the threat of earthquakes. By marking the apartments older than 15 years on the price per square meters map, both older and expensive square meters apartments list can be gathered. By the help of this list, the priority could be given to the selected higher valued old apartments to support the economy of the country

  9. The Association between Food Insecurity and Obesity in Children-The National Health and Nutrition Examination Survey.

    Science.gov (United States)

    Kaur, Jasbir; Lamb, Molly M; Ogden, Cynthia L

    2015-05-01

    Food insecurity can put children at greater risk of obesity because of altered food choices and nonuniform consumption patterns. We examined the association between obesity and both child-level food insecurity and personal food insecurity in US children. Data from 9,701 participants in the National Health and Nutrition Examination Survey, 2001-2010, aged 2 to 11 years were analyzed. Child-level food insecurity was assessed with the US Department of Agriculture's Food Security Survey Module based on eight child-specific questions. Personal food insecurity was assessed with five additional questions. Obesity was defined, using physical measurements, as body mass index (calculated as kg/m²) greater than or equal to the age- and sex-specific 95th percentile of the Centers for Disease Control and Prevention growth charts. Logistic regressions adjusted for sex, race/ethnic group, poverty level, and survey year were conducted to describe associations between obesity and food insecurity. Obesity was significantly associated with personal food insecurity for children aged 6 to 11 years (odds ratio=1.81; 95% CI 1.33 to 2.48), but not in children aged 2 to 5 years (odds ratio=0.88; 95% CI 0.51 to 1.51). Child-level food insecurity was not associated with obesity among 2- to 5-year-olds or 6- to 11-year-olds. Personal food insecurity is associated with an increased risk of obesity only in children aged 6 to 11 years. Personal food-insecurity measures may give different results than aggregate food-insecurity measures in children. Published by Elsevier Inc.

  10. Celiac Disease Associated with a Benign Granulomatous Mass Demonstrating Self-Regression after Initiation of a Gluten-Free Diet.

    Science.gov (United States)

    Tiwari, Abhinav; Sharma, Himani; Qamar, Khola; Khan, Zubair; Darr, Umar; Renno, Anas; Nawras, Ali

    2017-01-01

    Celiac disease is a chronic immune-mediated enteropathy in which dietary gluten induces an inflammatory reaction predominantly in the duodenum. Celiac disease is known to be associated with benign small bowel thickening and reactive lymphadenopathy that often regresses after the institution of a gluten-free diet. A 66-year-old male patient with celiac disease presented with abdominal pain and diarrheal illness. Computerized tomography of the abdomen revealed a duodenal mass. Endoscopic ultrasound-guided fine needle aspiration of the mass revealed bizarre stromal cells which represent a nonspecific tissue reaction to inflammation. This inflammatory mass regressed after the institution of a gluten-free diet. This case report describes a unique presentation of celiac disease in the form of a granulomatous self-regressing mass. Also, this is the first reported case of bizarre stromal cells found in association with celiac disease. In addition to lymphoma and small bowel adenocarcinoma, celiac disease can present with a benign inflammatory mass, which should be serially monitored for resolution with a gluten-free diet.

  11. Celiac Disease Associated with a Benign Granulomatous Mass Demonstrating Self-Regression after Initiation of a Gluten-Free Diet

    Directory of Open Access Journals (Sweden)

    Abhinav Tiwari

    2017-08-01

    Full Text Available Celiac disease is a chronic immune-mediated enteropathy in which dietary gluten induces an inflammatory reaction predominantly in the duodenum. Celiac disease is known to be associated with benign small bowel thickening and reactive lymphadenopathy that often regresses after the institution of a gluten-free diet. A 66-year-old male patient with celiac disease presented with abdominal pain and diarrheal illness. Computerized tomography of the abdomen revealed a duodenal mass. Endoscopic ultrasound-guided fine needle aspiration of the mass revealed bizarre stromal cells which represent a nonspecific tissue reaction to inflammation. This inflammatory mass regressed after the institution of a gluten-free diet. This case report describes a unique presentation of celiac disease in the form of a granulomatous self-regressing mass. Also, this is the first reported case of bizarre stromal cells found in association with celiac disease. In addition to lymphoma and small bowel adenocarcinoma, celiac disease can present with a benign inflammatory mass, which should be serially monitored for resolution with a gluten-free diet.

  12. Is past life regression therapy ethical?

    Science.gov (United States)

    Andrade, Gabriel

    2017-01-01

    Past life regression therapy is used by some physicians in cases with some mental diseases. Anxiety disorders, mood disorders, and gender dysphoria have all been treated using life regression therapy by some doctors on the assumption that they reflect problems in past lives. Although it is not supported by psychiatric associations, few medical associations have actually condemned it as unethical. In this article, I argue that past life regression therapy is unethical for two basic reasons. First, it is not evidence-based. Past life regression is based on the reincarnation hypothesis, but this hypothesis is not supported by evidence, and in fact, it faces some insurmountable conceptual problems. If patients are not fully informed about these problems, they cannot provide an informed consent, and hence, the principle of autonomy is violated. Second, past life regression therapy has the great risk of implanting false memories in patients, and thus, causing significant harm. This is a violation of the principle of non-malfeasance, which is surely the most important principle in medical ethics.

  13. The Spatial Association Between Federally Qualified Health Centers and County-Level Reported Sexually Transmitted Infections: A Spatial Regression Approach.

    Science.gov (United States)

    Owusu-Edusei, Kwame; Gift, Thomas L; Leichliter, Jami S; Romaguera, Raul A

    2018-02-01

    The number of categorical sexually transmitted disease (STD) clinics is declining in the United States. Federally qualified health centers (FQHCs) have the potential to supplement the needed sexually transmitted infection (STI) services. In this study, we describe the spatial distribution of FQHC sites and determine if reported county-level nonviral STI morbidity were associated with having FQHC(s) using spatial regression techniques. We extracted map data from the Health Resources and Services Administration data warehouse on FQHCs (ie, geocoded health care service delivery [HCSD] sites) and extracted county-level data on the reported rates of chlamydia, gonorrhea and, primary and secondary (P&S) syphilis (2008-2012) from surveillance data. A 3-equation seemingly unrelated regression estimation procedure (with a spatial regression specification that controlled for county-level multiyear (2008-2012) demographic and socioeconomic factors) was used to determine the association between reported county-level STI morbidity and HCSD sites. Counties with HCSD sites had higher STI, poverty, unemployment, and violent crime rates than counties with no HCSD sites (P < 0.05). The number of HCSD sites was associated (P < 0.01) with increases in the temporally smoothed rates of chlamydia, gonorrhea, and P&S syphilis, but there was no significant association between the number of HCSD per 100,000 population and reported STI rates. There is a positive association between STI morbidity and the number of HCSD sites; however, this association does not exist when adjusting by population size. Further work may determine the extent to which HCSD sites can meet unmet needs for safety net STI services.

  14. Examining the association between livestock ownership typologies and child nutrition in the Luangwa Valley, Zambia.

    Science.gov (United States)

    Dumas, Sarah E; Kassa, Lea; Young, Sera L; Travis, Alexander J

    2018-01-01

    To investigate the association between livestock ownership and dietary diversity, animal-source food consumption, height-for-age z-score, and stunting among children living in wildlife "buffer zones" of Zambia's Luangwa Valley using a novel livestock typology approach. We conducted a cross-sectional study of 838 children aged 6-36 months. Households were categorized into typologies based on the types and numbers of animals owned, ranging from no livestock to large numbers of mixed livestock. We used multilevel mixed-effects linear and logistic regression to examine the association between livestock typologies and four nutrition-related outcomes of interest. Results were compared with analyses using more common binary and count measures of livestock ownership. No measure of livestock ownership was significantly associated with children's odds of animal-source food consumption, child height-for-age z-score, or stunting odds. Livestock ownership Type 2 (having a small number of poultry) was surprisingly associated with decreased child dietary diversity (β = -0.477; p<0.01) relative to owning no livestock. Similarly, in comparison models, chicken ownership was negatively associated with dietary diversity (β = -0.320; p<0.01), but increasing numbers of chickens were positively associated with dietary diversity (β = 0.022; p<0.01). Notably, neither child dietary diversity nor animal-source food consumption was significantly associated with height, perhaps due to unusually high prevalences of morbidities. Our novel typologies methodology allowed for an efficient and a more in-depth examination of the differential impact of livestock ownership patterns compared to typical binary or count measures of livestock ownership. We found that these patterns were not positively associated with child nutrition outcomes in this context. Development and conservation programs focusing on livestock must carefully consider the complex, context-specific relationship between livestock

  15. Examining the association between livestock ownership typologies and child nutrition in the Luangwa Valley, Zambia.

    Directory of Open Access Journals (Sweden)

    Sarah E Dumas

    Full Text Available To investigate the association between livestock ownership and dietary diversity, animal-source food consumption, height-for-age z-score, and stunting among children living in wildlife "buffer zones" of Zambia's Luangwa Valley using a novel livestock typology approach.We conducted a cross-sectional study of 838 children aged 6-36 months. Households were categorized into typologies based on the types and numbers of animals owned, ranging from no livestock to large numbers of mixed livestock. We used multilevel mixed-effects linear and logistic regression to examine the association between livestock typologies and four nutrition-related outcomes of interest. Results were compared with analyses using more common binary and count measures of livestock ownership.No measure of livestock ownership was significantly associated with children's odds of animal-source food consumption, child height-for-age z-score, or stunting odds. Livestock ownership Type 2 (having a small number of poultry was surprisingly associated with decreased child dietary diversity (β = -0.477; p<0.01 relative to owning no livestock. Similarly, in comparison models, chicken ownership was negatively associated with dietary diversity (β = -0.320; p<0.01, but increasing numbers of chickens were positively associated with dietary diversity (β = 0.022; p<0.01. Notably, neither child dietary diversity nor animal-source food consumption was significantly associated with height, perhaps due to unusually high prevalences of morbidities.Our novel typologies methodology allowed for an efficient and a more in-depth examination of the differential impact of livestock ownership patterns compared to typical binary or count measures of livestock ownership. We found that these patterns were not positively associated with child nutrition outcomes in this context. Development and conservation programs focusing on livestock must carefully consider the complex, context-specific relationship between

  16. Tumor regression patterns in retinoblastoma

    International Nuclear Information System (INIS)

    Zafar, S.N.; Siddique, S.N.; Zaheer, N.

    2016-01-01

    To observe the types of tumor regression after treatment, and identify the common pattern of regression in our patients. Study Design: Descriptive study. Place and Duration of Study: Department of Pediatric Ophthalmology and Strabismus, Al-Shifa Trust Eye Hospital, Rawalpindi, Pakistan, from October 2011 to October 2014. Methodology: Children with unilateral and bilateral retinoblastoma were included in the study. Patients were referred to Pakistan Institute of Medical Sciences, Islamabad, for chemotherapy. After every cycle of chemotherapy, dilated funds examination under anesthesia was performed to record response of the treatment. Regression patterns were recorded on RetCam II. Results: Seventy-four tumors were included in the study. Out of 74 tumors, 3 were ICRB group A tumors, 43 were ICRB group B tumors, 14 tumors belonged to ICRB group C, and remaining 14 were ICRB group D tumors. Type IV regression was seen in 39.1% (n=29) tumors, type II in 29.7% (n=22), type III in 25.6% (n=19), and type I in 5.4% (n=4). All group A tumors (100%) showed type IV regression. Seventeen (39.5%) group B tumors showed type IV regression. In group C, 5 tumors (35.7%) showed type II regression and 5 tumors (35.7%) showed type IV regression. In group D, 6 tumors (42.9%) regressed to type II non-calcified remnants. Conclusion: The response and success of the focal and systemic treatment, as judged by the appearance of different patterns of tumor regression, varies with the ICRB grouping of the tumor. (author)

  17. Examining the association between male circumcision and sexual function: evidence from a British probability survey.

    Science.gov (United States)

    Homfray, Virginia; Tanton, Clare; Mitchell, Kirstin R; Miller, Robert F; Field, Nigel; Macdowall, Wendy; Wellings, Kaye; Sonnenberg, Pam; Johnson, Anne M; Mercer, Catherine H

    2015-07-17

    Despite biological advantages of male circumcision in reducing HIV/sexually transmitted infection acquisition, concern is often expressed that it may reduce sexual enjoyment and function. We examine the association between circumcision and sexual function among sexually active men in Britain using data from Britain's third National Survey of Sexual Attitudes and Lifestyles (Natsal-3). Natsal-3 asked about circumcision and included a validated measure of sexual function, the Natsal-SF, which takes into account not only sexual difficulties but also the relationship context and overall level of satisfaction. A stratified probability survey of 6293 men and 8869 women aged 16-74 years, resident in Britain, undertaken 2010-2012, using computer-assisted face-to-face interviewing with computer-assisted self-interview for the more sensitive questions. Logistic regression was used to calculate odds ratios (ORs) to examine the association between reporting male circumcision and aspects of sexual function among sexually active men (n = 4816). The prevalence of male circumcision in Britain was 20.7% [95% confidence interval (CI): 19.3-21.8]. There was no association between male circumcision and, being in the lowest quintile of scores for the Natsal-SF, an indicator of poorer sexual function (adjusted OR: 0.95, 95% CI: 0.76-1.18). Circumcised men were as likely as uncircumcised men to report the specific sexual difficulties asked about in Natsal-3, except that a larger proportion of circumcised men reported erectile difficulties. This association was of borderline statistical significance after adjusting for age and relationship status (adjusted OR: 1.27, 95% CI: 0.99-1.63). Data from a large, nationally representative British survey suggest that circumcision is not associated with men's overall sexual function at a population level.

  18. Complete regression of myocardial involvement associated with lymphoma following chemotherapy.

    Science.gov (United States)

    Vinicki, Juan Pablo; Cianciulli, Tomás F; Farace, Gustavo A; Saccheri, María C; Lax, Jorge A; Kazelian, Lucía R; Wachs, Adolfo

    2013-09-26

    Cardiac involvement as an initial presentation of malignant lymphoma is a rare occurrence. We describe the case of a 26 year old man who had initially been diagnosed with myocardial infiltration on an echocardiogram, presenting with a testicular mass and unilateral peripheral facial paralysis. On admission, electrocardiograms (ECG) revealed negative T-waves in all leads and ST-segment elevation in the inferior leads. On two-dimensional echocardiography, there was infiltration of the pericardium with mild effusion, infiltrative thickening of the aortic walls, both atria and the interatrial septum and a mildly depressed systolic function of both ventricles. An axillary biopsy was performed and reported as a T-cell lymphoblastic lymphoma (T-LBL). Following the diagnosis and staging, chemotherapy was started. Twenty-two days after finishing the first cycle of chemotherapy, the ECG showed regression of T-wave changes in all leads and normalization of the ST-segment elevation in the inferior leads. A follow-up Two-dimensional echocardiography confirmed regression of the myocardial infiltration. This case report illustrates a lymphoma presenting with testicular mass, unilateral peripheral facial paralysis and myocardial involvement, and demonstrates that regression of infiltration can be achieved by intensive chemotherapy treatment. To our knowledge, there are no reported cases of T-LBL presenting as a testicular mass and unilateral peripheral facial paralysis, with complete regression of myocardial involvement.

  19. Factors associated with child sexual abuse confirmation at forensic examinations

    Directory of Open Access Journals (Sweden)

    Welington dos Santos Silva

    Full Text Available Abstract The aim of this study is identify potential factors associated with child sexual abuse confirmation at forensic examinations. The forensic files of children under 12 years of age reporting sexual abuse at the Nina Rodrigues Institute of Forensic Medicine in Salvador, Bahia, Brazil between January 2008 and December 2009 were reviewed. A multivariate analysis was conducted to identify factors associated with finding evidence of sexual abuse in forensic examinations. The proportion of cases confirmed by the forensic physician based on material evidence was 10.4%. Adjusted analysis showed that the variables place of birth, type of abuse reported, family relationship between the child and the perpetrator, and the interval between the reported abuse and the forensic examination were not independently associated with finding forensic evidence of sexual abuse. A report of penetration was associated with a five-fold greater likelihood of confirmation, while the victim being 10-11 years of age was associated with a two-fold of abuse confirmation than younger children. These findings should be taken into consideration when drawing up guidelines for the multidisciplinary evaluation of children suspected of being victims of sexual abuse and in deciding whether to refer the child for forensic examination.

  20. Abstract Expression Grammar Symbolic Regression

    Science.gov (United States)

    Korns, Michael F.

    This chapter examines the use of Abstract Expression Grammars to perform the entire Symbolic Regression process without the use of Genetic Programming per se. The techniques explored produce a symbolic regression engine which has absolutely no bloat, which allows total user control of the search space and output formulas, which is faster, and more accurate than the engines produced in our previous papers using Genetic Programming. The genome is an all vector structure with four chromosomes plus additional epigenetic and constraint vectors, allowing total user control of the search space and the final output formulas. A combination of specialized compiler techniques, genetic algorithms, particle swarm, aged layered populations, plus discrete and continuous differential evolution are used to produce an improved symbolic regression sytem. Nine base test cases, from the literature, are used to test the improvement in speed and accuracy. The improved results indicate that these techniques move us a big step closer toward future industrial strength symbolic regression systems.

  1. Molecular Genetic Changes Associated With Colorectal Carcinogenesis Are Not Prognostic for Tumor Regression Following Preoperative Chemoradiation of Rectal Carcinoma

    International Nuclear Information System (INIS)

    Zauber, N. Peter; Marotta, Steven P.; Berman, Errol; Grann, Alison; Rao, Maithili; Komati, Naga; Ribiero, Kezia; Bishop, D. Timothy

    2009-01-01

    Purpose: Preoperative chemotherapy and radiation has become the standard of care for many patients with rectal cancer. The therapy may have toxicity and delays definitive surgery. It would therefore be desirable to identify those cancers that will not regress with preoperative therapy. We assessed a series of rectal cancers for the molecular changes of loss of heterozygosity of the APC and DCC genes, K-ras mutations, and microsatellite instability, changes that have clearly been associated with rectal carcinogenesis. Methods and Materials: Diagnostic colonoscopic biopsies from 53 patients who received preoperative chemotherapy and radiation were assayed using polymerase chain reaction techniques followed by single-stranded conformation polymorphism and DNA sequencing. Regression of the primary tumor was evaluated using the surgically removed specimen. Results: Twenty-three lesions (45%) were found to have a high degree of regression. None of the molecular changes were useful as indicators of regression. Conclusions: Recognized molecular changes critical for rectal carcinogenesis including APC and DCC loss of heterozygosity, K-ras mutations, and microsatellite instability are not useful as indicators of tumor regression following chemoradiation for rectal carcinoma.

  2. Esophageal Stenosis Associated With Tumor Regression in Radiotherapy for Esophageal Cancer: Frequency and Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Atsumi, Kazushige [Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka (Japan); Shioyama, Yoshiyuki, E-mail: shioyama@radiol.med.kyushu-u.ac.jp [Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka (Japan); Arimura, Hidetaka [Department of Health Sciences, Kyushu University, Fukuoka (Japan); Terashima, Kotaro [Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka (Japan); Matsuki, Takaomi [Department of Health Sciences, Kyushu University, Fukuoka (Japan); Ohga, Saiji; Yoshitake, Tadamasa; Nonoshita, Takeshi; Tsurumaru, Daisuke; Ohnishi, Kayoko; Asai, Kaori; Matsumoto, Keiji [Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka (Japan); Nakamura, Katsumasa [Department of Radiology, Kyushu University Hospital at Beppu, Oita (Japan); Honda, Hiroshi [Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka (Japan)

    2012-04-01

    Purpose: To determine clinical factors for predicting the frequency and severity of esophageal stenosis associated with tumor regression in radiotherapy for esophageal cancer. Methods and Materials: The study group consisted of 109 patients with esophageal cancer of T1-4 and Stage I-III who were treated with definitive radiotherapy and achieved a complete response of their primary lesion at Kyushu University Hospital between January 1998 and December 2007. Esophageal stenosis was evaluated using esophagographic images within 3 months after completion of radiotherapy. We investigated the correlation between esophageal stenosis after radiotherapy and each of the clinical factors with regard to tumors and therapy. For validation of the correlative factors for esophageal stenosis, an artificial neural network was used to predict the esophageal stenotic ratio. Results: Esophageal stenosis tended to be more severe and more frequent in T3-4 cases than in T1-2 cases. Esophageal stenosis in cases with full circumference involvement tended to be more severe and more frequent than that in cases without full circumference involvement. Increases in wall thickness tended to be associated with increases in esophageal stenosis severity and frequency. In the multivariate analysis, T stage, extent of involved circumference, and wall thickness of the tumor region were significantly correlated to esophageal stenosis (p = 0.031, p < 0.0001, and p = 0.0011, respectively). The esophageal stenotic ratio predicted by the artificial neural network, which learned these three factors, was significantly correlated to the actual observed stenotic ratio, with a correlation coefficient of 0.864 (p < 0.001). Conclusion: Our study suggested that T stage, extent of involved circumference, and esophageal wall thickness of the tumor region were useful to predict the frequency and severity of esophageal stenosis associated with tumor regression in radiotherapy for esophageal cancer.

  3. Dietary patterns by reduced rank regression are associated with obesity and hypertension in Australian adults.

    Science.gov (United States)

    Livingstone, Katherine M; McNaughton, Sarah A

    2017-01-01

    Evidence linking dietary patterns (DP) and obesity and hypertension prevalence is inconsistent. We aimed to identify DP derived from energy density, fibre and sugar intakes, as well as Na, K, fibre, SFA and PUFA, and investigate associations with obesity and hypertension. Adults (n 4908) were included from the cross-sectional Australian Health Survey 2011-2013. Two 24-h dietary recalls estimated food and nutrient intakes. Reduced rank regression derived DP with dietary energy density (DED), fibre density and total sugar intake as response variables for obesity and Na:K, SFA:PUFA and fibre density as variables for hypertension. Poisson regression investigated relationships between DP and prevalence ratios (PR) of overweight/obesity (BMI≥25 kg/m2) and hypertension (blood pressure≥140/90 mmHg). Obesity-DP1 was positively correlated with fibre density and sugars and inversely with DED. Obesity-DP2 was positively correlated with sugars and inversely with fibre density. Individuals in the highest tertile of Obesity-DP1 and Obesity-DP2, compared with the lowest, had lower (PR 0·88; 95 % CI 0·81, 0·95) and higher (PR 1·09; 95 % CI 1·01, 1·18) prevalence of obesity, respectively. Na:K and SFA:PUFA were positively correlated with Hypertension-DP1 and inversely correlated with Hypertension-DP2, respectively. There was a trend towards higher hypertension prevalence in the highest tertile of Hypertension-DP1 compared with the lowest (PR 1·18; 95 % CI 0·99, 1·41). Hypertension-DP2 was not associated with hypertension. Obesity prevalence was inversely associated with low-DED, high-fibre and high-sugar (natural sugars) diets and positively associated with low-fibre and high-sugar (added sugars) diets. Hypertension prevalence was higher on low-fibre and high-Na and SFA diets.

  4. Methods for identifying SNP interactions: a review on variations of Logic Regression, Random Forest and Bayesian logistic regression.

    Science.gov (United States)

    Chen, Carla Chia-Ming; Schwender, Holger; Keith, Jonathan; Nunkesser, Robin; Mengersen, Kerrie; Macrossan, Paula

    2011-01-01

    Due to advancements in computational ability, enhanced technology and a reduction in the price of genotyping, more data are being generated for understanding genetic associations with diseases and disorders. However, with the availability of large data sets comes the inherent challenges of new methods of statistical analysis and modeling. Considering a complex phenotype may be the effect of a combination of multiple loci, various statistical methods have been developed for identifying genetic epistasis effects. Among these methods, logic regression (LR) is an intriguing approach incorporating tree-like structures. Various methods have built on the original LR to improve different aspects of the model. In this study, we review four variations of LR, namely Logic Feature Selection, Monte Carlo Logic Regression, Genetic Programming for Association Studies, and Modified Logic Regression-Gene Expression Programming, and investigate the performance of each method using simulated and real genotype data. We contrast these with another tree-like approach, namely Random Forests, and a Bayesian logistic regression with stochastic search variable selection.

  5. Multiple Linear Regression Analysis Indicates Association of P-Glycoprotein Substrate or Inhibitor Character with Bitterness Intensity, Measured with a Sensor.

    Science.gov (United States)

    Yano, Kentaro; Mita, Suzune; Morimoto, Kaori; Haraguchi, Tamami; Arakawa, Hiroshi; Yoshida, Miyako; Yamashita, Fumiyoshi; Uchida, Takahiro; Ogihara, Takuo

    2015-09-01

    P-glycoprotein (P-gp) regulates absorption of many drugs in the gastrointestinal tract and their accumulation in tumor tissues, but the basis of substrate recognition by P-gp remains unclear. Bitter-tasting phenylthiocarbamide, which stimulates taste receptor 2 member 38 (T2R38), increases P-gp activity and is a substrate of P-gp. This led us to hypothesize that bitterness intensity might be a predictor of P-gp-inhibitor/substrate status. Here, we measured the bitterness intensity of a panel of P-gp substrates and nonsubstrates with various taste sensors, and used multiple linear regression analysis to examine the relationship between P-gp-inhibitor/substrate status and various physical properties, including intensity of bitter taste measured with the taste sensor. We calculated the first principal component analysis score (PC1) as the representative value of bitterness, as all taste sensor's outputs shared significant correlation. The P-gp substrates showed remarkably greater mean bitterness intensity than non-P-gp substrates. We found that Km value of P-gp substrates were correlated with molecular weight, log P, and PC1 value, and the coefficient of determination (R(2) ) of the linear regression equation was 0.63. This relationship might be useful as an aid to predict P-gp substrate status at an early stage of drug discovery. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

  6. [Milk yield and environmental factors: Multiple regression analysis of the association between milk yield and udder health, fertility data and replacement rate].

    Science.gov (United States)

    Fölsche, C; Staufenbiel, R

    2014-01-01

    The relationship between milk yield and both fertility and general animal health in dairy herds is discussed from opposing viewpoints. The hypothesis (1) that raising the herd milk yield would decrease fertility results, the number of milk cells as an indicator for udder health and the replacement rate as a global indicator for animal health as well as increasing the occurrence of specific diseases as a herd problem was compared to the opposing hypotheses that there is no relationship (2) or that there is a differentiated and changing relationship (3). A total of 743 herd examinations, considered independent, were performed in 489 herds between 1995 and 2010. The milk yield, fertility rate, milk cell count, replacement rate, categorized herd problems and management information were recorded. The relationship between the milk yield and both the fertility data and animal health was evaluated using simple and multiple regression analyses. The period between calving and the first service displayed no significant relationship to the herd milk yield. Simple regression analysis showed that the period between calving and gestation, the calving interval and the insemination number were significantly positively associated with the herd milk yield. This positive correlation was lost in multiple regression analysis. The milk cell count and replacement rate using both the simple and multiple regression analyses displayed a significant negative relationship to the milk yield. The alternative hypothesis (3) was confirmed. A higher milk yield has no negative influence on the milk cell count and the replacement rate in terms of the udder and general health. When parameterizing the fertility, the herd milk yield should be considered. Extending the resting time may increase the milk yield while preventing a decline in the insemination index.

  7. Evaluating penalized logistic regression models to predict Heat-Related Electric grid stress days

    Energy Technology Data Exchange (ETDEWEB)

    Bramer, L. M.; Rounds, J.; Burleyson, C. D.; Fortin, D.; Hathaway, J.; Rice, J.; Kraucunas, I.

    2017-11-01

    Understanding the conditions associated with stress on the electricity grid is important in the development of contingency plans for maintaining reliability during periods when the grid is stressed. In this paper, heat-related grid stress and the relationship with weather conditions is examined using data from the eastern United States. Penalized logistic regression models were developed and applied to predict stress on the electric grid using weather data. The inclusion of other weather variables, such as precipitation, in addition to temperature improved model performance. Several candidate models and datasets were examined. A penalized logistic regression model fit at the operation-zone level was found to provide predictive value and interpretability. Additionally, the importance of different weather variables observed at different time scales were examined. Maximum temperature and precipitation were identified as important across all zones while the importance of other weather variables was zone specific. The methods presented in this work are extensible to other regions and can be used to aid in planning and development of the electrical grid.

  8. Modified Regression Correlation Coefficient for Poisson Regression Model

    Science.gov (United States)

    Kaengthong, Nattacha; Domthong, Uthumporn

    2017-09-01

    This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

  9. Fasting Glucose and the Risk of Depressive Symptoms: Instrumental-Variable Regression in the Cardiovascular Risk in Young Finns Study.

    Science.gov (United States)

    Wesołowska, Karolina; Elovainio, Marko; Hintsa, Taina; Jokela, Markus; Pulkki-Råback, Laura; Pitkänen, Niina; Lipsanen, Jari; Tukiainen, Janne; Lyytikäinen, Leo-Pekka; Lehtimäki, Terho; Juonala, Markus; Raitakari, Olli; Keltikangas-Järvinen, Liisa

    2017-12-01

    Type 2 diabetes (T2D) has been associated with depressive symptoms, but the causal direction of this association and the underlying mechanisms, such as increased glucose levels, remain unclear. We used instrumental-variable regression with a genetic instrument (Mendelian randomization) to examine a causal role of increased glucose concentrations in the development of depressive symptoms. Data were from the population-based Cardiovascular Risk in Young Finns Study (n = 1217). Depressive symptoms were assessed in 2012 using a modified Beck Depression Inventory (BDI-I). Fasting glucose was measured concurrently with depressive symptoms. A genetic risk score for fasting glucose (with 35 single nucleotide polymorphisms) was used as an instrumental variable for glucose. Glucose was not associated with depressive symptoms in the standard linear regression (B = -0.04, 95% CI [-0.12, 0.04], p = .34), but the instrumental-variable regression showed an inverse association between glucose and depressive symptoms (B = -0.43, 95% CI [-0.79, -0.07], p = .020). The difference between the estimates of standard linear regression and instrumental-variable regression was significant (p = .026) CONCLUSION: Our results suggest that the association between T2D and depressive symptoms is unlikely to be caused by increased glucose concentrations. It seems possible that T2D might be linked to depressive symptoms due to low glucose levels.

  10. A Simulation Investigation of Principal Component Regression.

    Science.gov (United States)

    Allen, David E.

    Regression analysis is one of the more common analytic tools used by researchers. However, multicollinearity between the predictor variables can cause problems in using the results of regression analyses. Problems associated with multicollinearity include entanglement of relative influences of variables due to reduced precision of estimation,…

  11. Enhanced left ventricular mass regression after aortic valve replacement in patients with aortic stenosis is associated with improved long-term survival.

    Science.gov (United States)

    Ali, Ayyaz; Patel, Amit; Ali, Ziad; Abu-Omar, Yasir; Saeed, Amber; Athanasiou, Thanos; Pepper, John

    2011-08-01

    Aortic valve replacement in patients with aortic stenosis is usually followed by regression of left ventricular hypertrophy. More complete resolution of left ventricular hypertrophy is suggested to be associated with superior clinical outcomes; however, its translational impact on long-term survival after aortic valve replacement has not been investigated. Demographic, operative, and clinical data were obtained retrospectively through case note review. Transthoracic echocardiography was used to measure left ventricular mass preoperatively and at annual follow-up visits. Patients were classified according to their reduction in left ventricular mass at 1 year after the operation: group 1, less than 25 g; group 2, 25 to 150 g; and group 3, more than 150 g. Kaplan-Meier and multivariable Cox regression were used. A total of 147 patients were discharged from the hospital after aortic valve replacement for aortic stenosis between 1991 and 2001. Preoperative left ventricular mass was 279 ± 98 g in group 1 (n = 47), 347 ± 104 g in group 2 (n = 62), and 491 ± 183 g in group 3 (n = 38) (P regression such as ischemic heart disease or hypertension, valve type, or valve size used. Ten-year actuarial survival was not statistically different in patients with enhanced left ventricular mass regression when compared with the log-rank test (group 1, 51% ± 9%; group 2, 54% ± 8%; and group 3, 72% ± 10%) (P = .26). After adjustment, left ventricular mass reduction of more than 150 g was demonstrated as an independent predictor of improved long-term survival on multivariate analysis (P = .02). Our study is the first to suggest that enhanced postoperative left ventricular mass regression, specifically in patients undergoing aortic valve replacement for aortic stenosis, may be associated with improved long-term survival. In view of these findings, strategies purported to be associated with superior left ventricular mass regression should be considered when undertaking

  12. Quasi-experimental evidence on tobacco tax regressivity.

    Science.gov (United States)

    Koch, Steven F

    2018-01-01

    Tobacco taxes are known to reduce tobacco consumption and to be regressive, such that tobacco control policy may have the perverse effect of further harming the poor. However, if tobacco consumption falls faster amongst the poor than the rich, tobacco control policy can actually be progressive. We take advantage of persistent and committed tobacco control activities in South Africa to examine the household tobacco expenditure burden. For the analysis, we make use of two South African Income and Expenditure Surveys (2005/06 and 2010/11) that span a series of such tax increases and have been matched across the years, yielding 7806 matched pairs of tobacco consuming households and 4909 matched pairs of cigarette consuming households. By matching households across the surveys, we are able to examine both the regressivity of the household tobacco burden, and any change in that regressivity, and since tobacco taxes have been a consistent component of tobacco prices, our results also relate to the regressivity of tobacco taxes. Like previous research into cigarette and tobacco expenditures, we find that the tobacco burden is regressive; thus, so are tobacco taxes. However, we find that over the five-year period considered, the tobacco burden has decreased, and, most importantly, falls less heavily on the poor. Thus, the tobacco burden and the tobacco tax is less regressive in 2010/11 than in 2005/06. Thus, increased tobacco taxes can, in at least some circumstances, reduce the financial burden that tobacco places on households. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. The Association Between Barium Examination and Subsequent Appendicitis: A Nationwide Population-Based Study.

    Science.gov (United States)

    Li, Hao-Ming; Yeh, Lee-Ren; Huang, Ying-Kai; Lin, Cheng-Li; Kao, Chia-Hung

    2017-01-01

    The incidence and association between appendicitis and barium examination (BE) remain unclear. Such potential risk may be omitted. We conducted a longitudinal, nationwide, population-based cohort study to investigate the association between BE and appendicitis risk. From the Taiwan National Health Insurance Research Database, a total of 24,885 patients who underwent BE between January 1, 2000 and December 31, 2010 were enrolled in a BE cohort; an additional 98,384 subjects without BE exposure were selected as a non-BE cohort, matched by age, sex, and index date. The cumulative incidences of subsequent appendicitis in the BE and non-BE cohorts were assessed using the Kaplan-Meier curves and log-rank test. Cox proportional hazards regression analyses were employed to calculate the appendicitis risk between the groups. The cumulative incidence of appendicitis was higher in the BE cohort than in the non-BE cohort (P = .001). The overall incidence rates of appendicitis for the BE and non-BE cohorts were 1.19 and 0.80 per 1000 person-years, respectively. After adjustment for sex, age, and comorbidities, the risk of appendicitis was higher in the BE cohort (adjusted hazard ratio = 1.46, 95% confidence interval = 1.23-1.73) compared with the non-BE cohort, especially in the first 2 months (adjusted hazard ratio = 9.72, 95% confidence interval = 4.65-20.3). BE was associated with an increased, time-dependent appendicitis risk. Clinicians should be aware of this potential risk to avoid delayed diagnoses. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. Prenatal diagnosis of Caudal Regression Syndrome : a case report

    Directory of Open Access Journals (Sweden)

    Celikaslan Nurgul

    2001-12-01

    Full Text Available Abstract Background Caudal regression is a rare syndrome which has a spectrum of congenital malformations ranging from simple anal atresia to absence of sacral, lumbar and possibly lower thoracic vertebrae, to the most severe form which is known as sirenomelia. Maternal diabetes, genetic predisposition and vascular hypoperfusion have been suggested as possible causative factors. Case presentation We report a case of caudal regression syndrome diagnosed in utero at 22 weeks' of gestation. Prenatal ultrasound examination revealed a sudden interruption of the spine and "frog-like" position of lower limbs. Termination of pregnancy and autopsy findings confirmed the diagnosis. Conclusion Prenatal ultrasonographic diagnosis of caudal regression syndrome is possible at 22 weeks' of gestation by ultrasound examination.

  15. Risk and benefit associated with preventive mammography examinations

    International Nuclear Information System (INIS)

    Vladar, M.; Nikodemova, D.

    1998-01-01

    The risk of mammographic examination was estimated. It is concluded that a mean glandular dose (MGD) of 1 mGy per exposure can be associated with a risk of 1 radiation-induced carcinoma per less than 100 positive detected by the preventive examination. The variability of actual MGD at various hospitals can be quite large. Although the majority of measurements were made on phantoms it is assumed that the national MGD average will exceed 3 mGy for the average breast size of 55 mm

  16. Identification of Sexually Abused Female Adolescents at Risk for Suicidal Ideations: A Classification and Regression Tree Analysis

    Science.gov (United States)

    Brabant, Marie-Eve; Hebert, Martine; Chagnon, Francois

    2013-01-01

    This study explored the clinical profiles of 77 female teenager survivors of sexual abuse and examined the association of abuse-related and personal variables with suicidal ideations. Analyses revealed that 64% of participants experienced suicidal ideations. Findings from classification and regression tree analysis indicated that depression,…

  17. A simple approach to power and sample size calculations in logistic regression and Cox regression models.

    Science.gov (United States)

    Vaeth, Michael; Skovlund, Eva

    2004-06-15

    For a given regression problem it is possible to identify a suitably defined equivalent two-sample problem such that the power or sample size obtained for the two-sample problem also applies to the regression problem. For a standard linear regression model the equivalent two-sample problem is easily identified, but for generalized linear models and for Cox regression models the situation is more complicated. An approximately equivalent two-sample problem may, however, also be identified here. In particular, we show that for logistic regression and Cox regression models the equivalent two-sample problem is obtained by selecting two equally sized samples for which the parameters differ by a value equal to the slope times twice the standard deviation of the independent variable and further requiring that the overall expected number of events is unchanged. In a simulation study we examine the validity of this approach to power calculations in logistic regression and Cox regression models. Several different covariate distributions are considered for selected values of the overall response probability and a range of alternatives. For the Cox regression model we consider both constant and non-constant hazard rates. The results show that in general the approach is remarkably accurate even in relatively small samples. Some discrepancies are, however, found in small samples with few events and a highly skewed covariate distribution. Comparison with results based on alternative methods for logistic regression models with a single continuous covariate indicates that the proposed method is at least as good as its competitors. The method is easy to implement and therefore provides a simple way to extend the range of problems that can be covered by the usual formulas for power and sample size determination. Copyright 2004 John Wiley & Sons, Ltd.

  18. Factors Associated with Hemorrhoids in Korean Adults: Korean National Health and Nutrition Examination Survey

    Science.gov (United States)

    Lee, Jong-Hyun; Kim, Hyo-Eun; Kang, Ji-Hun

    2014-01-01

    Background Although hemorrhoids are one of the most common anal diseases among Koreans, risk factors for hemorrhoids have not been well identified. Methods We analyzed the data from the 4th Korean National Health and Nutrition Examination Survey (KNHANES) between 2007 and 2009. Study subjects were 17,228 participants of KNHANES who were aged 19 years or older. Logistic regression analysis was conducted to evaluate associations between hemorrhoids and probable risk factors. Results Overall prevalence of hemorrhoids among study subjects was 14.4%, being more prevalent among women (15.7%) than among men (13.0%). Obesity and abdominal obesity were associated with a higher risk of hemorrhoids with odds ratio (OR) (95% confidence intervals, 95% CI) of 1.13 (1.01 to 1.26) and 1.16 (1.04 to 1.30), respectively. Both self-reported depression (OR, 1.83; 95% CI, 1.62 to 2.08) and physician diagnosed depression (OR, 1.71; 95% CI, 1.35 to 2.17) were associated with significantly higher risk of hemorrhoids. No regular walking (OR, 1.11; 95% CI, 1.00 to 1.23) and experience of pregnancy (OR, 1.62; 95% CI, 1.17 to 2.25) for women were also associated with higher risk of hemorrhoids. However, educational level, alcohol consumption, physical activities, diabetes mellitus, hypertension, fiber, fat intake, and energy intake were not associated with a risk of hemorrhoids. Low quality of life assessed with EuroQol-5 Dimension and EuroQol-Visual Analogue Scale was significantly associated with hemorrhoids. Conclusion This nationwide cross-sectional study of Korean adults suggests that obesity, abdominal obesity, depression, and past pregnancy may be risk factors for hemorrhoids and hemorrhoids affect quality of life negatively. PMID:25309703

  19. Predictors of course in obsessive-compulsive disorder: logistic regression versus Cox regression for recurrent events.

    Science.gov (United States)

    Kempe, P T; van Oppen, P; de Haan, E; Twisk, J W R; Sluis, A; Smit, J H; van Dyck, R; van Balkom, A J L M

    2007-09-01

    Two methods for predicting remissions in obsessive-compulsive disorder (OCD) treatment are evaluated. Y-BOCS measurements of 88 patients with a primary OCD (DSM-III-R) diagnosis were performed over a 16-week treatment period, and during three follow-ups. Remission at any measurement was defined as a Y-BOCS score lower than thirteen combined with a reduction of seven points when compared with baseline. Logistic regression models were compared with a Cox regression for recurrent events model. Logistic regression yielded different models at different evaluation times. The recurrent events model remained stable when fewer measurements were used. Higher baseline levels of neuroticism and more severe OCD symptoms were associated with a lower chance of remission, early age of onset and more depressive symptoms with a higher chance. Choice of outcome time affects logistic regression prediction models. Recurrent events analysis uses all information on remissions and relapses. Short- and long-term predictors for OCD remission show overlap.

  20. A regression tree for identifying combinations of fall risk factors associated to recurrent falling: a cross-sectional elderly population-based study.

    Science.gov (United States)

    Kabeshova, A; Annweiler, C; Fantino, B; Philip, T; Gromov, V A; Launay, C P; Beauchet, O

    2014-06-01

    Regression tree (RT) analyses are particularly adapted to explore the risk of recurrent falling according to various combinations of fall risk factors compared to logistic regression models. The aims of this study were (1) to determine which combinations of fall risk factors were associated with the occurrence of recurrent falls in older community-dwellers, and (2) to compare the efficacy of RT and multiple logistic regression model for the identification of recurrent falls. A total of 1,760 community-dwelling volunteers (mean age ± standard deviation, 71.0 ± 5.1 years; 49.4 % female) were recruited prospectively in this cross-sectional study. Age, gender, polypharmacy, use of psychoactive drugs, fear of falling (FOF), cognitive disorders and sad mood were recorded. In addition, the history of falls within the past year was recorded using a standardized questionnaire. Among 1,760 participants, 19.7 % (n = 346) were recurrent fallers. The RT identified 14 nodes groups and 8 end nodes with FOF as the first major split. Among participants with FOF, those who had sad mood and polypharmacy formed the end node with the greatest OR for recurrent falls (OR = 6.06 with p falls (OR = 0.25 with p factors for recurrent falls, the combination most associated with recurrent falls involving FOF, sad mood and polypharmacy. The FOF emerged as the risk factor strongly associated with recurrent falls. In addition, RT and multiple logistic regression were not sensitive enough to identify the majority of recurrent fallers but appeared efficient in detecting individuals not at risk of recurrent falls.

  1. Modifiable variables in physical therapy education programs associated with first-time and three-year National Physical Therapy Examination pass rates in the United States

    Directory of Open Access Journals (Sweden)

    Chad Cook

    2015-09-01

    Full Text Available Purpose: This study aimed to examine the modifiable programmatic characteristics reflected in the Commission on Accreditation in Physical Therapy Education (CAPTE Annual Accreditation Report for all accredited programs that reported pass rates on the National Physical Therapist Examination, and to build a predictive model for first-time and three-year ultimate pass rates. Methods: This observational study analyzed programmatic information from the 185 CAPTE-accredited physical therapy programs in the United States and Puerto Rico out of a total of 193 programs that provided the first-time and three-year ultimate pass rates in 2011. Fourteen predictive variables representing student selection and composition, clinical education length and design, and general program length and design were analyzed against first-time pass rates and ultimate pass rates on the NPTE. Univariate and multivariate multinomial regression analysis for first-time pass rates and logistic regression analysis for three-year ultimate pass rates were performed. Results: The variables associated with the first-time pass rate in the multivariate analysis were the mean undergraduate grade point average (GPA and the average age of the cohort. Multivariate analysis showed that mean undergraduate GPA was associated with the three-year ultimate pass rate. Conclusions: Mean undergraduate GPA was found to be the only modifiable predictor for both first-time and three-year pass rates among CAPTE-accredited physical therapy programs.

  2. Age-Related Imbalance Is Associated With Slower Walking Speed: An Analysis From the National Health and Nutrition Examination Survey.

    Science.gov (United States)

    Xie, Yanjun J; Liu, Elizabeth Y; Anson, Eric R; Agrawal, Yuri

    Walking speed is an important dimension of gait function and is known to decline with age. Gait function is a process of dynamic balance and motor control that relies on multiple sensory inputs (eg, visual, proprioceptive, and vestibular) and motor outputs. These sensory and motor physiologic systems also play a role in static postural control, which has been shown to decline with age. In this study, we evaluated whether imbalance that occurs as part of healthy aging is associated with slower walking speed in a nationally representative sample of older adults. We performed a cross-sectional analysis of the previously collected 1999 to 2002 National Health and Nutrition Examination Survey (NHANES) data to evaluate whether age-related imbalance is associated with slower walking speed in older adults aged 50 to 85 years (n = 2116). Balance was assessed on a pass/fail basis during a challenging postural task-condition 4 of the modified Romberg Test-and walking speed was determined using a 20-ft (6.10 m) timed walk. Multivariable linear regression was used to evaluate the association between imbalance and walking speed, adjusting for demographic and health-related covariates. A structural equation model was developed to estimate the extent to which imbalance mediates the association between age and slower walking speed. In the unadjusted regression model, inability to perform the NHANES balance task was significantly associated with 0.10 m/s slower walking speed (95% confidence interval: -0.13 to -0.07; P imbalance mediates 12.2% of the association between age and slower walking speed in older adults. In a nationally representative sample, age-related balance limitation was associated with slower walking speed. Balance impairment may lead to walking speed declines. In addition, reduced static postural control and dynamic walking speed that occur with aging may share common etiologic origins, including the decline in visual, proprioceptive, and vestibular sensory and

  3. Dual Regression

    OpenAIRE

    Spady, Richard; Stouli, Sami

    2012-01-01

    We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional distribution f...

  4. What are patient factors associated with the quality of diabetes care?: results from the Korean National Health and Nutrition Examination Survey

    Directory of Open Access Journals (Sweden)

    Ko Ki

    2012-08-01

    Full Text Available Abstract Background Recently there has been a growing interest in healthcare quality control in Korea. We examined the association between patient factors and quality indicators of diabetic care among Korean adults with diabetes. Methods We obtained a sample of 335 adults aged 20 or older diagnosed with diabetes from the 2005 Korean National Health and Nutrition Examination Survey. Patient factors were divided into two categories: socioeconomic position and health-related factors. Quality indicators for diabetes care were defined as receiving preventive care services for diabetes complications (e.g., fundus examination, microalbuminuria examination, diabetes education and diabetes-related clinical outcomes (e.g., HbA1c, blood pressure, LDL-cholesterol. We performed multiple logistic regression analyses for each quality indicator. Results We found that people with lower education levels or shorter duration of diabetes illness were less likely to receive preventive care services for diabetes complications. Women or people with longer duration of diabetes were less likely to reach the glycemic target. Obese diabetic patients were less likely to accomplish adequate control of blood pressure and LDL-cholesterol. Conclusions Several factors of patients with diabetes, such as education level, duration of illness, gender, and obesity grade are associated with the quality of diabetes care. These findings can help inform policy makers about subpopulations at risk in developing a public health strategy in the future.

  5. Liver Fibrosis Regression Measured by Transient Elastography in Human Immunodeficiency Virus (HIV)-Hepatitis B Virus (HBV)-Coinfected Individuals on Long-Term HBV-Active Combination Antiretroviral Therapy.

    Science.gov (United States)

    Audsley, Jennifer; Robson, Christopher; Aitchison, Stacey; Matthews, Gail V; Iser, David; Sasadeusz, Joe; Lewin, Sharon R

    2016-01-01

    Background.  Advanced fibrosis occurs more commonly in human immunodeficiency virus (HIV)-hepatitis B virus (HBV) coinfected individuals; therefore, fibrosis monitoring is important in this population. However, transient elastography (TE) data in HIV-HBV coinfection are lacking. We aimed to assess liver fibrosis using TE in a cross-sectional study of HIV-HBV coinfected individuals receiving combination HBV-active (lamivudine and/or tenofovir/tenofovir-emtricitabine) antiretroviral therapy, identify factors associated with advanced fibrosis, and examine change in fibrosis in those with >1 TE assessment. Methods.  We assessed liver fibrosis in 70 HIV-HBV coinfected individuals on HBV-active combination antiretroviral therapy (cART). Change in fibrosis over time was examined in a subset with more than 1 TE result (n = 49). Clinical and laboratory variables at the time of the first TE were collected, and associations with advanced fibrosis (≥F3, Metavir scoring system) and fibrosis regression (of least 1 stage) were examined. Results.  The majority of the cohort (64%) had mild to moderate fibrosis at the time of the first TE, and we identified alanine transaminase, platelets, and detectable HIV ribonucleic acid as associated with advanced liver fibrosis. Alanine transaminase and platelets remained independently advanced in multivariate modeling. More than 28% of those with >1 TE subsequently showed liver fibrosis regression, and higher baseline HBV deoxyribonucleic acid was associated with regression. Prevalence of advanced fibrosis (≥F3) decreased 12.3% (32.7%-20.4%) over a median of 31 months. Conclusions.  The observed fibrosis regression in this group supports the beneficial effects of cART on liver stiffness. It would be important to study a larger group of individuals with more advanced fibrosis to more definitively assess factors associated with liver fibrosis regression.

  6. Nonparametric Mixture of Regression Models.

    Science.gov (United States)

    Huang, Mian; Li, Runze; Wang, Shaoli

    2013-07-01

    Motivated by an analysis of US house price index data, we propose nonparametric finite mixture of regression models. We study the identifiability issue of the proposed models, and develop an estimation procedure by employing kernel regression. We further systematically study the sampling properties of the proposed estimators, and establish their asymptotic normality. A modified EM algorithm is proposed to carry out the estimation procedure. We show that our algorithm preserves the ascent property of the EM algorithm in an asymptotic sense. Monte Carlo simulations are conducted to examine the finite sample performance of the proposed estimation procedure. An empirical analysis of the US house price index data is illustrated for the proposed methodology.

  7. Customized Fetal Growth Charts for Parents' Characteristics, Race, and Parity by Quantile Regression Analysis: A Cross-sectional Multicenter Italian Study.

    Science.gov (United States)

    Ghi, Tullio; Cariello, Luisa; Rizzo, Ludovica; Ferrazzi, Enrico; Periti, Enrico; Prefumo, Federico; Stampalija, Tamara; Viora, Elsa; Verrotti, Carla; Rizzo, Giuseppe

    2016-01-01

    The purpose of this study was to construct fetal biometric charts between 16 and 40 weeks' gestation that were customized for parental characteristics, race, and parity, using quantile regression analysis. In a multicenter cross-sectional study, 8070 sonographic examinations from low-risk pregnancies between 16 and 40 weeks' gestation were analyzed. The fetal measurements obtained were biparietal diameter, head circumference, abdominal circumference, and femur diaphysis length. Quantile regression was used to examine the impact of parental height and weight, parity, and race across biometric percentiles for the fetal measurements considered. Paternal and maternal height were significant covariates for all of the measurements considered (P < .05). Maternal weight significantly influenced head circumference, abdominal circumference, and femur diaphysis length. Parity was significantly associated with biparietal diameter and head circumference. Central African race was associated with head circumference and femur diaphysis length, whereas North African race was only associated with femur diaphysis length. In this study we constructed customized biometric growth charts using quantile regression in a large cohort of low-risk pregnancies. These charts offer the advantage of defining individualized normal ranges of fetal biometric parameters at each specific percentile corrected for parental height and weight, parity, and race. This study supports the importance of including these variables in routine sonographic screening for fetal growth abnormalities.

  8. Significance tests to determine the direction of effects in linear regression models.

    Science.gov (United States)

    Wiedermann, Wolfgang; Hagmann, Michael; von Eye, Alexander

    2015-02-01

    Previous studies have discussed asymmetric interpretations of the Pearson correlation coefficient and have shown that higher moments can be used to decide on the direction of dependence in the bivariate linear regression setting. The current study extends this approach by illustrating that the third moment of regression residuals may also be used to derive conclusions concerning the direction of effects. Assuming non-normally distributed variables, it is shown that the distribution of residuals of the correctly specified regression model (e.g., Y is regressed on X) is more symmetric than the distribution of residuals of the competing model (i.e., X is regressed on Y). Based on this result, 4 one-sample tests are discussed which can be used to decide which variable is more likely to be the response and which one is more likely to be the explanatory variable. A fifth significance test is proposed based on the differences of skewness estimates, which leads to a more direct test of a hypothesis that is compatible with direction of dependence. A Monte Carlo simulation study was performed to examine the behaviour of the procedures under various degrees of associations, sample sizes, and distributional properties of the underlying population. An empirical example is given which illustrates the application of the tests in practice. © 2014 The British Psychological Society.

  9. Regression of oral lichenoid lesions after replacement of dental restorations.

    Science.gov (United States)

    Mårell, L; Tillberg, A; Widman, L; Bergdahl, J; Berglund, A

    2014-05-01

    The aim of the study was to determine the prognosis and to evaluate the regression of lichenoid contact reactions (LCR) and oral lichen planus (OLP) after replacement of dental restorative materials suspected as causing the lesions. Forty-four referred patients with oral lesions participated in a follow-up study that was initiated an average of 6 years after the first examination at the Department of Odontology, i.e. the baseline examination. The patients underwent odontological clinical examination and answered a questionnaire with questions regarding dental health, medical and psychological health, and treatments undertaken from baseline to follow-up. After exchange of dental materials, regression of oral lesions was significantly higher among patients with LCR than with OLP. As no cases with OLP regressed after an exchange of materials, a proper diagnosis has to be made to avoid unnecessary exchanges of intact restorations on patients with OLP.

  10. Assessing risk factors for periodontitis using regression

    Science.gov (United States)

    Lobo Pereira, J. A.; Ferreira, Maria Cristina; Oliveira, Teresa

    2013-10-01

    Multivariate statistical analysis is indispensable to assess the associations and interactions between different factors and the risk of periodontitis. Among others, regression analysis is a statistical technique widely used in healthcare to investigate and model the relationship between variables. In our work we study the impact of socio-demographic, medical and behavioral factors on periodontal health. Using regression, linear and logistic models, we can assess the relevance, as risk factors for periodontitis disease, of the following independent variables (IVs): Age, Gender, Diabetic Status, Education, Smoking status and Plaque Index. The multiple linear regression analysis model was built to evaluate the influence of IVs on mean Attachment Loss (AL). Thus, the regression coefficients along with respective p-values will be obtained as well as the respective p-values from the significance tests. The classification of a case (individual) adopted in the logistic model was the extent of the destruction of periodontal tissues defined by an Attachment Loss greater than or equal to 4 mm in 25% (AL≥4mm/≥25%) of sites surveyed. The association measures include the Odds Ratios together with the correspondent 95% confidence intervals.

  11. A case-control study to examine the association between breastfeeding during late pregnancy and risk of a small-for-gestational-age birth in Lima, Peru.

    Science.gov (United States)

    Pareja, Rossina G; Marquis, Grace S; Penny, Mary E; Dixon, Philip M

    2015-04-01

    Excessive demands on maternal nutritional status may be a risk factor for poor birth outcomes. This study examined the association between breastfeeding during late pregnancy (≥ 28 weeks) and the risk of having a small-for-gestational-age (SGA) newborn, using a matched case-control design (78 SGA cases: birthweight project midwives visited daily three government hospitals in Lima, Peru and identified cases and matched controls based on hospital, gestational age, and inter-gestational period. Mothers were interviewed and clinical chart extractions were completed. Factors associated with risk of SGA were assessed by their adjusted odds ratios (aOR) from conditional logistic regression. Exposure to an overlap of breastfeeding during late pregnancy was not associated with an increased risk of having a SGA newborn [aOR=0.58, 95% confidence interval (CI): 0.10-3.30]. However, increased risk was associated with having a previous low-birthweight birth (aOR=6.53; 95% CI: 1.43-29.70) and a low intake of animal source foods (power are needed to definitively examine this possible association and clarify whether there are other risks to the new baby, the toddler and the pregnant woman. © 2012 Blackwell Publishing Ltd.

  12. Sociocultural factors associated with breast self-examination among Iranian women.

    Directory of Open Access Journals (Sweden)

    Seyed Abolhasan Naghibi

    2015-01-01

    Full Text Available Of the ways to fight breast cancer and reduce deaths hazard due to early detection is one of early detection programs in women's breast self- examination. Examining breast by oneself increase individuals knowledge of her breast health that helps in detecting breast cancer early. Different cultural, social, family and individual factors play roles in women's behavior about breast self- examination applying PEN-3 model in this study is to analyze factors influencing on breast self-examination. The research is a descriptive- analytical, cross-sectional type. Research community consists of women at fertility age of 20-49 in sari. Sample volume is 415 individuals and sampling method is cluster method. In this study, a 50-item questionnaire based on PEN-3 was used. Questions were answered by Likert scoring method. Questionnaire was gathered by personal presence of questioners. Data was analyzed via descriptive statistics and logistic regression methods. Based on the study findings, the most significant positive behaviors related to perceptual factors included effectiveness of disease background in family and relatives (73%, believing in breast self- examination for pursuing health (93% and the most important negative behaviors were shyness and modesty (83.9% and increased worry (78.9%. The most remarkable positive behaviors regarding enabling factors covered the skill to do breast examination oneself (35.2%, the availability of health and therapeutic centers (80.7% and the most significant negative behavior was being busy and lack of time (85.3%. The most important positive behavior about nurturing factors included family consent (68.9% and the most significant negative one was the inappropriate treatment of health and therapeutic personnel (61.8%. In this study, there is a meaningful difference between employment ages, education with PEN-3 model constituents. Since behaviors due to enabling and nurturing perceptual factors have been important in

  13. Association of Attorney Advertising and FDA Action with Prescription Claims: A Time Series Segmented Regression Analysis.

    Science.gov (United States)

    Tippett, Elizabeth C; Chen, Brian K

    2015-12-01

    Attorneys sponsor television advertisements that include repeated warnings about adverse drug events to solicit consumers for lawsuits against drug manufacturers. The relationship between such advertising, safety actions by the US Food and Drug Administration (FDA), and healthcare use is unknown. To investigate the relationship between attorney advertising, FDA actions, and prescription drug claims. The study examined total users per month and prescription rates for seven drugs with substantial attorney advertising volume and FDA or other safety interventions during 2009. Segmented regression analysis was used to detect pre-intervention trends, post-intervention level changes, and changes in post-intervention trends relative to the pre-intervention trends in the use of these seven drugs, using advertising volume, media hits, and the number of Medicare enrollees as covariates. Data for these variables were obtained from the Center for Medicare and Medicaid Services, Kantar Media, and LexisNexis. Several types of safety actions were associated with reductions in drug users and/or prescription rates, particularly for fentanyl, varenicline, and paroxetine. In most cases, attorney advertising volume rose in conjunction with major safety actions. Attorney advertising volume was positively correlated with prescription rates in five of seven drugs, likely because advertising volume began rising before safety actions, when prescription rates were still increasing. On the other hand, attorney advertising had mixed associations with the number of users per month. Regulatory and safety actions likely reduced the number of users and/or prescription rates for some drugs. Attorneys may have strategically chosen to begin advertising adverse drug events prior to major safety actions, but we found little evidence that attorney advertising reduced drug use. Further research is needed to better understand how consumers and physicians respond to attorney advertising.

  14. Job characteristics in relation to the prevalence of myocardial infarction in the US Health Examination Survey (HES) and the Health and Nutrition Examination Survey (HANES).

    Science.gov (United States)

    Karasek, R A; Theorell, T; Schwartz, J E; Schnall, P L; Pieper, C F; Michela, J L

    1988-08-01

    Associations between psychosocial job characteristics and past myocardial infarction (MI) prevalence for employed males were tested with the Health Examination Survey (HES) 1960-61, N = 2,409, and the Health and Nutrition Examination Survey (HANES) 1971-75, N = 2,424. A new estimation method is used which imputes to census occupation codes, job characteristic information from national surveys of job characteristics (US Department of Labor, Quality of Employment Surveys). Controlling for age, we find that employed males with jobs which are simultaneously low in decision latitude and high in psychological work load (a multiplicative product term isolating 20 per cent of the population) have a higher prevalence of myocardial infarction in both data bases. In a logistic regression analysis, using job measures adjusted for demographic factors and controlling for age, race, education, systolic blood pressure, serum cholesterol, smoking (HANES only), and physical exertion, we find a low decision latitude/high psychological demand multiplicative product term associated with MI in both data bases. Additional multiple logistic regressions show that low decision latitude is associated with increased prevalence of MI in both the HES and the HANES. Psychological workload and physical exertion are significant only in the HANES.

  15. Regression: A Bibliography.

    Science.gov (United States)

    Pedrini, D. T.; Pedrini, Bonnie C.

    Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…

  16. Advanced statistics: linear regression, part I: simple linear regression.

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

    Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

  17. Testing for marginal linear effects in quantile regression

    KAUST Repository

    Wang, Huixia Judy

    2017-10-23

    The paper develops a new marginal testing procedure to detect significant predictors that are associated with the conditional quantiles of a scalar response. The idea is to fit the marginal quantile regression on each predictor one at a time, and then to base the test on the t-statistics that are associated with the most predictive predictors. A resampling method is devised to calibrate this test statistic, which has non-regular limiting behaviour due to the selection of the most predictive variables. Asymptotic validity of the procedure is established in a general quantile regression setting in which the marginal quantile regression models can be misspecified. Even though a fixed dimension is assumed to derive the asymptotic results, the test proposed is applicable and computationally feasible for large dimensional predictors. The method is more flexible than existing marginal screening test methods based on mean regression and has the added advantage of being robust against outliers in the response. The approach is illustrated by using an application to a human immunodeficiency virus drug resistance data set.

  18. Testing for marginal linear effects in quantile regression

    KAUST Repository

    Wang, Huixia Judy; McKeague, Ian W.; Qian, Min

    2017-01-01

    The paper develops a new marginal testing procedure to detect significant predictors that are associated with the conditional quantiles of a scalar response. The idea is to fit the marginal quantile regression on each predictor one at a time, and then to base the test on the t-statistics that are associated with the most predictive predictors. A resampling method is devised to calibrate this test statistic, which has non-regular limiting behaviour due to the selection of the most predictive variables. Asymptotic validity of the procedure is established in a general quantile regression setting in which the marginal quantile regression models can be misspecified. Even though a fixed dimension is assumed to derive the asymptotic results, the test proposed is applicable and computationally feasible for large dimensional predictors. The method is more flexible than existing marginal screening test methods based on mean regression and has the added advantage of being robust against outliers in the response. The approach is illustrated by using an application to a human immunodeficiency virus drug resistance data set.

  19. Aid and growth regressions

    DEFF Research Database (Denmark)

    Hansen, Henrik; Tarp, Finn

    2001-01-01

    This paper examines the relationship between foreign aid and growth in real GDP per capita as it emerges from simple augmentations of popular cross country growth specifications. It is shown that aid in all likelihood increases the growth rate, and this result is not conditional on ‘good’ policy....... investment. We conclude by stressing the need for more theoretical work before this kind of cross-country regressions are used for policy purposes.......This paper examines the relationship between foreign aid and growth in real GDP per capita as it emerges from simple augmentations of popular cross country growth specifications. It is shown that aid in all likelihood increases the growth rate, and this result is not conditional on ‘good’ policy...

  20. Office workers' computer use patterns are associated with workplace stressors

    NARCIS (Netherlands)

    Eijckelhof, B.H.W.; Huysmans, M.A.; Blatter, B.M.; Leider, P.C.; Johnson, P.W.; van Dieen, J.H.; Dennerlein, J.T.; van der Beek, A.J.

    2014-01-01

    This field study examined associations between workplace stressors and office workers' computer use patterns. We collected keyboard and mouse activities of 93 office workers (68F, 25M) for approximately two work weeks. Linear regression analyses examined the associations between self-reported

  1. Characteristics of utility cyclists in Queensland, Australia: an examination of the associations between individual, social, and environmental factors and utility cycling.

    Science.gov (United States)

    Sahlqvist, Shannon L; Heesch, Kristiann C

    2012-08-01

    Initiatives to promote utility cycling in countries like Australia and the US, which have low rates of utility cycling, may be more effective if they first target recreational cyclists. This study aimed to describe patterns of utility cycling and examine its correlates, among cyclists in Queensland, Australia. An online survey was administered to adult members of a state-based cycling community and advocacy group (n=1813). The survey asked about demographic characteristics and cycling behavior, motivators and constraints. Utility cycling patterns were described, and logistic regression modeling was used to examine associations between utility cycling and other variables. Forty-seven percent of respondents reported utility cycling: most did so to commute (86%). Most journeys (83%) were >5 km. Being male, younger, employed full-time, or university-educated increased the likelihood of utility cycling (P<.05). Perceiving cycling to be a cheap or a convenient form of transport was associated with utility cycling (P<.05). The moderate rate of utility cycling among recreational cyclists highlights a potential to promote utility cycling among this group. To increase utility cycling, strategies should target female and older recreational cyclists and focus on making cycling a cheap and convenient mode of transport.

  2. The Association of Metabolic Syndrome with Diabetic Retinopathy: The Korean National Health and Nutrition Examination Survey 2008-2012.

    Directory of Open Access Journals (Sweden)

    Tai Kyong Kim

    Full Text Available To explore gender differences and associations between metabolic syndrome (MetS and its components, and diabetic retinopathy (DR in Korean adults aged 40 years and older with diabetes.We analyzed data from the Korean National Health and Nutrition Examination Surveys (2008-2012. In total, 2,576 type 2 diabetic participants, aged 40 and older, were evaluated. Seven standard retinal fundus photographs were obtained after pupil dilation in both eyes. DR was graded using the modified Airlie House classification system. Vision-threatening diabetic retinopathy (VTDR included proliferative diabetic retinopathy and clinically significant macular edema. MetS was defined according to the Joint Interim Statement, proposed in 2009, by the International Diabetes Federation and the American Heart Association/National Heart, Lung, and Blood Institute. Multivariate logistic regression analysis was used to assess the relationship between MetS and its individual components with DR and VTDR.After controlling for confounders, MetS was not associated with DR in men or women. Moreover, the risk for DR or VTDR did not increase with increasing MetS components. However, high waist circumference was significantly inversely associated with VTDR (adjusted odds ratio = 0.36; 95% confidence interval = 0.14-0.93 only in men.MetS was not associated with DR or VTDR in a Korean diabetic population. However, among MetS components, it seems that abdominal obesity was inversely associated with VTDR in Korean diabetic men.

  3. Performance on the Cardiovascular In-Training Examination in Relation to the ABIM Cardiovascular Disease Certification Examination.

    Science.gov (United States)

    Indik, Julia H; Duhigg, Lauren M; McDonald, Furman S; Lipner, Rebecca S; Rubright, Jonathan D; Haist, Steven A; Botkin, Naomi F; Kuvin, Jeffrey T

    2017-06-13

    The American College of Cardiology In-Training Exam (ACC-ITE) is incorporated into most U.S. training programs, but its relationship to performance on the American Board of Internal Medicine Cardiovascular Disease (ABIM CVD) Certification Examination is unknown. ACC-ITE scores from third-year fellows from 2011 to 2014 (n = 1,918) were examined. Covariates for regression analyses included sex, age, medical school country, U.S. Medical Licensing Examination Step, and ABIM Internal Medicine Certification Examination scores. A secondary analysis examined fellows (n = 511) who took the ACC-ITE in the first and third years. ACC-ITE scores were the strongest predictor of ABIM CVD scores (p ITE scores from first to third year was a strong predictor of the ABIM CVD score (p ITE is strongly associated with performance on the ABIM CVD Certification Examination. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

  4. Reported Theory Use by Digital Interventions for Hazardous and Harmful Alcohol Consumption, and Association With Effectiveness: Meta-Regression

    Science.gov (United States)

    Crane, David; Brown, Jamie; Kaner, Eileen; Beyer, Fiona; Muirhead, Colin; Hickman, Matthew; Redmore, James; de Vocht, Frank; Beard, Emma; Michie, Susan

    2018-01-01

    Background Applying theory to the design and evaluation of interventions is likely to increase effectiveness and improve the evidence base from which future interventions are developed, though few interventions report this. Objective The aim of this paper was to assess how digital interventions to reduce hazardous and harmful alcohol consumption report the use of theory in their development and evaluation, and whether reporting of theory use is associated with intervention effectiveness. Methods Randomized controlled trials were extracted from a Cochrane review on digital interventions for reducing hazardous and harmful alcohol consumption. Reporting of theory use within these digital interventions was investigated using the theory coding scheme (TCS). Reported theory use was analyzed by frequency counts and descriptive statistics. Associations were analyzed with meta-regression models. Results Of 41 trials involving 42 comparisons, half did not mention theory (50% [21/42]), and only 38% (16/42) used theory to select or develop the intervention techniques. Significant heterogeneity existed between studies in the effect of interventions on alcohol reduction (I2=77.6%, Ptheory use and intervention effectiveness in unadjusted models, though the meta-regression was underpowered to detect modest associations. Conclusions Digital interventions offer a unique opportunity to refine and develop new dynamic, temporally sensitive theories, yet none of the studies reported refining or developing theory. Clearer selection, application, and reporting of theory use is needed to accurately assess how useful theory is in this field and to advance the field of behavior change theories. PMID:29490895

  5. Impact of performance grading on annual numbers of acute myocardial infarction-associated emergency department visits in Taiwan: Results of segmented regression analysis.

    Science.gov (United States)

    Tzeng, I-Shiang; Liu, Su-Hsun; Chen, Kuan-Fu; Wu, Chin-Chieh; Chen, Jih-Chang

    2016-10-01

    To reduce patient boarding time at the emergency department (ED) and to improve the overall quality of the emergent care system in Taiwan, the Minister of Health and Welfare of Taiwan (MOHW) piloted the Grading Responsible Hospitals for Acute Care (GRHAC) audit program in 2007-2009.The aim of the study was to evaluate the impact of the GRHAC audit program on the identification and management of acute myocardial infarction (AMI)-associated ED visits by describing and comparing the incidence of AMI-associated ED visits before (2003-2007), during (2007-2009), and after (2009-2012) the initial audit program implementation.Using aggregated data from the MOHW of Taiwan, we estimated the annual incidence of AMI-associated ED visits by Poisson regression models. We used segmented regression techniques to evaluate differences in the annual rates and in the year-to-year changes in AMI-associated ED visits between 2003 and 2012. Medical comorbidities such as diabetes mellitus, hyperlipidemia, and hypertensive disease were considered as potential confounders.Overall, the number of AMI-associated patient visits increased from 8130 visits in 2003 to 12,695 visits in 2012 (P-value for trend capacity for timely and correctly diagnosing and managing patients presenting with AMI-associated symptoms or signs at the ED.

  6. Regression-based approach for testing the association between multi-region haplotype configuration and complex trait

    Directory of Open Access Journals (Sweden)

    Zhao Hongbo

    2009-09-01

    Full Text Available Abstract Background It is quite common that the genetic architecture of complex traits involves many genes and their interactions. Therefore, dealing with multiple unlinked genomic regions simultaneously is desirable. Results In this paper we develop a regression-based approach to assess the interactions of haplotypes that belong to different unlinked regions, and we use score statistics to test the null hypothesis of non-genetic association. Additionally, multiple marker combinations at each unlinked region are considered. The multiple tests are settled via the minP approach. The P value of the "best" multi-region multi-marker configuration is corrected via Monte-Carlo simulations. Through simulation studies, we assess the performance of the proposed approach and demonstrate its validity and power in testing for haplotype interaction association. Conclusion Our simulations showed that, for binary trait without covariates, our proposed methods prove to be equal and even more powerful than htr and hapcc which are part of the FAMHAP program. Additionally, our model can be applied to a wider variety of traits and allow adjustment for other covariates. To test the validity, our methods are applied to analyze the association between four unlinked candidate genes and pig meat quality.

  7. Psychosocial predictors of breast self-examination behavior among female students: an application of the health belief model using logistic regression.

    Science.gov (United States)

    Didarloo, Alireza; Nabilou, Bahram; Khalkhali, Hamid Reza

    2017-11-03

    Breast cancer is a life-threatening condition affecting women around the world. The early detection of breast lumps using a breast self-examination (BSE) is important for the prevention and control of this disease. The aim of this study was to examine BSE behavior and its predictive factors among female university students using the Health Belief Model (HBM). This investigation was a cross-sectional survey carried out with 334 female students at Urmia University of Medical Sciences in the northwest of Iran. To collect the necessary data, researchers applied a valid and reliable three-part questionnaire. The data were analyzed using descriptive statistics and a chi-square test, in addition to multivariate logistic regression statistics in SPSS software version 16.0 (SPSS Inc., Chicago, IL, USA). The results indicated that 82 of the 334 participants (24.6%) reported practicing BSEs. Multivariate logistic regression analyses showed that high perceived severity [OR = 2.38, 95% CI = (1.02-5.54)], high perceived benefits [OR = 1.94, 95% CI = (1.09-3.46)], and high perceived self-efficacy [OR = 13.15, 95% CI = (3.64-47.51)] were better predictors of BSE behavior (P < 0.05) than low perceived severity, benefits, and self-efficacy. The findings also showed that a high level of knowledge compared to a low level of knowledge [OR = 5.51, 95% CI = (1.79-16.86)] and academic undergraduate and graduate degrees compared to doctoral degrees [OR = 2.90, 95% CI = (1.42-5.92)] of the participants were predictors of BSE performance (P < 0.05). The study revealed that the HBM constructs are able to predict BSE behavior. Among these constructs, self-efficacy was the most important predictor of the behavior. Interventions based on the constructs of perceived self-efficacy, benefits, and severity are recommended for increasing women's regular screening for breast cancer.

  8. Examining empathy and its association with aggression in young ...

    African Journals Online (AJOL)

    Objective: In a context of disturbing rates of violent crime, this pilot study initiated examination of the association between empathy and aggressive behaviour in young Western Cape children. Establishing which empathy measures are appropriate for our context was a primary concern. Method: To capture various aspects of ...

  9. Spontaneous regression of metastatic Merkel cell carcinoma.

    LENUS (Irish Health Repository)

    Hassan, S J

    2010-01-01

    Merkel cell carcinoma is a rare aggressive neuroendocrine carcinoma of the skin predominantly affecting elderly Caucasians. It has a high rate of local recurrence and regional lymph node metastases. It is associated with a poor prognosis. Complete spontaneous regression of Merkel cell carcinoma has been reported but is a poorly understood phenomenon. Here we present a case of complete spontaneous regression of metastatic Merkel cell carcinoma demonstrating a markedly different pattern of events from those previously published.

  10. Comorbid anxiety disorders alter the association between cardiovascular diseases and depression: the German National Health Interview and Examination Survey.

    Science.gov (United States)

    Tully, Phillip J; Baune, Bernhard T

    2014-05-01

    This study aims to examine whether specific anxiety disorder comorbidity alters the purported association between depression and specific cardiovascular diseases (CVDs). In 4,181 representative German participants of the general population, 12-month prevalence of psychiatric disorders was assessed through the Composite International Diagnostic Interview and CVDs by physician verified diagnosis. Adjusting for conventional risk factors logistic regression analyzed the association between CVDs (peripheral vascular disease (PVD), hypertension, cerebrovascular disease and heart disease) and combinations of comorbidity between depression and anxiety disorder types (panic disorder, specific phobia, social phobia and generalized anxiety). There were 770 cases of hypertension (18.4 %), 763 cases of cerebrovascular disease (18.2 %), 748 cases of PVD (17.9 %), and 1,087 cases of CVD (26.0 %). In adjusted analyses phobia comorbid with depression was associated with cerebrovascular disease (odds ratio (OR) 1.61; 95 % confidence interval (CI) 1.04-2.50) as was panic disorder (OR 2.89; 95 % CI 1.47-5.69). PVD was significantly associated with panic disorder (adjusted OR 2.97; 95 % CI 1.55-5.69). Panic disorder was associated with CVDs (adjusted OR 2.28; 95 % CI 1.09-4.77) as was phobia (adjusted OR 1.35; 95 % CI 1.04-1.78). Classification of anxiety and depression according to comorbidity groups showed discrete effects for panic disorder and specific phobia with CVDs, independent from covariates and depression.

  11. A prospective cohort study to examine the association between dietary patterns and depressive symptoms in older Chinese people in Hong Kong.

    Directory of Open Access Journals (Sweden)

    Ruth Chan

    Full Text Available Dietary patterns are culturally specific and there is limited data on the association of dietary patterns with late-life depression in Chinese. This study examined the associations between dietary patterns and baseline and subsequent depressive symptoms in community-dwelling Chinese older people in Hong Kong.Participants aged ≥65 year participating in a cohort study examining the risk factors for osteoporosis completed a validated food frequency questionnaire at baseline between 2001 and 2003. Factor analysis was used to identify three dietary patterns: "vegetables-fruits" pattern, "snacks-drinks-milk products" pattern, and "meat-fish" pattern. Depressive symptoms were measured at baseline and 4-year using the validated Geriatric Depression Scale. Multiple logistic regression was used for cross-sectional analysis (n = 2,902 to assess the associations between dietary patterns and the presence of depressive symptoms, and for longitudinal analysis (n = 2,211 on their associations with 4-year depressive symptoms, with adjustment for socio-demographic and lifestyle factors.The highest quartile of "vegetables-fruits" pattern score was associated with reduced likelihood of depressive symptoms [Adjusted OR = 0.55 (95% CI: 0.36-0.83, ptrend = 0.017] compared to the lowest quartile at baseline. Similar inverse trend was observed for the highest quartile of "snacks-drinks-milk products" pattern score [Adjusted OR = 0.41 (95% CI: 0.26-0.65, ptrend<0.001] compared to the lowest quartile. There was no association of "meat-fish" pattern with the presence of depressive symptoms at baseline. None of the dietary patterns were associated with subsequent depressive symptoms at 4-year.Higher "vegetables-fruits" and "snacks-drinks-milk products" pattern scores were associated with reduced likelihood of baseline depressive symptoms in Chinese older people in Hong Kong. The longitudinal analyses failed to show any causal relationship between

  12. Association of vegetables and fruits consumption with sarcopenia in older adults: the Fourth Korea National Health and Nutrition Examination Survey.

    Science.gov (United States)

    Kim, Jinhee; Lee, Yunhwan; Kye, Seunghee; Chung, Yoon-Sok; Kim, Kwang-Min

    2015-01-01

    several studies have found nutrients, including antioxidants, to be associated with sarcopenia. However, whether specific foods, such as vegetables and fruits, are associated with sarcopenia has not been studied. to examine the association of the frequency of vegetables and fruits consumption with sarcopenia in older people. this study used cross-sectional data from the Fourth Korea National Health and Nutrition Examination Survey in 2008-09. Subjects were community-dwelling 823 men and 1,089 women aged ≥65 years. Frequency of food group consumption was obtained by using the food frequency questionnaire. Body composition was measured with the dual-energy X-ray absorptiometry and sarcopenia was defined as appendicular lean mass adjusted for height and fat mass. Logistic regression was used to assess the association of the frequency of food group consumption with sarcopenia, controlling for sociodemographics and health-related variables. dietary intake of vegetables, fruits and both vegetables and fruits was associated with a significantly reduced risk of sarcopenia after controlling for covariates in men (P = 0.026 for trend, P = 0.012 for trend, P = 0.003 for trend, respectively). Men in the highest quintile, compared with those in the lowest quintile, of vegetables [odds ratio (OR) = 0.48; 95% confidence interval (CI): 0.24-0.95], fruits (OR = 0.30; 95% CI: 0.13-0.70) and vegetables and fruits consumption (OR = 0.32; 95% CI: 0.16-0.67) demonstrated a lower risk of sarcopenia. In women, high consumption of fruits demonstrated a lower risk of sarcopenia (OR = 0.39; 95% CI: 0.18-0.83). frequent vegetables and fruits consumption was inversely associated with sarcopenia in older adults. © The Author 2014. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  13. Polynomial regression analysis and significance test of the regression function

    International Nuclear Information System (INIS)

    Gao Zhengming; Zhao Juan; He Shengping

    2012-01-01

    In order to analyze the decay heating power of a certain radioactive isotope per kilogram with polynomial regression method, the paper firstly demonstrated the broad usage of polynomial function and deduced its parameters with ordinary least squares estimate. Then significance test method of polynomial regression function is derived considering the similarity between the polynomial regression model and the multivariable linear regression model. Finally, polynomial regression analysis and significance test of the polynomial function are done to the decay heating power of the iso tope per kilogram in accord with the authors' real work. (authors)

  14. Is breakfast skipping associated with physical activity among U.S. adolescents? A cross-sectional study of adolescents aged 12-19 years, National Health and Nutrition Examination Survey (NHANES).

    Science.gov (United States)

    Lyerly, Jordan E; Huber, Larissa R; Warren-Findlow, Jan; Racine, Elizabeth F; Dmochowski, Jacek

    2014-04-01

    To examine the association between breakfast skipping and physical activity among US adolescents aged 12-19 years. A cross-sectional study of nationally representative 2007-2008 National Health and Nutrition Examination Survey (NHANES) data. Breakfast skipping was assessed by two 24 h dietary recalls. Physical activity was self-reported by participants and classified based on meeting national recommendations for physical activity for the appropriate age group. Multiple logistic regression analysis was used to model the association between breakfast skipping and physical activity while controlling for confounders. A total of 936 adolescents aged 12-19 years in the USA. After adjusting for family income, there was no association between breakfast skipping and meeting physical activity guidelines for age among adolescents aged 12-19 years (OR = 0.95, 95% CI 0.56, 1.32). Findings from the study differ from previous research findings on breakfast skipping and physical activity. Therefore, further research that uses large, nationally representative US samples and national recommended guidelines for physical activity is needed.

  15. Support Vector Regression Model Based on Empirical Mode Decomposition and Auto Regression for Electric Load Forecasting

    Directory of Open Access Journals (Sweden)

    Hong-Juan Li

    2013-04-01

    Full Text Available Electric load forecasting is an important issue for a power utility, associated with the management of daily operations such as energy transfer scheduling, unit commitment, and load dispatch. Inspired by strong non-linear learning capability of support vector regression (SVR, this paper presents a SVR model hybridized with the empirical mode decomposition (EMD method and auto regression (AR for electric load forecasting. The electric load data of the New South Wales (Australia market are employed for comparing the forecasting performances of different forecasting models. The results confirm the validity of the idea that the proposed model can simultaneously provide forecasting with good accuracy and interpretability.

  16. Reduced Rank Regression

    DEFF Research Database (Denmark)

    Johansen, Søren

    2008-01-01

    The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

  17. Five cases of caudal regression with an aberrant abdominal umbilical artery: Further support for a caudal regression-sirenomelia spectrum.

    Science.gov (United States)

    Duesterhoeft, Sara M; Ernst, Linda M; Siebert, Joseph R; Kapur, Raj P

    2007-12-15

    Sirenomelia and caudal regression have sparked centuries of interest and recent debate regarding their classification and pathogenetic relationship. Specific anomalies are common to both conditions, but aside from fusion of the lower extremities, an aberrant abdominal umbilical artery ("persistent vitelline artery") has been invoked as the chief anatomic finding that distinguishes sirenomelia from caudal regression. This observation is important from a pathogenetic viewpoint, in that diversion of blood away from the caudal portion of the embryo through the abdominal umbilical artery ("vascular steal") has been proposed as the primary mechanism leading to sirenomelia. In contrast, caudal regression is hypothesized to arise from primary deficiency of caudal mesoderm. We present five cases of caudal regression that exhibit an aberrant abdominal umbilical artery similar to that typically associated with sirenomelia. Review of the literature identified four similar cases. Collectively, the series lends support for a caudal regression-sirenomelia spectrum with a common pathogenetic basis and suggests that abnormal umbilical arterial anatomy may be the consequence, rather than the cause, of deficient caudal mesoderm. (c) 2007 Wiley-Liss, Inc.

  18. Quantile Regression With Measurement Error

    KAUST Repository

    Wei, Ying

    2009-08-27

    Regression quantiles can be substantially biased when the covariates are measured with error. In this paper we propose a new method that produces consistent linear quantile estimation in the presence of covariate measurement error. The method corrects the measurement error induced bias by constructing joint estimating equations that simultaneously hold for all the quantile levels. An iterative EM-type estimation algorithm to obtain the solutions to such joint estimation equations is provided. The finite sample performance of the proposed method is investigated in a simulation study, and compared to the standard regression calibration approach. Finally, we apply our methodology to part of the National Collaborative Perinatal Project growth data, a longitudinal study with an unusual measurement error structure. © 2009 American Statistical Association.

  19. Quantile Regression Methods

    DEFF Research Database (Denmark)

    Fitzenberger, Bernd; Wilke, Ralf Andreas

    2015-01-01

    if the mean regression model does not. We provide a short informal introduction into the principle of quantile regression which includes an illustrative application from empirical labor market research. This is followed by briefly sketching the underlying statistical model for linear quantile regression based......Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights...... by modeling conditional quantiles. Quantile regression can therefore detect whether the partial effect of a regressor on the conditional quantiles is the same for all quantiles or differs across quantiles. Quantile regression can provide evidence for a statistical relationship between two variables even...

  20. Multivariate Linear Regression and CART Regression Analysis of TBM Performance at Abu Hamour Phase-I Tunnel

    Science.gov (United States)

    Jakubowski, J.; Stypulkowski, J. B.; Bernardeau, F. G.

    2017-12-01

    The first phase of the Abu Hamour drainage and storm tunnel was completed in early 2017. The 9.5 km long, 3.7 m diameter tunnel was excavated with two Earth Pressure Balance (EPB) Tunnel Boring Machines from Herrenknecht. TBM operation processes were monitored and recorded by Data Acquisition and Evaluation System. The authors coupled collected TBM drive data with available information on rock mass properties, cleansed, completed with secondary variables and aggregated by weeks and shifts. Correlations and descriptive statistics charts were examined. Multivariate Linear Regression and CART regression tree models linking TBM penetration rate (PR), penetration per revolution (PPR) and field penetration index (FPI) with TBM operational and geotechnical characteristics were performed for the conditions of the weak/soft rock of Doha. Both regression methods are interpretable and the data were screened with different computational approaches allowing enriched insight. The primary goal of the analysis was to investigate empirical relations between multiple explanatory and responding variables, to search for best subsets of explanatory variables and to evaluate the strength of linear and non-linear relations. For each of the penetration indices, a predictive model coupling both regression methods was built and validated. The resultant models appeared to be stronger than constituent ones and indicated an opportunity for more accurate and robust TBM performance predictions.

  1. Association between pre-transplant dialysis modality and patient and graft survival after kidney transplantation

    DEFF Research Database (Denmark)

    Kramer, Anneke; Jager, Kitty J; Fogarty, Damian G

    2012-01-01

    Previous studies have found inconsistent associations between pre-transplant dialysis modality and subsequent post-transplant survival. We aimed to examine this relationship using the instrumental variable method and to compare the results with standard Cox regression.......Previous studies have found inconsistent associations between pre-transplant dialysis modality and subsequent post-transplant survival. We aimed to examine this relationship using the instrumental variable method and to compare the results with standard Cox regression....

  2. The number of subjects per variable required in linear regression analyses

    NARCIS (Netherlands)

    P.C. Austin (Peter); E.W. Steyerberg (Ewout)

    2015-01-01

    textabstractObjectives To determine the number of independent variables that can be included in a linear regression model. Study Design and Setting We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression

  3. Regression Analysis to Identify Factors Associated with Urinary Iodine Concentration at the Sub-National Level in India, Ghana, and Senegal

    Science.gov (United States)

    Knowles, Jacky; Kupka, Roland; Dumble, Sam; Garrett, Greg S.; Pandav, Chandrakant S.; Yadav, Kapil; Touré, Ndeye Khady; Foriwa Amoaful, Esi; Gorstein, Jonathan

    2018-01-01

    Single and multiple variable regression analyses were conducted using data from stratified, cluster sample design, iodine surveys in India, Ghana, and Senegal to identify factors associated with urinary iodine concentration (UIC) among women of reproductive age (WRA) at the national and sub-national level. Subjects were survey household respondents, typically WRA. For all three countries, UIC was significantly different (p regression analysis, UIC was significantly associated with strata and household salt iodine category in India and Ghana (p < 0.001). Estimated UIC was 1.6 (95% confidence intervals (CI) 1.3, 2.0) times higher (India) and 1.4 (95% CI 1.2, 1.6) times higher (Ghana) among WRA from households using adequately iodised salt than among WRA from households using non-iodised salt. Other significant associations with UIC were found in India, with having heard of iodine deficiency (1.2 times higher; CI 1.1, 1.3; p < 0.001) and having improved dietary diversity (1.1 times higher, CI 1.0, 1.2; p = 0.015); and in Ghana, with the level of tomato paste consumption the previous week (p = 0.029) (UIC for highest consumption level was 1.2 times lowest level; CI 1.1, 1.4). No significant associations were found in Senegal. Sub-national data on iodine status are required to assess equity of access to optimal iodine intake and to develop strategic responses as needed. PMID:29690505

  4. Germplasm-regression-combined marker-trait association ...

    African Journals Online (AJOL)

    STORAGESEVER

    2010-02-01

    susceptible genotypes from different parts of south India. RAPD and. SSR ... Fiber length (FL). 100 individuals SSR,. RAPD and. ISSR. MRA. Four. SSR markers associated with FL, PB15 of them could identify as high as 75% long ...

  5. [Factors associated with activities of daily living (ADL) in independently living elderly persons in a community: a baseline examination of a large scale cohort study, Fujiwara-kyo study].

    Science.gov (United States)

    Komatsu, Masayo; Nezu, Satoko; Tomioka, Kimiko; Hazaki, Kan; Harano, Akihiro; Morikawa, Masayuki; Takagi, Masahiro; Yamada, Masahiro; Matsumoto, Yoshitaka; Iwamoto, Junko; Ishizuka, Rika; Saeki, Keigo; Okamoto, Nozomi; Kurumatani, Norio

    2013-01-01

    To investigate factors associated with activities of daily living in independently living elderly persons in a community. The potential subjects were 4,472 individuals aged 65 years and older who voluntarily participated in a large cohort study, the Fujiwara-kyo study. We used self-administered questionnaires consisting of an activities of daily living (ADL) questionnaire with the Physical Fitness Test established by the Ministry of Education, Culture, Sports, Science and Technology (12 ADL items) to determine the index of higher-level physical independence, demographics, Geriatric Depression Scale, and so on. Mini-mental state examination, measurement of physical fitness, and blood tests were also carried out. A lower ADL level was defined as having a total score of the 12 ADL items (range, 12-36 points) that was below the first quartile of a total score for all the subjects. Factors associated with a low ADL level were examined by multiple logistic regression. A total of 4,198 remained as subjects for analysis. The male, female and 5-year-old groups showed significant differences in the median score of 12 ADL items between any two groups. The highest odds ratio among factors associated with lower ADL level by multiple logistic regression with mutually adjusted independent variables was 4.49 (95%CI: 2.82-7.17) in the groups of "very sharp pain" or "strong pain" during the last month. Low physical ability, self-awareness of limb weakness, a BMI of over 25, low physical activity, cerebrovascular disorder, depression, low cognitive function, unable "to see normally", unable "to hear someone", "muscle, bone and joint pain" were independently associated with lower ADL level. Multiple factors are associated with lower ADL level assessed on the basis of the 12 ADL items.

  6. A Poisson Regression Examination of the Relationship between Website Traffic and Search Engine Queries

    OpenAIRE

    Tierney, Heather L.R.; Pan, Bing

    2010-01-01

    A new area of research involves the use of Google data, which has been normalized and scaled to predict economic activity. This new source of data holds both many advantages as well as disadvantages, which are discussed through the use of daily and weekly data. Daily and weekly data are employed to show the effect of aggregation as it pertains to Google data, which can lead to contradictory findings. In this paper, Poisson regressions are used to explore the relationship between the online...

  7. Examining the association between late-life leisure activity participation and global cognitive decline in community-dwelling elderly Chinese in Hong Kong.

    Science.gov (United States)

    Leung, Grace Tak Yu; Fung, Ada Wai Tung; Tam, Cindy Woon Chi; Lui, Victor Wing Cheong; Chiu, Helen Fung Kum; Chan, Wai Man; Lam, Linda Chiu Wa

    2011-01-01

    This study examines the association between late-life leisure activity participation and global cognitive decline in community-dwelling elderly Chinese in Hong Kong. Five hundred and five participants, not clinically demented at the baseline, were analysed in the follow-up study of a population-based community survey among Hong Kong Chinese aged 60 and over. Information regarding leisure activity participation, global cognitive function and important sociodemographic variables was collected. Late life leisure activity profiles were classified into intellectual, social, physical and recreational categories, and were measured by total hours per week, total frequency and total number of subtypes. Multivariate logistic regression analyses were used to evaluate the association between leisure activity participation at the baseline and the incidence of global cognitive decline at the 22-month follow-up. The incidence of global cognitive decline was defined as a one-point drop in z-score of the Cantonese version of the mini-mental state examination (CMMSE). At the follow-up, a higher level of participation in intellectual activities was significantly associated with a lower incidence of global cognitive decline as measured by both the total hours per week (multivariate-adjusted OR 0.97 (95% CI 0.94-0.99, p=0.003)), and the total number of subtypes (multivariate-adjusted OR 0.74 (95% CI 0.58-0.95, p=0.018)). A higher level of late-life intellectual activity participation was associated with less global cognitive decline among community-dwelling elderly Chinese in Hong Kong. Copyright © 2010 John Wiley & Sons, Ltd.

  8. New approaches for examining associations with latent categorical variables: applications to substance abuse and aggression.

    Science.gov (United States)

    Feingold, Alan; Tiberio, Stacey S; Capaldi, Deborah M

    2014-03-01

    Assessments of substance use behaviors often include categorical variables that are frequently related to other measures using logistic regression or chi-square analysis. When the categorical variable is latent (e.g., extracted from a latent class analysis [LCA]), classification of observations is often used to create an observed nominal variable from the latent one for use in a subsequent analysis. However, recent simulation studies have found that this classical 3-step analysis championed by the pioneers of LCA produces underestimates of the associations of latent classes with other variables. Two preferable but underused alternatives for examining such linkages-each of which is most appropriate under certain conditions-are (a) 3-step analysis, which corrects the underestimation bias of the classical approach, and (b) 1-step analysis. The purpose of this article is to dissuade researchers from conducting classical 3-step analysis and to promote the use of the 2 newer approaches that are described and compared. In addition, the applications of these newer models-for use when the independent, the dependent, or both categorical variables are latent-are illustrated through substantive analyses relating classes of substance abusers to classes of intimate partner aggressors.

  9. Toward a panoramic perspective of the association between environmental factors and cardiovascular disease: An environment-wide association study from National Health and Nutrition Examination Survey 1999-2014.

    Science.gov (United States)

    Zhuang, Xiaodong; Guo, Yue; Ni, Ao; Yang, Daya; Liao, Lizhen; Zhang, Shaozhao; Zhou, Huimin; Sun, Xiuting; Wang, Lichun; Wang, Xueqin; Liao, Xinxue

    2018-06-04

    An environment-wide association study (EWAS) may be useful to comprehensively test and validate associations between environmental factors and cardiovascular disease (CVD) in an unbiased manner. Data from National Health and Nutrition Examination Survey (1999-2014) were randomly 50:50 spilt into training set and testing set. CVD was ascertained by a self-reported diagnosis of myocardial infarction, coronary heart disease or stroke. We performed multiple linear regression analyses associating 203 environmental factors and 132 clinical phenotypes with CVD in training set (false discovery rate multicollinearity elimination and variable importance ranking. Discriminative power of factors for CVD was calculated by area under the receiver operating characteristic (AUROC). Overall, 43,568 participants with 4084 (9.4%) CVD were included. After adjusting for age, sex, race, body mass index, blood pressure and socio-economic level, we identified 5 environmental variables and 19 clinical phenotypes associated with CVD in training and testing dataset. Top five factors in RF importance ranking were: waist, glucose, uric acid, and red cell distribution width and glycated hemoglobin. AUROC of the RF model was 0.816 (top 5 factors) and 0.819 (full model). Sensitivity analyses reveal no specific moderators of the associations. Our systematic evaluation provides new knowledge on the complex array of environmental correlates of CVD. These identified correlates may serve as a complementary approach to CVD risk assessment. Our findings need to be probed in further observational and interventional studies. Copyright © 2018. Published by Elsevier Ltd.

  10. Regression Phalanxes

    OpenAIRE

    Zhang, Hongyang; Welch, William J.; Zamar, Ruben H.

    2017-01-01

    Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems. A phalanx is a subset of features that work well for classification tasks. In this paper, we propose a different class of phalanxes for application in regression settings. We define a "Regression Phalanx" - a subset of features that work well together for prediction. We propose a novel algorithm which automatically chooses Regression Phalanxes from high-dimensi...

  11. Do clinical data and human papilloma virus genotype influence spontaneous regression in grade I cervical intraepithelial neoplasia?

    Science.gov (United States)

    Cortés-Alaguero, Caterina; González-Mirasol, Esteban; Morales-Roselló, José; Poblet-Martinez, Enrique

    2017-03-15

    To determine whether medical history, clinical examination and human papilloma virus (HPV) genotype influence spontaneous regression in cervical intraepithelial neoplasia grade I (CIN-I). We retrospectively evaluated 232 women who were histologically diagnosed as have CIN-I by means of Kaplan-Meier curves, the pattern of spontaneous regression according to the medical history, clinical examination, and HPV genotype. Spontaneous regression occurred in most patients and was influenced by the presence of multiple HPV genotypes but not by the HPV genotype itself. In addition, regression frequency was diminished when more than 50% of the cervix surface was affected or when an abnormal cytology was present at the beginning of follow-up. The frequency of regression in CIN-I is high, making long-term follow-up and conservative management advisable. Data from clinical examination and HPV genotyping might help to anticipate which lesions will regress.

  12. Reported Theory Use by Digital Interventions for Hazardous and Harmful Alcohol Consumption, and Association With Effectiveness: Meta-Regression.

    Science.gov (United States)

    Garnett, Claire; Crane, David; Brown, Jamie; Kaner, Eileen; Beyer, Fiona; Muirhead, Colin; Hickman, Matthew; Redmore, James; de Vocht, Frank; Beard, Emma; Michie, Susan

    2018-02-28

    Applying theory to the design and evaluation of interventions is likely to increase effectiveness and improve the evidence base from which future interventions are developed, though few interventions report this. The aim of this paper was to assess how digital interventions to reduce hazardous and harmful alcohol consumption report the use of theory in their development and evaluation, and whether reporting of theory use is associated with intervention effectiveness. Randomized controlled trials were extracted from a Cochrane review on digital interventions for reducing hazardous and harmful alcohol consumption. Reporting of theory use within these digital interventions was investigated using the theory coding scheme (TCS). Reported theory use was analyzed by frequency counts and descriptive statistics. Associations were analyzed with meta-regression models. Of 41 trials involving 42 comparisons, half did not mention theory (50% [21/42]), and only 38% (16/42) used theory to select or develop the intervention techniques. Significant heterogeneity existed between studies in the effect of interventions on alcohol reduction (I 2 =77.6%, Ptheory use and intervention effectiveness in unadjusted models, though the meta-regression was underpowered to detect modest associations. Digital interventions offer a unique opportunity to refine and develop new dynamic, temporally sensitive theories, yet none of the studies reported refining or developing theory. Clearer selection, application, and reporting of theory use is needed to accurately assess how useful theory is in this field and to advance the field of behavior change theories. ©Claire Garnett, David Crane, Jamie Brown, Eileen Kaner, Fiona Beyer, Colin Muirhead, Matthew Hickman, James Redmore, Frank de Vocht, Emma Beard, Susan Michie. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 28.02.2018.

  13. Mixed-effects regression models in linguistics

    CERN Document Server

    Heylen, Kris; Geeraerts, Dirk

    2018-01-01

    When data consist of grouped observations or clusters, and there is a risk that measurements within the same group are not independent, group-specific random effects can be added to a regression model in order to account for such within-group associations. Regression models that contain such group-specific random effects are called mixed-effects regression models, or simply mixed models. Mixed models are a versatile tool that can handle both balanced and unbalanced datasets and that can also be applied when several layers of grouping are present in the data; these layers can either be nested or crossed.  In linguistics, as in many other fields, the use of mixed models has gained ground rapidly over the last decade. This methodological evolution enables us to build more sophisticated and arguably more realistic models, but, due to its technical complexity, also introduces new challenges. This volume brings together a number of promising new evolutions in the use of mixed models in linguistics, but also addres...

  14. Examining the association between suicidal behaviors and referral for mental health services among children involved in the child welfare system in Ontario, Canada.

    Science.gov (United States)

    Baiden, Philip; Fallon, Barbara

    2018-05-01

    Although various studies have investigated factors associated with mental health service utilization, few studies have examined factors associated with referral for mental health services among maltreated children. The objective of this study was to examine the association between suicidal thoughts and self-harming behavior and referral for mental health services among children involved in the Child Welfare System in Ontario, Canada. Data for this study were obtained from the Ontario Incidence Study of Reported Child Abuse and Neglect 2013. An estimate 57,798 child maltreatment investigations was analyzed using binary logistic regression with referral for mental health service as the outcome variable. Of the 57,798 cases, 4709 (8.1%), were referred for mental health services. More than seven out of ten maltreated children who engaged in self-harming behavior and two out of three maltreated children who expressed suicidal thoughts were not referred for mental health services. In the multivariate logistic regression model, children who expressed suicidal thoughts had 2.39 times higher odds of being referred for mental health services compared to children with no suicidal thoughts (AOR = 2.39, 99% C.I. 2.05-2.77) and children who engaged in self-harming behavior had 1.44 times higher odds of being referred for mental health services compared to children who did not engage in self-harming behavior (AOR = 1.44, 99% C.I. 1.24-1.67), both after controlling for child demographic characteristics, maltreatment characteristics, and child functioning concerns. Given that referral is the initial step towards mental health service utilization, it is important that child welfare workers receive the necessary training so as to carefully assess and refer children in care who expressed suicidal thoughts or engaged in self-harming behavior for appropriate mental health services. The paper discusses the results and their implications for child welfare policy and practice

  15. Associations of financial stressors and physical intimate partner violence perpetration.

    Science.gov (United States)

    Schwab-Reese, Laura M; Peek-Asa, Corinne; Parker, Edith

    2016-12-01

    Contextual factors, such as exposure to stressors, may be antecedents to IPV perpetration. These contextual factors may be amenable to modification through intervention and prevention. However, few studies have examined specific contextual factors. To begin to address this gap, we examined the associations between financial stressors and three types of physical IPV perpetration. This analysis used data from Wave IV of The National Longitudinal Study of Adolescent to Adult Health. We used logistic regression to examine the associations of financial stressors and each type of IPV (minor, severe, causing injury), and multinomial logit regression to examine the associations of financial stressors and patterns of co-occurring types of IPV perpetration (only minor; only severe; minor and severe; minor, severe, and causing injury; compared with no perpetration). Fewer men perpetrated threats/minor physical IPV (6.7 %) or severe physical IPV (3.4 %) compared with women (11.4 % and 8.8 %, respectively). However, among physical IPV perpetrators, a higher percentage of men (32.0 %) than women (21.0 %) reported their partner was injured as a result of the IPV. In logistic regression models of each type of IPV perpetration, both the number of stressors experienced and several types of financial stressors were associated with perpetrating each type of IPV. Utilities nonpayment, housing nonpayment, food insecurity, and no phone service were associated with increased odds of perpetrating each form of IPV in adjusted analysis. Eviction was associated with perpetrating severe physical IPV but not threats/minor IPV or IPV causing injury. In multinomial logit regression comparing patterns of IPV perpetration to perpetrating no physical IPV, the relationships of financial stressors were less consistent. Food insecurity was associated with perpetrating only minor physical IPV. Comparatively, overall number of financial stressors and four types of financial stressors (utilities

  16. A gentle introduction to quantile regression for ecologists

    Science.gov (United States)

    Cade, B.S.; Noon, B.R.

    2003-01-01

    Quantile regression is a way to estimate the conditional quantiles of a response variable distribution in the linear model that provides a more complete view of possible causal relationships between variables in ecological processes. Typically, all the factors that affect ecological processes are not measured and included in the statistical models used to investigate relationships between variables associated with those processes. As a consequence, there may be a weak or no predictive relationship between the mean of the response variable (y) distribution and the measured predictive factors (X). Yet there may be stronger, useful predictive relationships with other parts of the response variable distribution. This primer relates quantile regression estimates to prediction intervals in parametric error distribution regression models (eg least squares), and discusses the ordering characteristics, interval nature, sampling variation, weighting, and interpretation of the estimates for homogeneous and heterogeneous regression models.

  17. Advanced statistics: linear regression, part II: multiple linear regression.

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

    The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

  18. Examining Associations between Narcissism, Behavior Problems, and Anxiety in Non-Referred Adolescents

    Science.gov (United States)

    Lau, Katherine S. L.; Marsee, Monica A.; Kunimatsu, Melissa M.; Fassnacht, Gregory M.

    2011-01-01

    The present study examined associations between narcissism (total, adaptive, and maladaptive), self-esteem, and externalizing and internalizing problems in 157 non-referred adolescents (aged 14 to 18). Consistent with previous research, narcissism was positively associated with self-reported delinquency, overt aggression, and relational…

  19. Boosted beta regression.

    Directory of Open Access Journals (Sweden)

    Matthias Schmid

    Full Text Available Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1. Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures.

  20. Time series regression model for infectious disease and weather.

    Science.gov (United States)

    Imai, Chisato; Armstrong, Ben; Chalabi, Zaid; Mangtani, Punam; Hashizume, Masahiro

    2015-10-01

    Time series regression has been developed and long used to evaluate the short-term associations of air pollution and weather with mortality or morbidity of non-infectious diseases. The application of the regression approaches from this tradition to infectious diseases, however, is less well explored and raises some new issues. We discuss and present potential solutions for five issues often arising in such analyses: changes in immune population, strong autocorrelations, a wide range of plausible lag structures and association patterns, seasonality adjustments, and large overdispersion. The potential approaches are illustrated with datasets of cholera cases and rainfall from Bangladesh and influenza and temperature in Tokyo. Though this article focuses on the application of the traditional time series regression to infectious diseases and weather factors, we also briefly introduce alternative approaches, including mathematical modeling, wavelet analysis, and autoregressive integrated moving average (ARIMA) models. Modifications proposed to standard time series regression practice include using sums of past cases as proxies for the immune population, and using the logarithm of lagged disease counts to control autocorrelation due to true contagion, both of which are motivated from "susceptible-infectious-recovered" (SIR) models. The complexity of lag structures and association patterns can often be informed by biological mechanisms and explored by using distributed lag non-linear models. For overdispersed models, alternative distribution models such as quasi-Poisson and negative binomial should be considered. Time series regression can be used to investigate dependence of infectious diseases on weather, but may need modifying to allow for features specific to this context. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  1. Logistic regression analysis of factors associated with avascular necrosis of the femoral head following femoral neck fractures in middle-aged and elderly patients.

    Science.gov (United States)

    Ai, Zi-Sheng; Gao, You-Shui; Sun, Yuan; Liu, Yue; Zhang, Chang-Qing; Jiang, Cheng-Hua

    2013-03-01

    Risk factors for femoral neck fracture-induced avascular necrosis of the femoral head have not been elucidated clearly in middle-aged and elderly patients. Moreover, the high incidence of screw removal in China and its effect on the fate of the involved femoral head require statistical methods to reflect their intrinsic relationship. Ninety-nine patients older than 45 years with femoral neck fracture were treated by internal fixation between May 1999 and April 2004. Descriptive analysis, interaction analysis between associated factors, single factor logistic regression, multivariate logistic regression, and detailed interaction analysis were employed to explore potential relationships among associated factors. Avascular necrosis of the femoral head was found in 15 cases (15.2 %). Age × the status of implants (removal vs. maintenance) and gender × the timing of reduction were interactive according to two-factor interactive analysis. Age, the displacement of fractures, the quality of reduction, and the status of implants were found to be significant factors in single factor logistic regression analysis. Age, age × the status of implants, and the quality of reduction were found to be significant factors in multivariate logistic regression analysis. In fine interaction analysis after multivariate logistic regression analysis, implant removal was the most important risk factor for avascular necrosis in 56-to-85-year-old patients, with a risk ratio of 26.00 (95 % CI = 3.076-219.747). The middle-aged and elderly have less incidence of avascular necrosis of the femoral head following femoral neck fractures treated by cannulated screws. The removal of cannulated screws can induce a significantly high incidence of avascular necrosis of the femoral head in elderly patients, while a high-quality reduction is helpful to reduce avascular necrosis.

  2. Regression Analysis to Identify Factors Associated with Urinary Iodine Concentration at the Sub-National Level in India, Ghana, and Senegal

    Directory of Open Access Journals (Sweden)

    Jacky Knowles

    2018-04-01

    Full Text Available Single and multiple variable regression analyses were conducted using data from stratified, cluster sample design, iodine surveys in India, Ghana, and Senegal to identify factors associated with urinary iodine concentration (UIC among women of reproductive age (WRA at the national and sub-national level. Subjects were survey household respondents, typically WRA. For all three countries, UIC was significantly different (p < 0.05 by household salt iodine category. Other significant differences were by strata and by household vulnerability to poverty in India and Ghana. In multiple variable regression analysis, UIC was significantly associated with strata and household salt iodine category in India and Ghana (p < 0.001. Estimated UIC was 1.6 (95% confidence intervals (CI 1.3, 2.0 times higher (India and 1.4 (95% CI 1.2, 1.6 times higher (Ghana among WRA from households using adequately iodised salt than among WRA from households using non-iodised salt. Other significant associations with UIC were found in India, with having heard of iodine deficiency (1.2 times higher; CI 1.1, 1.3; p < 0.001 and having improved dietary diversity (1.1 times higher, CI 1.0, 1.2; p = 0.015; and in Ghana, with the level of tomato paste consumption the previous week (p = 0.029 (UIC for highest consumption level was 1.2 times lowest level; CI 1.1, 1.4. No significant associations were found in Senegal. Sub-national data on iodine status are required to assess equity of access to optimal iodine intake and to develop strategic responses as needed.

  3. Regression to Causality : Regression-style presentation influences causal attribution

    DEFF Research Database (Denmark)

    Bordacconi, Mats Joe; Larsen, Martin Vinæs

    2014-01-01

    of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... more likely. Our experiment drew on a sample of 235 university students from three different social science degree programs (political science, sociology and economics), all of whom had received substantial training in statistics. The subjects were asked to compare and evaluate the validity...

  4. Cultural Conceptions of Morality: Examining Laypeople's Associations of Moral Character

    Science.gov (United States)

    Vauclair, Christin-Melanie; Wilson, Marc; Fischer, Ronald

    2014-01-01

    Whether moral conceptions are universal or culture-specific is controversial in moral psychology. One option is to refrain from imposing theoretical constraints and to ask laypeople from different cultures how "they" conceptualize morality. Our article adopts this approach by examining laypeople's associations of moral character in…

  5. One-minute mental status examination for category fluency is more useful than mini-mental state examination to evaluate the reliability of insulin self-injection in elderly diabetic patients.

    Science.gov (United States)

    Yajima, Ken; Matsushita, Takaya; Sumitomo, Hidetaka; Sakurai, Hirofumi; Katayama, Takashi; Kanno, Kazuo; Sakai, Masashi; Shigeta, Masayuki; Shirabe, Shinichiro; Nakano, Tadasumi; Nishimura, Kazuhiro; Ueki, Akio; Kitaoka, Masafumi

    2014-05-04

    We investigated the factors associated with the reliability of insulin self-injection in elderly diabetic patients receiving insulin therapy. We enrolled diabetic patients aged ≥65 years and receiving insulin therapy, and assessed their cognitive function by the mini-mental state examination and 1-min mental status examination for category fluency. We also observed their technique of insulin self-injection, and evaluated whether or not patients were able to inject insulin by themselves according to nine defined details in terms of insulin self-injection. The predictive factors for the reliability of insulin self-injection were determined by univariate and multivariate logistic regression analysis. There were 278 participants (135 males, 143 females) enrolled in the present study. According to multivariate logistic regression analysis, only the 1-min mental status examination score was found to be a significant independent predictor of the reliability of insulin self-injection (odds ratio 0.75; 95% confidence interval 0.62-0.90; P = 0.002). The 1-min mental status examination for category fluency can be considered more useful than mini-mental state examination to evaluate the reliability of insulin self-injection in elderly diabetic patients receiving insulin therapy.

  6. Identifying Interacting Genetic Variations by Fish-Swarm Logic Regression

    Science.gov (United States)

    Yang, Aiyuan; Yan, Chunxia; Zhu, Feng; Zhao, Zhongmeng; Cao, Zhi

    2013-01-01

    Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR) is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR), which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds. PMID:23984382

  7. Identifying Interacting Genetic Variations by Fish-Swarm Logic Regression

    Directory of Open Access Journals (Sweden)

    Xuanping Zhang

    2013-01-01

    Full Text Available Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR, which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds.

  8. Association between Smoking and Periodontal Disease in Korean Adults: The Fifth Korea National Health and Nutrition Examination Survey (2010 and 2012).

    Science.gov (United States)

    Jang, Ah-Young; Lee, Jung-Kwon; Shin, Jin-Young; Lee, Hae-Young

    2016-03-01

    This study aimed to evaluate an association between smoking, smoking cessation, and periodontal disease in Korean adults. The data were collected from 8,336 participants, aged between 20 and 64 years, who participated in the fifth Korea National Health and Nutrition Examination (2010 and 2012). Smoking status was assessed using self-administered questionnaires. Periodontal disease was defined as a community periodontal index ≥3 points. Logistic regression analysis was used to evaluate an association between smoking, smoking cessation, and periodontal disease after adjusting for age, sex, education, monthly income, diabetes, obesity, alcohol intake, and frequency of tooth brushing. The risk of periodontal disease was higher among current smokers (odds ratio [OR], 1.49; 95% confidence interval [CI], 1.21-1.83) than never smokers. Among current smokers, the risk of periodontal disease was increased in smokers of ≥10 cigarettes/d, ≥20 years duration, and >10 pack-years compared with never smokers (Pperiodontal disease after 10 years since cessation declined to 0.56 (95% CI, 0.42-0.75) compared with current smokers and was indistinguishable statistically from never smokers. Periodontal disease is significantly associated with smoking status in Korean adults.

  9. Significance testing in ridge regression for genetic data

    Directory of Open Access Journals (Sweden)

    De Iorio Maria

    2011-09-01

    Full Text Available Abstract Background Technological developments have increased the feasibility of large scale genetic association studies. Densely typed genetic markers are obtained using SNP arrays, next-generation sequencing technologies and imputation. However, SNPs typed using these methods can be highly correlated due to linkage disequilibrium among them, and standard multiple regression techniques fail with these data sets due to their high dimensionality and correlation structure. There has been increasing interest in using penalised regression in the analysis of high dimensional data. Ridge regression is one such penalised regression technique which does not perform variable selection, instead estimating a regression coefficient for each predictor variable. It is therefore desirable to obtain an estimate of the significance of each ridge regression coefficient. Results We develop and evaluate a test of significance for ridge regression coefficients. Using simulation studies, we demonstrate that the performance of the test is comparable to that of a permutation test, with the advantage of a much-reduced computational cost. We introduce the p-value trace, a plot of the negative logarithm of the p-values of ridge regression coefficients with increasing shrinkage parameter, which enables the visualisation of the change in p-value of the regression coefficients with increasing penalisation. We apply the proposed method to a lung cancer case-control data set from EPIC, the European Prospective Investigation into Cancer and Nutrition. Conclusions The proposed test is a useful alternative to a permutation test for the estimation of the significance of ridge regression coefficients, at a much-reduced computational cost. The p-value trace is an informative graphical tool for evaluating the results of a test of significance of ridge regression coefficients as the shrinkage parameter increases, and the proposed test makes its production computationally feasible.

  10. The association between dietary patterns derived by reduced rank regression and depressive symptoms over time: the Invecchiare in Chianti (InCHIANTI) study

    NARCIS (Netherlands)

    Vermeulen, E.; Stronks, K.; Visser, M de; Brouwer, I.A.; Schene, A.H.; Mocking, R.J.T.; Colpo, M.; Bandinelli, S.; Ferrucci, L.; Nicolaou, M.

    2016-01-01

    This study aimed to identify dietary patterns using reduced rank regression (RRR) and to explore their associations with depressive symptoms over 9 years in the Invecchiare in Chianti study. At baseline, 1362 participants (55.4 % women) aged 18-102 years (mean age 68 (sd 15.5) years) were included

  11. Examining the association between participation in late-life leisure activities and cognitive function in community-dwelling elderly Chinese in Hong Kong.

    Science.gov (United States)

    Leung, Grace T Y; Fung, Ada W T; Tam, Cindy W C; Lui, Victor W C; Chiu, Helen F K; Chan, W M; Lam, Linda C W

    2010-02-01

    Growing evidence suggests that participation in late-life leisure activity may have beneficial effects on cognitive function. The objective of the study was to evaluate the association between leisure activity participation and cognitive function in an elderly population of community-dwelling Hong Kong Chinese. 512 participants were assessed in the follow-up study of a population-based community survey of the prevalence of cognitive impairment among Hong Kong Chinese aged 60 years and over. Leisure activities were classified into four categories (physical, intellectual, social and recreational). Information regarding leisure activity participation, cognitive function and other variables was collected. Multivariate linear regression analyses were performed to examine the association between leisure activity participation and cognitive function. A higher level of late-life leisure activity participation, particularly in intellectual activities, was significantly associated with better cognitive function in the elderly, as reflected by the results of the Cantonese Mini-mental State Examination (p = 0.007, 0.029 and 0.005), the Category Verbal Fluency Test (p = 0.027, 0.003 and 0.005) and digit backward span (p = 0.031, 0.002 and 0.009), as measured by the total frequency, total hours per week and total number of subtypes, respectively; the Chinese Alzheimer's Disease Assessment Scale-Cognitive Subscale (p = 0.045) and word list learning (p = 0.003), as measured by the total number of subtypes; and digit forward span (p = 0.007 and 0.015), as measured by the total hours per week and total number of subtypes, respectively. Late-life intellectual activity participation was associated with better cognitive function among community-dwelling Hong Kong elderly Chinese.

  12. A Two-Stage Penalized Logistic Regression Approach to Case-Control Genome-Wide Association Studies

    Directory of Open Access Journals (Sweden)

    Jingyuan Zhao

    2012-01-01

    Full Text Available We propose a two-stage penalized logistic regression approach to case-control genome-wide association studies. This approach consists of a screening stage and a selection stage. In the screening stage, main-effect and interaction-effect features are screened by using L1-penalized logistic like-lihoods. In the selection stage, the retained features are ranked by the logistic likelihood with the smoothly clipped absolute deviation (SCAD penalty (Fan and Li, 2001 and Jeffrey’s Prior penalty (Firth, 1993, a sequence of nested candidate models are formed, and the models are assessed by a family of extended Bayesian information criteria (J. Chen and Z. Chen, 2008. The proposed approach is applied to the analysis of the prostate cancer data of the Cancer Genetic Markers of Susceptibility (CGEMS project in the National Cancer Institute, USA. Simulation studies are carried out to compare the approach with the pair-wise multiple testing approach (Marchini et al. 2005 and the LASSO-patternsearch algorithm (Shi et al. 2007.

  13. Background stratified Poisson regression analysis of cohort data.

    Science.gov (United States)

    Richardson, David B; Langholz, Bryan

    2012-03-01

    Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models.

  14. Analysis of extreme drinking in patients with alcohol dependence using Pareto regression.

    Science.gov (United States)

    Das, Sourish; Harel, Ofer; Dey, Dipak K; Covault, Jonathan; Kranzler, Henry R

    2010-05-20

    We developed a novel Pareto regression model with an unknown shape parameter to analyze extreme drinking in patients with Alcohol Dependence (AD). We used the generalized linear model (GLM) framework and the log-link to include the covariate information through the scale parameter of the generalized Pareto distribution. We proposed a Bayesian method based on Ridge prior and Zellner's g-prior for the regression coefficients. Simulation study indicated that the proposed Bayesian method performs better than the existing likelihood-based inference for the Pareto regression.We examined two issues of importance in the study of AD. First, we tested whether a single nucleotide polymorphism within GABRA2 gene, which encodes a subunit of the GABA(A) receptor, and that has been associated with AD, influences 'extreme' alcohol intake and second, the efficacy of three psychotherapies for alcoholism in treating extreme drinking behavior. We found an association between extreme drinking behavior and GABRA2. We also found that, at baseline, men with a high-risk GABRA2 allele had a significantly higher probability of extreme drinking than men with no high-risk allele. However, men with a high-risk allele responded to the therapy better than those with two copies of the low-risk allele. Women with high-risk alleles also responded to the therapy better than those with two copies of the low-risk allele, while women who received the cognitive behavioral therapy had better outcomes than those receiving either of the other two therapies. Among men, motivational enhancement therapy was the best for the treatment of the extreme drinking behavior. Copyright 2010 John Wiley & Sons, Ltd.

  15. Predictive factors of esophageal stenosis associated with tumor regression in radiation therapy for locally advanced esophageal cancer

    International Nuclear Information System (INIS)

    Atsumi, Kazushige; Shioyama, Yoshiyuki; Nakamura, Katsumasa

    2010-01-01

    The purpose of this retrospective study was to clarify the predictive factors correlated with esophageal stenosis within three months after radiation therapy for locally advanced esophageal cancer. We enrolled 47 patients with advanced esophageal cancer with T2-4 and stage II-III who were treated with definitive radiation therapy and achieving complete response of primary lesion at Kyushu University Hospital between January 1998 and December 2005. Esophagography was performed for all patients before treatment and within three months after completion of the radiation therapy, the esophageal stenotic ratio was evaluated. The stenotic ratio was used to define four levels of stenosis: stenosis level 1, stenotic ratio of 0-25%; 2, 25-50%; 3, 50-75%; 4, 75-100%. We then estimated the correlation between the esophageal stenosis level after radiation therapy and each of numerous factors. The numbers and total percentages of patients at each stenosis level were as follows: level 1: n=14 (30%); level 2: 8 (17%); level 3: 14 (30%); and level 4: 11 (23%). Esophageal stenosis in the case of full circumference involvement tended to be more severe and more frequent. Increases in wall thickness tended to be associated with increases in esophageal stenosis severity and frequency. The extent of involved circumference and wall thickness of tumor region were significantly correlated with esophageal stenosis associated with tumor regression in radiation therapy (p=0.0006, p=0.005). For predicting the possibility of esophageal stenosis with tumor regression within three months in radiation therapy, the extent of involved circumference and esophageal wall thickness of the tumor region may be useful. (author)

  16. The association between dietary patterns derived by reduced rank regression and depressive symptoms over time : the Invecchiare in Chianti (InCHIANTI) study

    NARCIS (Netherlands)

    Vermeulen, Esther; Stronks, Karien; Visser, Marjolein; Brouwer, Ingeborg A; Schene, Aart H; Mocking, Roel J T; Colpo, Marco; Bandinelli, Stefania; Ferrucci, Luigi; Nicolaou, Mary

    This study aimed to identify dietary patterns using reduced rank regression (RRR) and to explore their associations with depressive symptoms over 9 years in the Invecchiare in Chianti study. At baseline, 1362 participants (55·4 % women) aged 18-102 years (mean age 68 (sd 15·5) years) were included

  17. Superquantile Regression: Theory, Algorithms, and Applications

    Science.gov (United States)

    2014-12-01

    Highway, Suite 1204, Arlington, Va 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188) Washington DC 20503. 1...Navy submariners, reliability engineering, uncertainty quantification, and financial risk management . Superquantile, superquantile regression...Royset Carlos F. Borges Associate Professor of Operations Research Dissertation Supervisor Professor of Applied Mathematics Lyn R. Whitaker Javier

  18. Association between Chronic Laryngitis and Particulate Matter Based on the Korea National Health and Nutrition Examination Survey 2008-2012.

    Directory of Open Access Journals (Sweden)

    Young-Hoon Joo

    Full Text Available Chronic laryngitis (CL has been described as chronic inflammation of the larynx. CL have various causes such as long-term smoking, acid reflux, voice overuse, bronchitis, allergies, pneumonia, excessive exposure to toxic chemicals and complications from the flu or a chronic cold. However, the prevalence of CL and role of air pollution in the etiology is uncertain.The aim of this study was to investigate the relationship between CL and particulate matter with aerodynamic diameter less than 10 μm (PM10 in South Korea using data from the Korea National Health and Nutrition Examination Surveys (KNHANES during 2008-2012.KNHANES is a cross-sectional survey of the civilian, non-institutionalized population of South Korea (n = 21,116. A field survey team that included an otolaryngologist moved with a mobile examination unit and performed interviews and physical examinations. The mean annual concentrations of ambient PM10, SO2, O3, NO2, and CO levels in Korea were determined from monitoring station data. Multiple logistic regression was used to examine the relationship of air pollution to CL.Among the population ≥ 19 years of age, the weighted prevalence of CL was 3.37 ± 0.30% (95% confidence interval, 2.79-3.95%. CL was more prevalent in men, current smokers, and those with lower household income and prevalence increased with age. A significant decrease over time was observed in the prevalence of CL (P for trend = 0.0049 and the annual average concentrations of PM10 (P for trend < 0.0001 from 2008 to 2012. In a multivariate model, the factors associated with CL included PM10 (odds ratio [OR], 1.378, p = 0.0457, age (OR, 1.020, p<0.0001, sex (OR, 0.734, p = 0.0179, and smoking status (OR, 1.438, p = 0.0054.Elevated PM10 exposures could be associated with increased risk of CL in South Koreans. Further epidemiological and experimental studies are necessary to clarify the impact of chronic PM10 exposure on CL.

  19. Personality disorders, violence, and antisocial behavior: a systematic review and meta-regression analysis.

    Science.gov (United States)

    Yu, Rongqin; Geddes, John R; Fazel, Seena

    2012-10-01

    The risk of antisocial outcomes in individuals with personality disorder (PD) remains uncertain. The authors synthesize the current evidence on the risks of antisocial behavior, violence, and repeat offending in PD, and they explore sources of heterogeneity in risk estimates through a systematic review and meta-regression analysis of observational studies comparing antisocial outcomes in personality disordered individuals with controls groups. Fourteen studies examined risk of antisocial and violent behavior in 10,007 individuals with PD, compared with over 12 million general population controls. There was a substantially increased risk of violent outcomes in studies with all PDs (random-effects pooled odds ratio [OR] = 3.0, 95% CI = 2.6 to 3.5). Meta-regression revealed that antisocial PD and gender were associated with higher risks (p = .01 and .07, respectively). The odds of all antisocial outcomes were also elevated. Twenty-five studies reported the risk of repeat offending in PD compared with other offenders. The risk of a repeat offense was also increased (fixed-effects pooled OR = 2.4, 95% CI = 2.2 to 2.7) in offenders with PD. The authors conclude that although PD is associated with antisocial outcomes and repeat offending, the risk appears to differ by PD category, gender, and whether individuals are offenders or not.

  20. Association Between Chewing Difficulty and Symptoms of Depression in Adults: Results from the Korea National Health and Nutrition Examination Survey.

    Science.gov (United States)

    Shin, Hye-Sun; Ahn, Yong-Soon; Lim, Do-Seon

    2016-12-01

    To assess the association between chewing difficulty and symptoms of depression in a representative sample of the Korean population. Cross-sectional. Korea National Health and Nutrition Examination Survey (KNHANES). KNHANES participants (N = 5,158). Chewing difficulty was assessed according to the self-reported presence of chewing problems using a structured questionnaire. Symptoms of depression were defined as having feelings of sadness or depression consecutively over 2 weeks during the last 12 months. Multivariable logistic regression analysis was used to determine the adjusted odds ratios (AORs) and 95% confidence intervals (CIs) of the associations between chewing difficulty and symptoms of depression, adjusted for age; sex; monthly household income; education; number of teeth; number of decayed, missing, or filled permanent teeth; periodontitis; state of dentition; tooth brushing frequency; regular dental visits; smoking status; alcohol consumption; hypertension; diabetes mellitus; and obesity. The interaction effects between chewing difficulty and confounders were evaluated, and age- and sex-stratified analyses were performed. There was a significant positive association between chewing difficulty and symptoms of depression in the fully adjusted model (AOR = 1.86, 95% CI = 1.48-2.33). The strength of the association was highest in men aged 60 and older (AOR = 3.28, 95% CI = 1.54-7.00). Chewing difficulty was independently associated with symptoms of depression in a representative sample of Korean adults. © 2016, Copyright the Authors Journal compilation © 2016, The American Geriatrics Society.

  1. Sarcopenia exacerbates obesity-associated insulin resistance and dysglycemia: findings from the National Health and Nutrition Examination Survey III.

    Directory of Open Access Journals (Sweden)

    Preethi Srikanthan

    2010-05-01

    Full Text Available Sarcopenia often co-exists with obesity, and may have additive effects on insulin resistance. Sarcopenic obese individuals could be at increased risk for type 2 diabetes. We performed a study to determine whether sarcopenia is associated with impairment in insulin sensitivity and glucose homeostasis in obese and non-obese individuals.We performed a cross-sectional analysis of National Health and Nutrition Examination Survey III data utilizing subjects of 20 years or older, non-pregnant (N = 14,528. Sarcopenia was identified from bioelectrical impedance measurement of muscle mass. Obesity was identified from body mass index. Outcomes were homeostasis model assessment of insulin resistance (HOMA IR, glycosylated hemoglobin level (HbA1C, and prevalence of pre-diabetes (6.0≤ HbA1C<6.5 and not on medication and type 2 diabetes. Covariates in multiple regression were age, educational level, ethnicity and sex.Sarcopenia was associated with insulin resistance in non-obese (HOMA IR ratio 1.39, 95% confidence interval (CI 1.26 to 1.52 and obese individuals (HOMA-IR ratio 1.16, 95% CI 1.12 to 1.18. Sarcopenia was associated with dysglycemia in obese individuals (HbA1C ratio 1.021, 95% CI 1.011 to 1.043 but not in non-obese individuals. Associations were stronger in those under 60 years of age. We acknowledge that the cross-sectional study design limits our ability to draw causal inferences.Sarcopenia, independent of obesity, is associated with adverse glucose metabolism, and the association is strongest in individuals under 60 years of age, which suggests that low muscle mass may be an early predictor of diabetes susceptibility. Given the increasing prevalence of obesity, further research is urgently needed to develop interventions to prevent sarcopenic obesity and its metabolic consequences.

  2. Multitask Quantile Regression under the Transnormal Model.

    Science.gov (United States)

    Fan, Jianqing; Xue, Lingzhou; Zou, Hui

    2016-01-01

    We consider estimating multi-task quantile regression under the transnormal model, with focus on high-dimensional setting. We derive a surprisingly simple closed-form solution through rank-based covariance regularization. In particular, we propose the rank-based ℓ 1 penalization with positive definite constraints for estimating sparse covariance matrices, and the rank-based banded Cholesky decomposition regularization for estimating banded precision matrices. By taking advantage of alternating direction method of multipliers, nearest correlation matrix projection is introduced that inherits sampling properties of the unprojected one. Our work combines strengths of quantile regression and rank-based covariance regularization to simultaneously deal with nonlinearity and nonnormality for high-dimensional regression. Furthermore, the proposed method strikes a good balance between robustness and efficiency, achieves the "oracle"-like convergence rate, and provides the provable prediction interval under the high-dimensional setting. The finite-sample performance of the proposed method is also examined. The performance of our proposed rank-based method is demonstrated in a real application to analyze the protein mass spectroscopy data.

  3. Relation of whole blood carboxyhemoglobin concentration to ambient carbon monoxide exposure estimated using regression.

    Science.gov (United States)

    Rudra, Carole B; Williams, Michelle A; Sheppard, Lianne; Koenig, Jane Q; Schiff, Melissa A; Frederick, Ihunnaya O; Dills, Russell

    2010-04-15

    Exposure to carbon monoxide (CO) and other ambient air pollutants is associated with adverse pregnancy outcomes. While there are several methods of estimating CO exposure, few have been evaluated against exposure biomarkers. The authors examined the relation between estimated CO exposure and blood carboxyhemoglobin concentration in 708 pregnant western Washington State women (1996-2004). Carboxyhemoglobin was measured in whole blood drawn around 13 weeks' gestation. CO exposure during the month of blood draw was estimated using a regression model containing predictor terms for year, month, street and population densities, and distance to the nearest major road. Year and month were the strongest predictors. Carboxyhemoglobin level was correlated with estimated CO exposure (rho = 0.22, 95% confidence interval (CI): 0.15, 0.29). After adjustment for covariates, each 10% increase in estimated exposure was associated with a 1.12% increase in median carboxyhemoglobin level (95% CI: 0.54, 1.69). This association remained after exclusion of 286 women who reported smoking or being exposed to secondhand smoke (rho = 0.24). In this subgroup, the median carboxyhemoglobin concentration increased 1.29% (95% CI: 0.67, 1.91) for each 10% increase in CO exposure. Monthly estimated CO exposure was moderately correlated with an exposure biomarker. These results support the validity of this regression model for estimating ambient CO exposures in this population and geographic setting.

  4. Dental Care Utilization for Examination and Regional Deprivation

    Science.gov (United States)

    Kim, Cheol-Sin; Han, Sun-Young; Lee, Seung Eun; Kang, Jeong-Hee; Kim, Chul-Woung

    2015-01-01

    Objectives: Receiving proper dental care plays a significant role in maintaining good oral health. We investigated the relationship between regional deprivation and dental care utilization. Methods: Multilevel logistic regression was used to identify the relationship between the regional deprivation level and dental care utilization purpose, adjusting for individual-level variables, in adults aged 19+ in the 2008 Korean Community Health Survey (n=220 258). Results: Among Korean adults, 12.8% used dental care to undergo examination and 21.0% visited a dentist for other reasons. In the final model, regional deprivation level was associated with significant variations in dental care utilization for examination (pdental care utilization for other reasons in the final model. Conclusions: This study’s findings suggest that policy interventions should be considered to reduce regional variations in rates of dental care utilization for examination. PMID:26265665

  5. Regression of the increased common carotid artery-intima media thickness in subclinical hypothyroidism after thyroid hormone replacement.

    Science.gov (United States)

    Kim, Soo-Kyung; Kim, Se-Hwa; Park, Kyung-Sun; Park, Seok-Won; Cho, Yong-Wook

    2009-01-01

    The association between subclinical hypothyroidism and cardiovascular disease and the beneficial effect of levothyroxine replacement in subclinical hypothyroidism are still under debate. The present study was designed to determine whether subclinical hypothyroidism is associated with an increase in the intima-media thickness of the common carotid artery (C-IMT) and whether thyroid hormone replacement can reverse this change in the C-IMT. Patients with newly-diagnosed subclinical (n=36) and overt (n=40) hypothyroidism and healthy euthyroid individuals (n=32) participated in this study. All the patients were examined for clinical characteristics, and the serum lipid levels and the C-IMT were measured. Patients with subclinical hypothyroidism had a C-IMT measurement after 18 months of levothyroxine replacement. There were meaningful differences in total cholesterol and LDL-cholesterol levels between patients with subclinical hypothyroidism and euthyroidism. The subjects with subclinical and overt hypothyroidism had a greater C-IMT compared with euthyroid controls (0.66+/- 0.10 and 0.70+/- 0.11 vs. 0.57+/- 0.08 mm, respectively; P replacement significantly decreased the C-IMT (0.67+/- 0.11 to 0.60+/- 0.10 mm; P = 0.021) and improved the lipid profile. Based on multiple regression analysis, the decrement in LDL-cholesterol was independently associated with the regression of the C-IMT. Subclinical hypothyroidism was closely related to an increased C-IMT. Thyroid hormone replacement resulted in regression of the increased C-IMT, which was attributed to the improvement in the lipid profile.

  6. Background stratified Poisson regression analysis of cohort data

    International Nuclear Information System (INIS)

    Richardson, David B.; Langholz, Bryan

    2012-01-01

    Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models. (orig.)

  7. Regression analysis with categorized regression calibrated exposure: some interesting findings

    Directory of Open Access Journals (Sweden)

    Hjartåker Anette

    2006-07-01

    Full Text Available Abstract Background Regression calibration as a method for handling measurement error is becoming increasingly well-known and used in epidemiologic research. However, the standard version of the method is not appropriate for exposure analyzed on a categorical (e.g. quintile scale, an approach commonly used in epidemiologic studies. A tempting solution could then be to use the predicted continuous exposure obtained through the regression calibration method and treat it as an approximation to the true exposure, that is, include the categorized calibrated exposure in the main regression analysis. Methods We use semi-analytical calculations and simulations to evaluate the performance of the proposed approach compared to the naive approach of not correcting for measurement error, in situations where analyses are performed on quintile scale and when incorporating the original scale into the categorical variables, respectively. We also present analyses of real data, containing measures of folate intake and depression, from the Norwegian Women and Cancer study (NOWAC. Results In cases where extra information is available through replicated measurements and not validation data, regression calibration does not maintain important qualities of the true exposure distribution, thus estimates of variance and percentiles can be severely biased. We show that the outlined approach maintains much, in some cases all, of the misclassification found in the observed exposure. For that reason, regression analysis with the corrected variable included on a categorical scale is still biased. In some cases the corrected estimates are analytically equal to those obtained by the naive approach. Regression calibration is however vastly superior to the naive method when applying the medians of each category in the analysis. Conclusion Regression calibration in its most well-known form is not appropriate for measurement error correction when the exposure is analyzed on a

  8. Performance on the adult rheumatology in-training examination and relationship to outcomes on the rheumatology certification examination.

    Science.gov (United States)

    Lohr, Kristine M; Clauser, Amanda; Hess, Brian J; Gelber, Allan C; Valeriano-Marcet, Joanne; Lipner, Rebecca S; Haist, Steven A; Hawley, Janine L; Zirkle, Sarah; Bolster, Marcy B

    2015-11-01

    The American College of Rheumatology (ACR) Adult Rheumatology In-Training Examination (ITE) is a feedback tool designed to identify strengths and weaknesses in the content knowledge of individual fellows-in-training and the training program curricula. We determined whether scores on the ACR ITE, as well as scores on other major standardized medical examinations and competency-based ratings, could be used to predict performance on the American Board of Internal Medicine (ABIM) Rheumatology Certification Examination. Between 2008 and 2012, 629 second-year fellows took the ACR ITE. Bivariate correlation analyses of assessment scores and multiple linear regression analyses were used to determine whether ABIM Rheumatology Certification Examination scores could be predicted on the basis of ACR ITE scores, United States Medical Licensing Examination scores, ABIM Internal Medicine Certification Examination scores, fellowship directors' ratings of overall clinical competency, and demographic variables. Logistic regression was used to evaluate whether these assessments were predictive of a passing outcome on the Rheumatology Certification Examination. In the initial linear model, the strongest predictors of the Rheumatology Certification Examination score were the second-year fellows' ACR ITE scores (β = 0.438) and ABIM Internal Medicine Certification Examination scores (β = 0.273). Using a stepwise model, the strongest predictors of higher scores on the Rheumatology Certification Examination were second-year fellows' ACR ITE scores (β = 0.449) and ABIM Internal Medicine Certification Examination scores (β = 0.276). Based on the findings of logistic regression analysis, ACR ITE performance was predictive of a pass/fail outcome on the Rheumatology Certification Examination (odds ratio 1.016 [95% confidence interval 1.011-1.021]). The predictive value of the ACR ITE score with regard to predicting performance on the Rheumatology Certification Examination

  9. How Can Comparison Groups Strengthen Regression Discontinuity Designs?

    Science.gov (United States)

    Wing, Coady; Cook, Thomas D.

    2011-01-01

    In this paper, the authors examine some of the ways that different types of non-equivalent comparison groups can be used to strengthen causal inferences based on regression discontinuity design (RDD). First, they consider a design that incorporates pre-test data on assignment scores and outcomes that were collected either before the treatment…

  10. Impact of Partial-Mouth Periodontal Examination Protocols on the Association Between Gingival Bleeding and Oral Health-Related Quality of Life in Adolescents.

    Science.gov (United States)

    Ediani Machado, Michely; Tomazoni, Fernanda; Ruffo Ortiz, Fernanda; Ardenghi, Thiago Machado; Zanatta, Fabricio Batistin

    2017-07-01

    It is not clear how using partial-mouth periodontal examination (PMPE) protocols affects estimates of the association between gingival bleeding (GB) and oral health-related quality of life (OHRQoL). The aim of the present study is to assess impact of different PMPEs on the association between GB and OHRQoL in 12-year-old adolescents. A total of 1,134 adolescents were evaluated for clinical and subjective variables. GB was determined by full-mouth examination (FME) of six sites (disto-buccal [DB], mid-buccal [B], mesio-buccal [MB], disto-lingual [DL], mid-lingual, and mesio-lingual [ML]) and different PMPEs were calculated using a 15% cut-off point: 1) full-mouth (MB-B-DB/MB-B-DL); 2) two diagonal quadrants (six sites/MB-B-DB/MB-B-DL); 3) two randomly selected half-mouth quadrants (six sites/MB-B-DB/ MB-B-DL/MB-DB-ML-DL); and 4) the community periodontal index. OHRQoL was assessed using the Child Perceptions Questionnaire (CPQ 11-14 ). Adjusted negative binomial regression models were used to calculate the rate ratio of CPQ 11-14 scores for each PMPE. Adolescents with GB showed significantly poorer OHRQoL than their counterparts when FME was used. In contrast, more than half of PMPE protocols did not detect significant associations between GB and CPQ 11-14 scores in the adjusted analysis. Using PMPE to assess GB in adolescents significantly affects associations with OHRQoL outcomes, depending on the protocol used. PMPEs that evaluated MB-B-DL sites of randomly selected half-mouth quadrants (1 or 2 and 3 or 4) achieved results closer to those obtained with FME.

  11. Model selection in kernel ridge regression

    DEFF Research Database (Denmark)

    Exterkate, Peter

    2013-01-01

    Kernel ridge regression is a technique to perform ridge regression with a potentially infinite number of nonlinear transformations of the independent variables as regressors. This method is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts....... The influence of the choice of kernel and the setting of tuning parameters on forecast accuracy is investigated. Several popular kernels are reviewed, including polynomial kernels, the Gaussian kernel, and the Sinc kernel. The latter two kernels are interpreted in terms of their smoothing properties......, and the tuning parameters associated to all these kernels are related to smoothness measures of the prediction function and to the signal-to-noise ratio. Based on these interpretations, guidelines are provided for selecting the tuning parameters from small grids using cross-validation. A Monte Carlo study...

  12. Modeling Group Differences in OLS and Orthogonal Regression: Implications for Differential Validity Studies

    Science.gov (United States)

    Kane, Michael T.; Mroch, Andrew A.

    2010-01-01

    In evaluating the relationship between two measures across different groups (i.e., in evaluating "differential validity") it is necessary to examine differences in correlation coefficients and in regression lines. Ordinary least squares (OLS) regression is the standard method for fitting lines to data, but its criterion for optimal fit…

  13. Association of Stressful Life Events with Psychological Problems: A Large-Scale Community-Based Study Using Grouped Outcomes Latent Factor Regression with Latent Predictors

    Directory of Open Access Journals (Sweden)

    Akbar Hassanzadeh

    2017-01-01

    Full Text Available Objective. The current study is aimed at investigating the association between stressful life events and psychological problems in a large sample of Iranian adults. Method. In a cross-sectional large-scale community-based study, 4763 Iranian adults, living in Isfahan, Iran, were investigated. Grouped outcomes latent factor regression on latent predictors was used for modeling the association of psychological problems (depression, anxiety, and psychological distress, measured by Hospital Anxiety and Depression Scale (HADS and General Health Questionnaire (GHQ-12, as the grouped outcomes, and stressful life events, measured by a self-administered stressful life events (SLEs questionnaire, as the latent predictors. Results. The results showed that the personal stressors domain has significant positive association with psychological distress (β=0.19, anxiety (β=0.25, depression (β=0.15, and their collective profile score (β=0.20, with greater associations in females (β=0.28 than in males (β=0.13 (all P<0.001. In addition, in the adjusted models, the regression coefficients for the association of social stressors domain and psychological problems profile score were 0.37, 0.35, and 0.46 in total sample, males, and females, respectively (P<0.001. Conclusion. Results of our study indicated that different stressors, particularly those socioeconomic related, have an effective impact on psychological problems. It is important to consider the social and cultural background of a population for managing the stressors as an effective approach for preventing and reducing the destructive burden of psychological problems.

  14. Association of Stressful Life Events with Psychological Problems: A Large-Scale Community-Based Study Using Grouped Outcomes Latent Factor Regression with Latent Predictors

    Science.gov (United States)

    Hassanzadeh, Akbar; Heidari, Zahra; Hassanzadeh Keshteli, Ammar; Afshar, Hamid

    2017-01-01

    Objective The current study is aimed at investigating the association between stressful life events and psychological problems in a large sample of Iranian adults. Method In a cross-sectional large-scale community-based study, 4763 Iranian adults, living in Isfahan, Iran, were investigated. Grouped outcomes latent factor regression on latent predictors was used for modeling the association of psychological problems (depression, anxiety, and psychological distress), measured by Hospital Anxiety and Depression Scale (HADS) and General Health Questionnaire (GHQ-12), as the grouped outcomes, and stressful life events, measured by a self-administered stressful life events (SLEs) questionnaire, as the latent predictors. Results The results showed that the personal stressors domain has significant positive association with psychological distress (β = 0.19), anxiety (β = 0.25), depression (β = 0.15), and their collective profile score (β = 0.20), with greater associations in females (β = 0.28) than in males (β = 0.13) (all P < 0.001). In addition, in the adjusted models, the regression coefficients for the association of social stressors domain and psychological problems profile score were 0.37, 0.35, and 0.46 in total sample, males, and females, respectively (P < 0.001). Conclusion Results of our study indicated that different stressors, particularly those socioeconomic related, have an effective impact on psychological problems. It is important to consider the social and cultural background of a population for managing the stressors as an effective approach for preventing and reducing the destructive burden of psychological problems. PMID:29312459

  15. Spontaneous regression of pulmonary bullae

    International Nuclear Information System (INIS)

    Satoh, H.; Ishikawa, H.; Ohtsuka, M.; Sekizawa, K.

    2002-01-01

    The natural history of pulmonary bullae is often characterized by gradual, progressive enlargement. Spontaneous regression of bullae is, however, very rare. We report a case in which complete resolution of pulmonary bullae in the left upper lung occurred spontaneously. The management of pulmonary bullae is occasionally made difficult because of gradual progressive enlargement associated with abnormal pulmonary function. Some patients have multiple bulla in both lungs and/or have a history of pulmonary emphysema. Others have a giant bulla without emphysematous change in the lungs. Our present case had treated lung cancer with no evidence of local recurrence. He had no emphysematous change in lung function test and had no complaints, although the high resolution CT scan shows evidence of underlying minimal changes of emphysema. Ortin and Gurney presented three cases of spontaneous reduction in size of bulla. Interestingly, one of them had a marked decrease in the size of a bulla in association with thickening of the wall of the bulla, which was observed in our patient. This case we describe is of interest, not only because of the rarity with which regression of pulmonary bulla has been reported in the literature, but also because of the spontaneous improvements in the radiological picture in the absence of overt infection or tumor. Copyright (2002) Blackwell Science Pty Ltd

  16. Longer sitting time and low physical activity are closely associated with chronic low back pain in population over 50 years of age: a cross-sectional study using the sixth korea national health and nutrition examination survey.

    Science.gov (United States)

    Park, Sang-Min; Kim, Ho-Joong; Jeong, Hyunseok; Kim, Hyoungmin; Chang, Bong-Soon; Lee, Choon-Ki; Yeom, Jin S

    2018-04-17

    There is increasing evidence supporting an association between sitting time and low back pain (LBP). However, the degree of the association between the total daily sitting time and LBP in the general population is poorly understood. (1) To analyze the association between the duration of sitting time and LBP, and (2) to examine this association according to the degree of physical activity in population over 50 years of age with a nationally representative sample of Korean adults. A cross-sectional study PATIENT SAMPLE: Data from version VI-2, 3 of the Korea National Health and Nutrition Examination Survey (KNHANES) performed in 2014 and 2015. Multiple logistic regression was performed to find the rates of association between chronic LBP, level of sitting time, and physical activity. Nationwide Health surveys and examinations were conducted in general Korean representative populations (n = 7,550 in 2014, n = 7,380 in 2015). Chronic LBP was defined as self-reported LBP lasting for more than 30 days during the past 3 months in a health survey. Sitting time and daily physical activity were evaluated using the long version of the international physical activity questionnaires (IPAQ). The duration of sitting time was divided into 2 categories according to the median value (7 hours), and further divided into 4 categories using quartiles. Physical activity was also divided into low and high physical activity according to duration of mid- to high-intensity activities. There were no sources of funding and no conflicts of interest associated with this study. On multiple logistic regression analysis, sitting time more than 7 hours/day was significantly associated with LBP (adjusted odds ratio, aOR: 1.33, pphysical activity, the duration of sitting time showed more positive association with LBP than that in all the participants and participants with high levels of physical activity. Longer duration of sitting time is a risk factor for LBP. Furthermore, long duration of sitting

  17. Sequences of Regressions Distinguish Nonmechanical from Mechanical Associations between Metabolic Factors, Body Composition, and Bone in Healthy Postmenopausal Women.

    Science.gov (United States)

    Solis-Trapala, Ivonne; Schoenmakers, Inez; Goldberg, Gail R; Prentice, Ann; Ward, Kate A

    2016-03-09

    There is increasing recognition of complex interrelations between the endocrine functions of bone and fat tissues or organs. The objective was to describe nonmechanical and mechanical links between metabolic factors, body composition, and bone with the use of graphical Markov models. Seventy postmenopausal women with a mean ± SD age of 62.3 ± 3.7 y and body mass index (in kg/m 2 ) of 24.9 ± 3.8 were recruited. Bone outcomes were peripheral quantitative computed tomography measures of the distal and diaphyseal tibia, cross-sectional area (CSA), volumetric bone mineral density (vBMD), and cortical CSA. Biomarkers of osteoblast and adipocyte function were plasma concentrations of leptin, adiponectin, osteocalcin, undercarboxylated osteocalcin (UCOC), and phylloquinone. Body composition measurements were lean and percent fat mass, which were derived with the use of a 4-compartment model. Sequences of Regressions, a subclass of graphical Markov models, were used to describe the direct (nonmechanical) and indirect (mechanical) interrelations between metabolic factors and bone by simultaneously modeling multiple bone outcomes and their relation with biomarker outcomes with lean mass, percent fat mass, and height as intermediate explanatory variables. The graphical Markov models showed both direct and indirect associations linking plasma leptin and adiponectin concentrations with CSA and vBMD. At the distal tibia, lean mass, height, and adiponectin-UCOC interaction were directly explanatory of CSA (R 2 = 0.45); at the diaphysis, lean mass, percent fat mass, leptin, osteocalcin, and age-adiponectin interaction were directly explanatory of CSA (R 2 = 0.49). The regression models exploring direct associations for vBMD were much weaker, with R 2 = 0.15 and 0.18 at the distal and diaphyseal sites, respectively. Lean mass and UCOC were associated, and the global Markov property of the graph indicated that this association was explained by osteocalcin. This study, to our

  18. Time course for tail regression during metamorphosis of the ascidian Ciona intestinalis.

    Science.gov (United States)

    Matsunobu, Shohei; Sasakura, Yasunori

    2015-09-01

    In most ascidians, the tadpole-like swimming larvae dramatically change their body-plans during metamorphosis and develop into sessile adults. The mechanisms of ascidian metamorphosis have been researched and debated for many years. Until now information on the detailed time course of the initiation and completion of each metamorphic event has not been described. One dramatic and important event in ascidian metamorphosis is tail regression, in which ascidian larvae lose their tails to adjust themselves to sessile life. In the present study, we measured the time associated with tail regression in the ascidian Ciona intestinalis. Larvae are thought to acquire competency for each metamorphic event in certain developmental periods. We show that the timing with which the competence for tail regression is acquired is determined by the time since hatching, and this timing is not affected by the timing of post-hatching events such as adhesion. Because larvae need to adhere to substrates with their papillae to induce tail regression, we measured the duration for which larvae need to remain adhered in order to initiate tail regression and the time needed for the tail to regress. Larvae acquire the ability to adhere to substrates before they acquire tail regression competence. We found that when larvae adhered before they acquired tail regression competence, they were able to remember the experience of adhesion until they acquired the ability to undergo tail regression. The time course of the events associated with tail regression provides a valuable reference, upon which the cellular and molecular mechanisms of ascidian metamorphosis can be elucidated. Copyright © 2015 Elsevier Inc. All rights reserved.

  19. Time-adaptive quantile regression

    DEFF Research Database (Denmark)

    Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg; Madsen, Henrik

    2008-01-01

    and an updating procedure are combined into a new algorithm for time-adaptive quantile regression, which generates new solutions on the basis of the old solution, leading to savings in computation time. The suggested algorithm is tested against a static quantile regression model on a data set with wind power......An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regression problem is given. The observations have been split to allow a direct use of the simplex algorithm. The simplex method...... production, where the models combine splines and quantile regression. The comparison indicates superior performance for the time-adaptive quantile regression in all the performance parameters considered....

  20. Analyzing hospitalization data: potential limitations of Poisson regression.

    Science.gov (United States)

    Weaver, Colin G; Ravani, Pietro; Oliver, Matthew J; Austin, Peter C; Quinn, Robert R

    2015-08-01

    Poisson regression is commonly used to analyze hospitalization data when outcomes are expressed as counts (e.g. number of days in hospital). However, data often violate the assumptions on which Poisson regression is based. More appropriate extensions of this model, while available, are rarely used. We compared hospitalization data between 206 patients treated with hemodialysis (HD) and 107 treated with peritoneal dialysis (PD) using Poisson regression and compared results from standard Poisson regression with those obtained using three other approaches for modeling count data: negative binomial (NB) regression, zero-inflated Poisson (ZIP) regression and zero-inflated negative binomial (ZINB) regression. We examined the appropriateness of each model and compared the results obtained with each approach. During a mean 1.9 years of follow-up, 183 of 313 patients (58%) were never hospitalized (indicating an excess of 'zeros'). The data also displayed overdispersion (variance greater than mean), violating another assumption of the Poisson model. Using four criteria, we determined that the NB and ZINB models performed best. According to these two models, patients treated with HD experienced similar hospitalization rates as those receiving PD {NB rate ratio (RR): 1.04 [bootstrapped 95% confidence interval (CI): 0.49-2.20]; ZINB summary RR: 1.21 (bootstrapped 95% CI 0.60-2.46)}. Poisson and ZIP models fit the data poorly and had much larger point estimates than the NB and ZINB models [Poisson RR: 1.93 (bootstrapped 95% CI 0.88-4.23); ZIP summary RR: 1.84 (bootstrapped 95% CI 0.88-3.84)]. We found substantially different results when modeling hospitalization data, depending on the approach used. Our results argue strongly for a sound model selection process and improved reporting around statistical methods used for modeling count data. © The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

  1. The number of subjects per variable required in linear regression analyses.

    Science.gov (United States)

    Austin, Peter C; Steyerberg, Ewout W

    2015-06-01

    To determine the number of independent variables that can be included in a linear regression model. We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression coefficients and standard errors, on the empirical coverage of estimated confidence intervals, and on the accuracy of the estimated R(2) of the fitted model. A minimum of approximately two SPV tended to result in estimation of regression coefficients with relative bias of less than 10%. Furthermore, with this minimum number of SPV, the standard errors of the regression coefficients were accurately estimated and estimated confidence intervals had approximately the advertised coverage rates. A much higher number of SPV were necessary to minimize bias in estimating the model R(2), although adjusted R(2) estimates behaved well. The bias in estimating the model R(2) statistic was inversely proportional to the magnitude of the proportion of variation explained by the population regression model. Linear regression models require only two SPV for adequate estimation of regression coefficients, standard errors, and confidence intervals. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  2. Potential pitfalls when denoising resting state fMRI data using nuisance regression.

    Science.gov (United States)

    Bright, Molly G; Tench, Christopher R; Murphy, Kevin

    2017-07-01

    In resting state fMRI, it is necessary to remove signal variance associated with noise sources, leaving cleaned fMRI time-series that more accurately reflect the underlying intrinsic brain fluctuations of interest. This is commonly achieved through nuisance regression, in which the fit is calculated of a noise model of head motion and physiological processes to the fMRI data in a General Linear Model, and the "cleaned" residuals of this fit are used in further analysis. We examine the statistical assumptions and requirements of the General Linear Model, and whether these are met during nuisance regression of resting state fMRI data. Using toy examples and real data we show how pre-whitening, temporal filtering and temporal shifting of regressors impact model fit. Based on our own observations, existing literature, and statistical theory, we make the following recommendations when employing nuisance regression: pre-whitening should be applied to achieve valid statistical inference of the noise model fit parameters; temporal filtering should be incorporated into the noise model to best account for changes in degrees of freedom; temporal shifting of regressors, although merited, should be achieved via optimisation and validation of a single temporal shift. We encourage all readers to make simple, practical changes to their fMRI denoising pipeline, and to regularly assess the appropriateness of the noise model used. By negotiating the potential pitfalls described in this paper, and by clearly reporting the details of nuisance regression in future manuscripts, we hope that the field will achieve more accurate and precise noise models for cleaning the resting state fMRI time-series. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  3. Defects of the central nervous system in Finland. IV. Associations with diagnostic x-ray examinations

    International Nuclear Information System (INIS)

    Granroth, G.

    1979-01-01

    Based on the Finnish Register of Congenital Malformations a search was undertaken to find possible associations between defects of the CNS and diagnostic x-ray examinations of the mother during pregnancy as well as pelvic x-ray examinations prior to pregnancy. Time-area-matched pregnancies and polydactylic children were used as controls. The risk of having a microcephalic child was increased for mothers with pelvic x-ray prior to pregnancy, but the number of discordant pairs was small. Of the examinations performed during pregnancy, fetal x-ray was significantly more common among mothers who delivered a CNS-defective child. No associations were observed for other kinds of examinations

  4. A Systematic Examination of the Association between Parental and Child Obesity across Countries.

    Science.gov (United States)

    Wang, Youfa; Min, Jungwon; Khuri, Jacob; Li, Miao

    2017-05-01

    Childhood obesity has become a global epidemic. Parents can have an important influence on their children's health behaviors and weight status. Many studies have examined the association between parental and childhood weight status. However, much heterogeneity between studies exists, and the parent-child (P-C) association in obesity has varied. The purpose of this systematic examination and meta-analysis was to examine the strength and variation of the P-C association in obesity and to identify factors (e.g., demographic characteristics and country's economic level) that may influence this association. PubMed was searched for relevant studies published between January 2000 and July 2015. Thirty-two studies from 21 countries met inclusion criteria; 27 reported ORs for the P-C obesity association and were included in a meta-analysis. The meta-analysis showed a strong P-C obesity association (pooled OR: 2.22; 95% CI: 2.09, 2.36), which varied by type of P-C pair (i.e., parents-child, father-child, and mother-child), child age, parent and child weight status, and the country's economic level. Stronger associations were shown in older children than in younger children (β ± SE: 0.02 ± 0.01), in both parents than in father only (β ± SE: 0.51 ± 0.11) or mother only (β ± SE: 0.38 ± 0.11), in parental obesity (β ± SE: 0.26 ± 0.10) and child obesity (β ± SE: 0.28 ± 0.12) than in parental and child overweight, and in high- than in middle-income countries (β ± SE: 0.23 ± 0.08). Thus, research from multiple countries shows significant P-C associations in weight status, but this association varies by child age, type of P-C pair, weight status, and the country's economic level. Results suggest that families and parents should be a key target for obesity intervention efforts. © 2017 American Society for Nutrition.

  5. The association of Socio-demographics characteristics and social support from family and community with depression: The National Health and Nutrition Examination Survey 2005-2006

    Directory of Open Access Journals (Sweden)

    Erfan Ayubi

    2012-01-01

    Full Text Available Aims & objectives: Protective effect of social support networks on depressive symptoms has been reported. The aim of this study was to examine the association between depressive symptoms and social support from family and community using data from the National Health and Nutrition Examination Survey (NHANES 2005-2006. Methodology: This is a cross-sectional population-based study of 10,348 people participating in the NHANES 2005-2006. Participants were interviewed on their level of social support and depressive symptoms. Logistic regression and analysis of variance was used to assess the effects of demographic variables and social support with depression. Results: Bing married and having a high education level is inversely related to depressive symptoms. Also social supports from family had protective effect on depression symptoms and impacts of each family member were different. It also became clear that family support in associated with social support had a protective effect on the emergence of depressive symptoms. In this effect, the interaction between spouse and professional support on depressive symptoms were more prominent. In addition to, interaction between children’s emotional support and religious practices was important. Conclusion: The result of this study adherent with the protective theory of social support on depression.

  6. The association of Socio-demographics characteristics and social support from family and community with depression: The National Health and Nutrition Examination Survey 2005-2006

    Directory of Open Access Journals (Sweden)

    Kavitha Dinesh

    2012-03-01

    Full Text Available Aims & objectives: Protective effect of social support networks on depressive symptoms has been reported. The aim of this study was to examine the association between depressive symptoms and social support from family and community using data from the National Health and Nutrition Examination Survey (NHANES 2005-2006. Methodology: This is a cross-sectional population-based study of 10,348 people participating in the NHANES 2005-2006. Participants were interviewed on their level of social support and depressive symptoms. Logistic regression and analysis of variance was used to assess the effects of demographic variables and social support with depression. Results: Bing married and having a high education level is inversely related to depressive symptoms. Also social supports from family had protective effect on depression symptoms and impacts of each family member were different. It also became clear that family support in associated with social support had a protective effect on the emergence of depressive symptoms. In this effect, the interaction between spouse and professional support on depressive symptoms were more prominent. In addition to, interaction between children’s emotional support and religious practices was important. Conclusion: The result of this study adherent with the protective theory of social support on depression.

  7. Factors Associated with Parental Intent not to Circumcise Daughters ...

    African Journals Online (AJOL)

    USER

    Daughters in Enugu State of Nigeria: An Application of the Theory ... dichotomized into two categories and logistic regression analysis was performed to examine the association between the ..... The impact of perceived cost and rewards.

  8. Dirichlet Component Regression and its Applications to Psychiatric Data.

    Science.gov (United States)

    Gueorguieva, Ralitza; Rosenheck, Robert; Zelterman, Daniel

    2008-08-15

    We describe a Dirichlet multivariable regression method useful for modeling data representing components as a percentage of a total. This model is motivated by the unmet need in psychiatry and other areas to simultaneously assess the effects of covariates on the relative contributions of different components of a measure. The model is illustrated using the Positive and Negative Syndrome Scale (PANSS) for assessment of schizophrenia symptoms which, like many other metrics in psychiatry, is composed of a sum of scores on several components, each in turn, made up of sums of evaluations on several questions. We simultaneously examine the effects of baseline socio-demographic and co-morbid correlates on all of the components of the total PANSS score of patients from a schizophrenia clinical trial and identify variables associated with increasing or decreasing relative contributions of each component. Several definitions of residuals are provided. Diagnostics include measures of overdispersion, Cook's distance, and a local jackknife influence metric.

  9. A land use regression model for ambient ultrafine particles in Montreal, Canada: A comparison of linear regression and a machine learning approach.

    Science.gov (United States)

    Weichenthal, Scott; Ryswyk, Keith Van; Goldstein, Alon; Bagg, Scott; Shekkarizfard, Maryam; Hatzopoulou, Marianne

    2016-04-01

    Existing evidence suggests that ambient ultrafine particles (UFPs) (regression model for UFPs in Montreal, Canada using mobile monitoring data collected from 414 road segments during the summer and winter months between 2011 and 2012. Two different approaches were examined for model development including standard multivariable linear regression and a machine learning approach (kernel-based regularized least squares (KRLS)) that learns the functional form of covariate impacts on ambient UFP concentrations from the data. The final models included parameters for population density, ambient temperature and wind speed, land use parameters (park space and open space), length of local roads and rail, and estimated annual average NOx emissions from traffic. The final multivariable linear regression model explained 62% of the spatial variation in ambient UFP concentrations whereas the KRLS model explained 79% of the variance. The KRLS model performed slightly better than the linear regression model when evaluated using an external dataset (R(2)=0.58 vs. 0.55) or a cross-validation procedure (R(2)=0.67 vs. 0.60). In general, our findings suggest that the KRLS approach may offer modest improvements in predictive performance compared to standard multivariable linear regression models used to estimate spatial variations in ambient UFPs. However, differences in predictive performance were not statistically significant when evaluated using the cross-validation procedure. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

  10. Vector regression introduced

    Directory of Open Access Journals (Sweden)

    Mok Tik

    2014-06-01

    Full Text Available This study formulates regression of vector data that will enable statistical analysis of various geodetic phenomena such as, polar motion, ocean currents, typhoon/hurricane tracking, crustal deformations, and precursory earthquake signals. The observed vector variable of an event (dependent vector variable is expressed as a function of a number of hypothesized phenomena realized also as vector variables (independent vector variables and/or scalar variables that are likely to impact the dependent vector variable. The proposed representation has the unique property of solving the coefficients of independent vector variables (explanatory variables also as vectors, hence it supersedes multivariate multiple regression models, in which the unknown coefficients are scalar quantities. For the solution, complex numbers are used to rep- resent vector information, and the method of least squares is deployed to estimate the vector model parameters after transforming the complex vector regression model into a real vector regression model through isomorphism. Various operational statistics for testing the predictive significance of the estimated vector parameter coefficients are also derived. A simple numerical example demonstrates the use of the proposed vector regression analysis in modeling typhoon paths.

  11. HIV-, HCV-, and co-infections and associated risk factors among drug users in southwestern China: a township-level ecological study incorporating spatial regression.

    Directory of Open Access Journals (Sweden)

    Yi-Biao Zhou

    Full Text Available BACKGROUND: The human immunodeficiency virus (HIV and hepatitis C virus (HCV are major public health problems. Many studies have been performed to investigate the association between demographic and behavioral factors and HIV or HCV infection. However, some of the results of these studies have been in conflict. METHODOLOGY/PRINCIPAL FINDINGS: The data of all entrants in the 11 national methadone clinics in the Yi Autonomous Prefecture from March 2004 to December 2012 were collected from the national database. Several spatial regression models were used to analyze specific community characteristics associated with the prevalence of HIV and HCV infection at the township level. The study enrolled 6,417 adult patients. The prevalence of HIV infection, HCV infection and co-infection was 25.4%, 30.9%, and 11.0%, respectively. Prevalence exhibited stark geographical variations in the area studied. The four regression models showed Yi ethnicity to be associated with both the prevalence of HIV and of HIV/HCV co-infection. The male drug users in some northwestern counties had greater odds of being infected with HIV than female drug users, but the opposite was observed in some eastern counties. The 'being in drug rehabilitation variable was found to be positively associated with prevalence of HCV infection in some southern townships, however, it was found to be negatively associated with it in some northern townships. CONCLUSIONS/SIGNIFICANCE: The spatial modeling creates better representations of data such that public health interventions must focus on areas with high frequency of HIV/HCV to prevent further transmission of both HIV and HCV.

  12. The N400 as a snapshot of interactive processing: evidence from regression analyses of orthographic neighbor and lexical associate effects

    Science.gov (United States)

    Laszlo, Sarah; Federmeier, Kara D.

    2010-01-01

    Linking print with meaning tends to be divided into subprocesses, such as recognition of an input's lexical entry and subsequent access of semantics. However, recent results suggest that the set of semantic features activated by an input is broader than implied by a view wherein access serially follows recognition. EEG was collected from participants who viewed items varying in number and frequency of both orthographic neighbors and lexical associates. Regression analysis of single item ERPs replicated past findings, showing that N400 amplitudes are greater for items with more neighbors, and further revealed that N400 amplitudes increase for items with more lexical associates and with higher frequency neighbors or associates. Together, the data suggest that in the N400 time window semantic features of items broadly related to inputs are active, consistent with models in which semantic access takes place in parallel with stimulus recognition. PMID:20624252

  13. Enhancement of Visual Field Predictions with Pointwise Exponential Regression (PER) and Pointwise Linear Regression (PLR).

    Science.gov (United States)

    Morales, Esteban; de Leon, John Mark S; Abdollahi, Niloufar; Yu, Fei; Nouri-Mahdavi, Kouros; Caprioli, Joseph

    2016-03-01

    The study was conducted to evaluate threshold smoothing algorithms to enhance prediction of the rates of visual field (VF) worsening in glaucoma. We studied 798 patients with primary open-angle glaucoma and 6 or more years of follow-up who underwent 8 or more VF examinations. Thresholds at each VF location for the first 4 years or first half of the follow-up time (whichever was greater) were smoothed with clusters defined by the nearest neighbor (NN), Garway-Heath, Glaucoma Hemifield Test (GHT), and weighting by the correlation of rates at all other VF locations. Thresholds were regressed with a pointwise exponential regression (PER) model and a pointwise linear regression (PLR) model. Smaller root mean square error (RMSE) values of the differences between the observed and the predicted thresholds at last two follow-ups indicated better model predictions. The mean (SD) follow-up times for the smoothing and prediction phase were 5.3 (1.5) and 10.5 (3.9) years. The mean RMSE values for the PER and PLR models were unsmoothed data, 6.09 and 6.55; NN, 3.40 and 3.42; Garway-Heath, 3.47 and 3.48; GHT, 3.57 and 3.74; and correlation of rates, 3.59 and 3.64. Smoothed VF data predicted better than unsmoothed data. Nearest neighbor provided the best predictions; PER also predicted consistently more accurately than PLR. Smoothing algorithms should be used when forecasting VF results with PER or PLR. The application of smoothing algorithms on VF data can improve forecasting in VF points to assist in treatment decisions.

  14. Applied linear regression

    CERN Document Server

    Weisberg, Sanford

    2013-01-01

    Praise for the Third Edition ""...this is an excellent book which could easily be used as a course text...""-International Statistical Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples. Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illus

  15. Prevalence of microalbuminuria and its associated cardiometabolic risk factors in Korean youth: Data from the Korea National Health and Nutrition Examination Survey.

    Directory of Open Access Journals (Sweden)

    Heeyeon Cho

    Full Text Available Microalbuminuria is a known early predictive factor for renal and cardiovascular diseases, not only for patients with diabetes mellitus or hypertension but also in the general population. However, the prevalence and risk factors associated with microalbuminuria in Korean youth are unknown.The aims of this study are to evaluate the prevalence of microalbuminuria and the association between microalbuminuria and obesity or cardiometabolic risk factors in Korean children and adolescents without diabetes.This study examines data obtained from the Korea National Health and Nutrition Examination Survey (between 2011 and 2014. It includes a total of 1,976 participants aged between 10 and 19 years (boys 1,128 and girls 848. Microalbuminuria was defined as a urine albumin-to-creatinine ratio (UACR of ≥ 30 mg/g and < 300 mg/g. Association between microalbuminuria and the risk factors for cardiometabolic diseases including insulin resistance was evaluated.The prevalence of microalbuminuria was found to be 3.0% in Korean children and adolescents over this time period. The mean UACR for non-obese youth was significantly greater than that found in obese youth (3.2 ± 0.1 mg/g in the non-obese group vs. 2.1 ± 0.2 mg/g in the obese group; P < 0.001. In multiple logistic regression analysis, microalbuminuria was associated with hyperglycemia (OR 2.62, 95% CI 1.09-6.30 and hemoglobin A1c (OR 3.34, 95% CI 1.09-10.17 in the non-obese group and hypertension (OR 14.10, 95% CI 1.12-177.98 and HbA1c (OR 6.68, 95% CI 1.87-23.95 in the obese group.The prevalence of microalbuminuria is not prominent in obese children and adolescents. Our findings demonstrated that the presence of hypertension and hyperglycemia was associated with microalbuminuria. Especially Hemoglobin A1c was associated with microalbuminuria in youths regardless of weight status. Microalbuminuria in pediatric population can be a helpful marker for the risk of cardiovascular disease.

  16. Sparse Reduced-Rank Regression for Simultaneous Dimension Reduction and Variable Selection

    KAUST Repository

    Chen, Lisha

    2012-12-01

    The reduced-rank regression is an effective method in predicting multiple response variables from the same set of predictor variables. It reduces the number of model parameters and takes advantage of interrelations between the response variables and hence improves predictive accuracy. We propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty. We apply a group-lasso type penalty that treats each row of the matrix of the regression coefficients as a group and show that this penalty satisfies certain desirable invariance properties. We develop two numerical algorithms to solve the penalized regression problem and establish the asymptotic consistency of the proposed method. In particular, the manifold structure of the reduced-rank regression coefficient matrix is considered and studied in our theoretical analysis. In our simulation study and real data analysis, the new method is compared with several existing variable selection methods for multivariate regression and exhibits competitive performance in prediction and variable selection. © 2012 American Statistical Association.

  17. Analysis of quantile regression as alternative to ordinary least squares

    OpenAIRE

    Ibrahim Abdullahi; Abubakar Yahaya

    2015-01-01

    In this article, an alternative to ordinary least squares (OLS) regression based on analytical solution in the Statgraphics software is considered, and this alternative is no other than quantile regression (QR) model. We also present goodness of fit statistic as well as approximate distributions of the associated test statistics for the parameters. Furthermore, we suggest a goodness of fit statistic called the least absolute deviation (LAD) coefficient of determination. The procedure is well ...

  18. [Multivariate ordinal logistic regression analysis on the association between consumption of fried food and both esophageal cancer and precancerous lesions].

    Science.gov (United States)

    Guo, L W; Liu, S Z; Zhang, M; Chen, Q; Zhang, S K; Sun, X B

    2017-12-10

    Objective: To investigate the effect of fried food intake on the pathogenesis of esophageal cancer and precancerous lesions. Methods: From 2005 to 2013, all the residents aged 40-69 years from 11 counties (cities) where cancer screening of upper gastrointestinal cancer had been conducted in rural areas of Henan province, were recruited as the subjects of study. Information on demography and lifestyle was collected. The residents under study were screened with iodine staining endoscopic examination and biopsy samples were diagnosed pathologically, under standardized criteria. Subjects with high risk were divided into the groups based on their different pathological degrees. Multivariate ordinal logistic regression analysis was used to analyze the relationship between the frequency of fried food intake and esophageal cancer and precancerous lesions. Results: A total number of 8 792 cases with normal esophagus, 3 680 with mild hyperplasia, 972 with moderate hyperplasia, 413 with severe hyperplasia carcinoma in situ, and 336 cases of esophageal cancer were recruited. Results from multivariate logistic regression analysis showed that, when compared with those who did not eat fried food, the intake of fried food (food appeared a risk factor for both esophageal cancer and precancerous lesions.

  19. Understanding poisson regression.

    Science.gov (United States)

    Hayat, Matthew J; Higgins, Melinda

    2014-04-01

    Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.

  20. Alternative Methods of Regression

    CERN Document Server

    Birkes, David

    2011-01-01

    Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald G. Watts ".an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models." --Technometrics This book provides a balance between theory and practice supported by extensive displays of instructive geometrical constructs. Numerous in-depth case studies illustrate the use of nonlinear regression analysis--with all data s

  1. Association between dental pain and depression in Korean adults using the Korean National Health and Nutrition Examination Survey.

    Science.gov (United States)

    Yang, S E; Park, Y G; Han, K; Min, J A; Kim, S Y

    2016-01-01

    The purpose of this study was to evaluate the relationships between the prevalence of depression and dental pain using a well characterised, nationally representative, population-based study. This study analysed data from the 2012 Korea National Health and Nutrition Examination Survey (n = 4886). Oral health status was assessed using the oral health questionnaire, and oral examination was performed by trained dentists. Depression was defined as the participant having been diagnosed as depression during the previous year. Logistic regression was applied to estimate adjusted odds ratios (AOR) and 95% confidence intervals (CI), controlling for a range of covariates. Results demonstrated that participants included in 'root canal treatment is necessary' showed higher prevalence of self-reported dental pain; in particular, participants with depression presented more dental pain than those without depression. After adjusting for sociodemographic factors, self-reported dental pain increased in participants with depression. The AOR (95% CI) for having self-reported dental pain was 1·58 (1·08-2·33) in dentists' diagnosis of no dental pain/depression group, 1·62 (1·32-1·98) in dentists' diagnosis of dental pain/no depression group and 2·84 (1·10-7·37) in dentists' diagnosis of dental pain/depression group. It was concluded that depression was associated with dental pain after adjustment for potential confounders in Korean adults. Thus, dentists should consider the possible presence of psychopathology when treating patients with dental pain. © 2015 John Wiley & Sons Ltd.

  2. Gender differences in the associations between urinary bisphenol A and body composition among American children: The National Health and Nutrition Examination Survey, 2003–2006

    Directory of Open Access Journals (Sweden)

    Ji Li

    2017-05-01

    Full Text Available Background: As an endocrine disruptor, bisphenol A (BPA exposure has been implicated as a potential risk factor in childhood obesity, which is defined using percentiles of body mass index for age. We aimed to examine the associations between BPA exposure, reflected by urinary BPA concentration, and body composition in American children. Methods: Data of 1860 children aged 8–19 years who participated in the 2003–2006 National Health and Nutrition Examination Survey (NHANES were analyzed in this study. Urinary BPA concentration (ng/mL was used to indicate BPA status in the body. Body composition was measured by dual-energy X-ray absorptiometry (DXA. Multivariate linear regression models were fitted using survey procedures to investigate the associations between urinary BPA level and body composition separately for boys and girls. Results: After adjusting for demographic and lifestyle covariates, higher quartiled and log-transformed urinary BPA levels were significantly associated with elevated lean body mass index (LBMI z-scores in boys (p < 0.05, and significantly associated with elevated fat mass index (FMI z-scores in girls (p < 0.05. Lower urinary BPA concentration was associated with lower percentage of trunk fat in girls (compared to 1st quartile, 2nd-quartile: β = 2.85, 95% CI, 0.92–4.78; 3rd-quartile: β = 2.57, 95% CI, 0.28–4.85; 4th-quartile: β = 2.79, 95% CI, 0.44–5.14; all p < 0.05. Such patterns were not observed in boys. Conclusions: Higher BPA levels may be associated with elevated LBM in boys, but not in girls, while higher BPA levels may be associated with elevated FM in girls, but not in boys.

  3. Thermal Efficiency Degradation Diagnosis Method Using Regression Model

    International Nuclear Information System (INIS)

    Jee, Chang Hyun; Heo, Gyun Young; Jang, Seok Won; Lee, In Cheol

    2011-01-01

    This paper proposes an idea for thermal efficiency degradation diagnosis in turbine cycles, which is based on turbine cycle simulation under abnormal conditions and a linear regression model. The correlation between the inputs for representing degradation conditions (normally unmeasured but intrinsic states) and the simulation outputs (normally measured but superficial states) was analyzed with the linear regression model. The regression models can inversely response an associated intrinsic state for a superficial state observed from a power plant. The diagnosis method proposed herein is classified into three processes, 1) simulations for degradation conditions to get measured states (referred as what-if method), 2) development of the linear model correlating intrinsic and superficial states, and 3) determination of an intrinsic state using the superficial states of current plant and the linear regression model (referred as inverse what-if method). The what-if method is to generate the outputs for the inputs including various root causes and/or boundary conditions whereas the inverse what-if method is the process of calculating the inverse matrix with the given superficial states, that is, component degradation modes. The method suggested in this paper was validated using the turbine cycle model for an operating power plant

  4. Consecutive regression of MALT lymphomas coexisting in the pharyngeal and gastric tissue after the eradication of Helicobacter pylori

    Directory of Open Access Journals (Sweden)

    Giuseppe Ivan Potente

    2012-09-01

    Full Text Available The stomach is one of the most common organs in which mucosa-associated lymphoid tissue (MALT lymphoma develops. It is well established that Helicobacter pylori (Hp infection plays a major role in the development of gastric MALT lymphoma and that the presence of Hp in the gastric mucosa is connected with mucosa-associated lymphatic tissue (MALT.The same tissue is located in the oral cavity and pharynx in Waldayer’s circuit. Recently, the oral cavity was proposed as an extragastric reservoir of Hp infection. We report the case of a 79-year-old female patient with concomitant pharyngeal (MALT lymphoma and Hp-related gastric MALT lymphoma. Gastric MALT lymphoma was detected both through endoscopic examination as well as in biopsies. Pharyngeal MALT lymphoma was also detected in biopsies. Hp has been recognized in the gastric mucosa by positive serum H. pylori antibody and urease tests. Treatment of the Hp infection in our patient using antibiotics led to the regression of both lesions. This is the first case report on the regression of a pharyngeal MALT lymphoma after Hp eradication.

  5. Bronchoscopic examinations for evaluating chest abnormal shadows associated with hematological disease

    International Nuclear Information System (INIS)

    Nakayama, Masayuki; Bando, Masashi; Kobayashi, Akira; Yamasawa, Hideaki; Ohno, Shoji; Sugiyama, Yukihiko

    2006-01-01

    Hematological diseases cause various respiratory complications, but their differentiation only by blood tests and chest radiology is often difficult. To clarify the characteristics of respiratory complications associated with hematological diseases and the diagnostic usefulness of bronchoscopic examinations for these complications, we clinically evaluated mainly underlying diseases, chest radiological findings, and bronchoscopic findings in 31 patients in whom we performed bronchoscopy for chest abnormal shadows associated with hematological disease during the past 13-year period. Among hematological disease, leukemia was most frequently observed, followed by malignant lymphoma and myelodysplastic syndrome. The most frequently observed chest CT findings were localized consolidation and diffuse Ground-glass opacity. Bronchoscopic examinations provided a definitive diagnosis in 20 patients (64.5%), and the most frequent diagnosis was pulmonary invasion by neoplastic cells (7 patients). Pulmonary invasion by neoplastic cells showed various images, and transbronchial lung biopsy : TBLB was useful for definitive diagnosis. After consideration of the general condition of patients and the risk of complications, bronchoscopy including TBLB should be performed when possible. (author)

  6. Association between Patient History and Physical Examination and Osteoarthritis after Ankle Sprain.

    Science.gov (United States)

    van Ochten, John M; de Vries, Anja D; van Putte, Nienke; Oei, Edwin H G; Bindels, Patrick J E; Bierma-Zeinstra, Sita M A; van Middelkoop, Marienke

    2017-09-01

    Structural abnormalities on MRI are frequent after an ankle sprain. To determine the association between patient history, physical examination and early osteoarthritis (OA) in patients after a previous ankle sprain, 98 patients with persistent complaints were selected from a cross-sectional study. Patient history taking and physical examination were applied and MRI was taken. Univariate and multivariable analyses were used to test possible associations. Signs of OA (cartilage loss, osteophytes and bone marrow edema) were seen in the talocrural joint (TCJ) in 40% and the talonavicular joint (TNJ) in 49%. Multivariable analysis showed a significant positive association between swelling (OR 3.58, 95%CI 1.13;11.4), a difference in ROM of passive plantar flexion (OR 1.09, 95%CI 1.01;1.18) and bone edema in the TCJ. A difference in ROM of passive plantar flexion (OR 1.07, 95%CI 1.00;1.15) and pain at the end range of dorsiflexion/plantar flexion (OR 5.23, 95%CI 1.88;14.58) were associated with osteophytes in the TNJ. Pain at the end of dorsiflexion/plantar flexion, a difference in ROM of passive plantar flexion and swelling seem to be associated with features of OA (bone marrow edema, osteophytes) in the TCJ and TNJ. Our findings may guide physicians to predict structural joint abnormalities as signs of osteoarthritis. 1b. © Georg Thieme Verlag KG Stuttgart · New York.

  7. The power of regression to the mean: a social norm study revisited

    NARCIS (Netherlands)

    Verkooijen, K.T.; Stok, F.M.; Mollen, S.

    2015-01-01

    This research follows up on a study by Schultz et al. (2007), in which the effect of a social norm intervention on energy consumption was examined. The present studies included control groups to examine whether social norm effects would persist beyond regression to the mean. Both studies had a 2

  8. The power of regression to the mean: A social norm study revisited

    NARCIS (Netherlands)

    Verkooijen, K.T.; Stok, F.M.; Mollen, S.

    2015-01-01

    This research follows up on a study by Schultz et al. (2007), in which the effect of a social norm intervention on energy consumption was examined. The present studies included control groups to examine whether social norm effects would persist beyond regression to the mean. Both studies had a 2

  9. Multivariate nonparametric regression and visualization with R and applications to finance

    CERN Document Server

    Klemelä, Jussi

    2014-01-01

    A modern approach to statistical learning and its applications through visualization methods With a unique and innovative presentation, Multivariate Nonparametric Regression and Visualization provides readers with the core statistical concepts to obtain complete and accurate predictions when given a set of data. Focusing on nonparametric methods to adapt to the multiple types of data generatingmechanisms, the book begins with an overview of classification and regression. The book then introduces and examines various tested and proven visualization techniques for learning samples and functio

  10. Introduction to regression graphics

    CERN Document Server

    Cook, R Dennis

    2009-01-01

    Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like plot rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be utilized as the main computer program in a linear regression course. The accompanying disks, for both Macintosh and Windows computers, contain the R-code and Xlisp-Stat. An Instructor's Manual presenting detailed solutions to all the problems in the book is ava

  11. Examining the association of smoking with work productivity and associated costs in Japan.

    Science.gov (United States)

    Suwa, Kiyomi; Flores, Natalia M; Yoshikawa, Reiko; Goto, Rei; Vietri, Jeffrey; Igarashi, Ataru

    2017-09-01

    Smoking is associated with significant health and economic burden globally, including an increased risk of many leading causes of mortality and significant impairments in work productivity. This burden is attenuated by successful tobacco cessation, including reduced risk of disease and improved productivity. The current study aimed to show the benefits of smoking cessation for workplace productivity and decreased costs associated with loss of work impairment. The data source was the 2011 Japan National Health and Wellness Survey (n = 30,000). Respondents aged 20-64 were used in the analyses (n = 23,738) and were categorized into: current smokers, former smokers, and never smokers. Generalized linear models controlling for demographics and health characteristics examined the relationship of smoking status with the Work Productivity and Activity Impairment questionnaire (WPAI-GH) endpoints, as well as estimated indirect costs. Current smokers reported the greatest overall work impairment, including absenteeism (i.e. work time missed) and presenteeism (i.e. impairment while at work); however, after controlling for covariates, there were no significant differences between former smokers and never smokers on overall work impairment. Current smokers and former smokers had greater activity impairment (i.e. impairment in daily activities) than never smokers. Current smokers reported the highest indirect costs (i.e. costs associated with work impairment); however, after controlling for covariates, there were no significant differences between former smokers and never smokers on indirect costs. Smoking exerts a large health and economic burden; however, smoking cessation attenuates this burden. The current study provides important further evidence of this association, with former smokers appearing statistically indistinguishable from never smokers in terms of work productivity loss and associated indirect costs among a large representative sample of Japanese workers

  12. Diet Quality Associated with Total Sodium Intake among US Adults Aged ≥18 Years-National Health and Nutrition Examination Survey, 2009-2012.

    Science.gov (United States)

    Mercado, Carla I; Cogswell, Mary E; Perrine, Cria G; Gillespie, Cathleen

    2017-10-25

    Diet quality or macronutrient composition of total daily sodium intake (dNa) <2300 mg/day in the United States (US) is unknown. Using data from 2011-2014 NHANES (National Health and Nutrition Examination Survey), we examined 24-h dietary recalls ( n = 10,142) from adults aged ≥18 years and investigated how diet composition and quality are associated with dNa. Diet quality was assessed using components of macronutrients and Healthy Eating Index 2010 (HEI-2010). Associations were tested using linear regression analysis adjusted for total energy (kcal), age, gender, and race/ethnicity. One-day dNa in the lower quartiles were more likely reported among women, older adults (≥65 years old), and lower quartiles of total energy (kcal) ( p -values ≤ 0.001). With increasing dNa, there was an increase in the mean protein, fiber, and total fat densities, while total carbohydrates densities decreased. As dNa increased, meat protein, refined grains, dairy, and total vegetables, greens and beans densities increased; while total fruit and whole fruit densities decreased. Modified HEI-2010 total score (total score without sodium component) increased as dNa increased (adjusted coefficient: 0.11, 95% confidence interval = 0.07, 0.15). Although diet quality, based on modified HEI-2010 total score, increased on days with greater dNa, there is much room for improvement with mean diet quality of about half of the optimal level.

  13. Emergency department documentation templates: variability in template selection and association with physical examination and test ordering in dizziness presentations

    Directory of Open Access Journals (Sweden)

    Meurer William J

    2011-03-01

    Full Text Available Abstract Background Clinical documentation systems, such as templates, have been associated with process utilization. The T-System emergency department (ED templates are widely used but lacking are analyses of the templates association with processes. This system is also unique because of the many different template options available, and thus the selection of the template may also be important. We aimed to describe the selection of templates in ED dizziness presentations and to investigate the association between items on templates and process utilization. Methods Dizziness visits were captured from a population-based study of EDs that use documentation templates. Two relevant process outcomes were assessed: head computerized tomography (CT scan and nystagmus examination. Multivariable logistic regression was used to estimate the probability of each outcome for patients who did or did not receive a relevant-item template. Propensity scores were also used to adjust for selection effects. Results The final cohort was 1,485 visits. Thirty-one different templates were used. Use of a template with a head CT item was associated with an increase in the adjusted probability of head CT utilization from 12.2% (95% CI, 8.9%-16.6% to 29.3% (95% CI, 26.0%-32.9%. The adjusted probability of documentation of a nystagmus assessment increased from 12.0% (95%CI, 8.8%-16.2% when a nystagmus-item template was not used to 95.0% (95% CI, 92.8%-96.6% when a nystagmus-item template was used. The associations remained significant after propensity score adjustments. Conclusions Providers use many different templates in dizziness presentations. Important differences exist in the various templates and the template that is used likely impacts process utilization, even though selection may be arbitrary. The optimal design and selection of templates may offer a feasible and effective opportunity to improve care delivery.

  14. Differential item functioning analysis with ordinal logistic regression techniques. DIFdetect and difwithpar.

    Science.gov (United States)

    Crane, Paul K; Gibbons, Laura E; Jolley, Lance; van Belle, Gerald

    2006-11-01

    We present an ordinal logistic regression model for identification of items with differential item functioning (DIF) and apply this model to a Mini-Mental State Examination (MMSE) dataset. We employ item response theory ability estimation in our models. Three nested ordinal logistic regression models are applied to each item. Model testing begins with examination of the statistical significance of the interaction term between ability and the group indicator, consistent with nonuniform DIF. Then we turn our attention to the coefficient of the ability term in models with and without the group term. If including the group term has a marked effect on that coefficient, we declare that it has uniform DIF. We examined DIF related to language of test administration in addition to self-reported race, Hispanic ethnicity, age, years of education, and sex. We used PARSCALE for IRT analyses and STATA for ordinal logistic regression approaches. We used an iterative technique for adjusting IRT ability estimates on the basis of DIF findings. Five items were found to have DIF related to language. These same items also had DIF related to other covariates. The ordinal logistic regression approach to DIF detection, when combined with IRT ability estimates, provides a reasonable alternative for DIF detection. There appear to be several items with significant DIF related to language of test administration in the MMSE. More attention needs to be paid to the specific criteria used to determine whether an item has DIF, not just the technique used to identify DIF.

  15. Analysis of stress fractures associated with lameness in Thoroughbred flat racehorses training on different track surfaces undergoing nuclear scintigraphic examination.

    Science.gov (United States)

    MacKinnon, M C; Bonder, D; Boston, R C; Ross, M W

    2015-05-01

    There is limited information regarding the impact of training track surface on the occurrence of stress fractures. To evaluate the impact of training track surface on the proportion of long bone and pelvic stress fractures associated with lameness in Thoroughbred horses in flat race training undergoing nuclear scintigraphic examination. Retrospective study. Scintigraphic examinations of Thoroughbred flat racehorses were evaluated from 2 hospitals (hospital A [Toronto Equine Hospital], 2003-2009, and hospital B [George D. Widener Hospital for Large Animals, School of Veterinary Medicine, University of Pennsylvania], 1994-2006). Horses admitted to hospital A trained at a single track, at which the main training surface changed from dirt to synthetic on 27 August 2006. Two distinct populations existed at hospital B: horses that trained on dirt (numerous trainers) and those that trained on turf (single trainer). All scintigraphic images were evaluated by a blinded reviewer. Fisher's exact test and logistic regression were used when appropriate, and significance was set at Pfractures detected in scintigraphic examinations from horses training on a synthetic surface (31.7%) in comparison to scintigraphic examinations from horses training on a dirt surface (23.0%) at an earlier point in time (P = 0.03). There was a greater proportion of hindlimb/pelvic and tibial stress fractures diagnosed in horses from the synthetic surface-trained group than from the dirt-trained group at hospital A (Pfractures diagnosed, but other factors, such as training philosophy, appear to be important. Future prospective investigations to fully elucidate the relationship between training track surface and the proportion of stress fractures and other nonfatal musculoskeletal injuries are warranted. © 2014 EVJ Ltd.

  16. The effect of postoperative medical treatment on left ventricular mass regression after aortic valve replacement.

    Science.gov (United States)

    Helder, Meghana R K; Ugur, Murat; Bavaria, Joseph E; Kshettry, Vibhu R; Groh, Mark A; Petracek, Michael R; Jones, Kent W; Suri, Rakesh M; Schaff, Hartzell V

    2015-03-01

    The study objective was to analyze factors associated with left ventricular mass regression in patients undergoing aortic valve replacement with a newer bioprosthesis, the Trifecta valve pericardial bioprosthesis (St Jude Medical Inc, St Paul, Minn). A total of 444 patients underwent aortic valve replacement with the Trifecta bioprosthesis from 2007 to 2009 at 6 US institutions. The clinical and echocardiographic data of 200 of these patients who had left ventricular hypertrophy and follow-up studies 1 year postoperatively were reviewed and compared to analyze factors affecting left ventricular mass regression. Mean (standard deviation) age of the 200 study patients was 73 (9) years, 66% were men, and 92% had pure or predominant aortic valve stenosis. Complete left ventricular mass regression was observed in 102 patients (51%) by 1 year postoperatively. In univariate analysis, male sex, implantation of larger valves, larger left ventricular end-diastolic volume, and beta-blocker or calcium-channel blocker treatment at dismissal were significantly associated with complete mass regression. In the multivariate model, odds ratios (95% confidence intervals) indicated that male sex (3.38 [1.39-8.26]) and beta-blocker or calcium-channel blocker treatment at dismissal (3.41 [1.40-8.34]) were associated with increased probability of complete left ventricular mass regression. Patients with higher preoperative systolic blood pressure were less likely to have complete left ventricular mass regression (0.98 [0.97-0.99]). Among patients with left ventricular hypertrophy, postoperative treatment with beta-blockers or calcium-channel blockers may enhance mass regression. This highlights the need for close medical follow-up after operation. Labeled valve size was not predictive of left ventricular mass regression. Copyright © 2015 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

  17. Spontaneous regression of intracranial malignant lymphoma

    International Nuclear Information System (INIS)

    Kojo, Nobuto; Tokutomi, Takashi; Eguchi, Gihachirou; Takagi, Shigeyuki; Matsumoto, Tomie; Sasaguri, Yasuyuki; Shigemori, Minoru.

    1988-01-01

    In a 46-year-old female with a 1-month history of gait and speech disturbances, computed tomography (CT) demonstrated mass lesions of slightly high density in the left basal ganglia and left frontal lobe. The lesions were markedly enhanced by contrast medium. The patient received no specific treatment, but her clinical manifestations gradually abated and the lesions decreased in size. Five months after her initial examination, the lesions were absent on CT scans; only a small area of low density remained. Residual clinical symptoms included mild right hemiparesis and aphasia. After 14 months the patient again deteriorated, and a CT scan revealed mass lesions in the right frontal lobe and the pons. However, no enhancement was observed in the previously affected regions. A biopsy revealed malignant lymphoma. Despite treatment with steroids and radiation, the patient's clinical status progressively worsened and she died 27 months after initial presentation. Seven other cases of spontaneous regression of primary malignant lymphoma have been reported. In this case, the mechanism of the spontaneous regression was not clear, but changes in immunologic status may have been involved. (author)

  18. Shy, but funny? Examining peer-valued characteristics as moderators of the associations between anxious-withdrawal and peer outcomes during early adolescence.

    Science.gov (United States)

    Markovic, Andrea; Bowker, Julie C

    2015-04-01

    Research has revealed significant heterogeneity in the group-level peer outcomes associated with anxious-withdrawal, but little is known about possible sources of this heterogeneity during early adolescence. This study of 271 young adolescents (49 % female; M age = 11.54 years) examined whether the concurrent and short-term longitudinal (3 month period) associations between peer-nominated anxious-withdrawn behaviors and three group-level peer outcomes (overt victimization, peer acceptance, popularity) varied as a function of peer-valued characteristics (humor, prosocial behavior, physical attractiveness, athletic ability) and gender, after accounting for the effects of involvement in mutual friendships. Regression analyses revealed that the associations between anxious-withdrawal and peer outcomes were moderated by peer-valued characteristics and, in many cases, gender. For example, anxious-withdrawal was related positively to overt victimization for all adolescents who were high in prosocial behavior. But, anxious-withdrawal was related negatively to popularity for adolescent boys who were high in prosocial behavior and adolescent girls who were low in prosocial behavior. Anxious-withdrawal also predicted increases in acceptance for adolescent girls who were high in humor, but decreases in acceptance for adolescent boys who were high in humor. Several additional moderator effects were found for boys only. The findings highlight the importance of considering the unique constellation of characteristics displayed by anxious-withdrawn young adolescents in studies on peer experiences at the group-level of social complexity.

  19. Predictive value of grade point average (GPA), Medical College Admission Test (MCAT), internal examinations (Block) and National Board of Medical Examiners (NBME) scores on Medical Council of Canada qualifying examination part I (MCCQE-1) scores.

    Science.gov (United States)

    Roy, Banibrata; Ripstein, Ira; Perry, Kyle; Cohen, Barry

    2016-01-01

    To determine whether the pre-medical Grade Point Average (GPA), Medical College Admission Test (MCAT), Internal examinations (Block) and National Board of Medical Examiners (NBME) scores are correlated with and predict the Medical Council of Canada Qualifying Examination Part I (MCCQE-1) scores. Data from 392 admitted students in the graduating classes of 2010-2013 at University of Manitoba (UofM), College of Medicine was considered. Pearson's correlation to assess the strength of the relationship, multiple linear regression to estimate MCCQE-1 score and stepwise linear regression to investigate the amount of variance were employed. Complete data from 367 (94%) students were studied. The MCCQE-1 had a moderate-to-large positive correlation with NBME scores and Block scores but a low correlation with GPA and MCAT scores. The multiple linear regression model gives a good estimate of the MCCQE-1 (R2 =0.604). Stepwise regression analysis demonstrated that 59.2% of the variation in the MCCQE-1 was accounted for by the NBME, but only 1.9% by the Block exams, and negligible variation came from the GPA and the MCAT. Amongst all the examinations used at UofM, the NBME is most closely correlated with MCCQE-1.

  20. Inverse association between insulin resistance and gait speed in nondiabetic older men: results from the U.S. National Health and Nutrition Examination Survey (NHANES 1999-2002

    Directory of Open Access Journals (Sweden)

    Yu Yau-Hua

    2009-11-01

    Full Text Available Abstract Background Recent studies have revealed the associations between insulin resistance (IR and geriatric conditions such as frailty and cognitive impairment. However, little is known about the relation of IR to physical impairment and limitation in the aging process, eg. slow gait speed and poor muscle strength. The aim of this study is to determine the effect of IR in performance-based physical function, specifically gait speed and leg strength, among nondiabetic older adults. Methods Cross-sectional data were from the population-based National Health and Nutrition Examination Survey (1999-2002. A total of 1168 nondiabetic adults (≥ 50 years with nonmissing values in fasting measures of insulin and glucose, habitual gait speed (HGS, and leg strength were analyzed. IR was assessed by homeostasis model assessment (HOMA-IR, whereas HGS and peak leg strength by the 20-foot timed walk test and an isokinetic dynamometer, respectively. We used multiple linear regression to examine the association between IR and performance-based physical function. Results IR was inversely associated with gait speed among the men. After adjusting demographics, body mass index, alcohol consumption, smoking status, chronic co-morbidities, and markers of nutrition and cardiovascular risk, each increment of 1 standard deviation in the HOMA-IR level was associated with a 0.04 m/sec decrease (p = 0.003 in the HGS in men. We did not find such association among the women. The IR-HGS association was not changed after further adjustment of leg strength. Last, HOMA-IR was not demonstrated in association with peak leg strength. Conclusion IR is inversely associated with HGS among older men without diabetes. The results suggest that IR, an important indicator of gait function among men, could be further investigated as an intervenable target to prevent walking limitation.

  1. Diabetes Mellitus Impairs Left Ventricular Mass Regression after Surgical or Transcatheter Aortic Valve Replacement for Severe Aortic Stenosis.

    Science.gov (United States)

    Nakamura, Teruya; Toda, Koichi; Kuratani, Toru; Miyagawa, Shigeru; Yoshikawa, Yasushi; Fukushima, Satsuki; Saito, Shunsuke; Yoshioka, Daisuke; Kashiyama, Noriyuki; Daimon, Takashi; Sawa, Yoshiki

    2016-01-01

    It is well-documented that persistent myocardial hypertrophy in patients with aortic stenosis is related to suboptimal postoperative outcomes after aortic valve replacement. Although diabetes is known to potentially exacerbate myocardial hypertrophy, it has yet to be examined if it affects postoperative left ventricular mass regression (LVMR). A single-centre, retrospective analysis was performed on 183 consecutive patients who underwent either surgical or transcatheter aortic valve replacement between 2010 and May 2013. Patient demographics, postoperative outcomes and echocardiographic data were obtained preoperatively and a year after surgery. There were 42 diabetic and 141 non-diabetic patients. Preoperative characteristics of diabetic patients were statistically similar to those of non-diabetic patients, except for higher prevalence of hyperlipidaemia (p regression analysis demonstrated that diabetes (standardised partial regression coefficient (SPRC)=-0.187, p=0.018), female gender (SPRC=0.245, p=0.026) and age (SPRC=0.203, p=0.018) were associated with poor postoperative LVMR. Patients with diabetes showed suboptimal postoperative LVMR, and the disease was a prognostic factor that was associated with poor LVMR. These findings suggest that diabetes may predispose the particular group of patients to worse postoperative outcomes. Copyright © 2015 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.

  2. Unsupportive social interactions and affective states: examining associations of two oxytocin-related polymorphisms.

    Science.gov (United States)

    McInnis, Opal A; McQuaid, Robyn J; Matheson, Kimberly; Anisman, Hymie

    2017-01-01

    Two single-nucleotide polymorphisms (SNPs) on oxytocin-related genes, specifically the oxytocin receptor (OXTR) rs53576 and the CD38 rs3796863 variants, have been associated with alterations in prosocial behaviors. A cross-sectional study was conducted among undergraduate students (N = 476) to examine associations between the OXTR and CD38 polymorphisms and unsupportive social interactions and mood states. Results revealed no association between perceived levels of unsupportive social interactions and the OXTR polymorphism. However, A carriers of the CD38 polymorphism, a variant previously associated with elevated oxytocin, reported greater perceived peer unsupportive interactions compared to CC carriers. As expected, perceived unsupportive interactions from peers was associated with greater negative affect, which was moderated by the CD38 polymorphism. Specifically, this relation was stronger among CC carriers of the CD38 polymorphism (a variant thought to be linked to lower oxytocin). When examining whether the OXTR polymorphism moderated the relation between unsupportive social interactions from peers and negative affect there was a trend toward significance, however, this did not withstand multiple testing corrections. These findings are consistent with the perspective that a variant on an oxytocin polymorphism that may be tied to lower oxytocin is related to poor mood outcomes in association with negative social interactions. At the same time, having a genetic constitution presumed to be associated with higher oxytocin was related to increased perceptions of unsupportive social interactions. These seemingly paradoxical findings could be related to previous reports in which variants associated with prosocial behaviors were also tied to relatively more effective coping styles to deal with challenges.

  3. Association of volume of patient encounters with residents' in-training examination performance.

    Science.gov (United States)

    McCoy, Christopher P; Stenerson, Matthew B; Halvorsen, Andrew J; Homme, Jason H; McDonald, Furman S

    2013-08-01

    Patient care and medical knowledge are Accreditation Council for Graduate Medical Education (ACGME) core competencies. The correlation between amount of patient contact and knowledge acquisition is not known. To determine if a correlation exists between the number of patient encounters and in-training exam (ITE) scores in internal medicine (IM) and pediatric residents at a large academic medical center. Retrospective cohort study Resident physicians at Mayo Clinic from July 2006 to June 2010 in IM (318 resident-years) and pediatrics (66 resident-years). We tabulated patient encounters through review of clinical notes in an electronic medical record during post graduate year (PGY)-1 and PGY-2. Using linear regression models, we investigated associations between ITE score and number of notes during the previous PGY, adjusted for previous ITE score, gender, medical school origin, and conference attendance. For IM, PGY-2 admission and consult encounters in the hospital and specialty clinics had a positive linear association with ITE-3 % score (β = 0.02; p = 0.004). For IM, PGY-1 conference attendance is positively associated with PGY-2 ITE performance. We did not detect a correlation between PGY-1 patient encounters and subsequent ITE scores for IM or pediatric residents. No association was found between IM PGY-2 ITE score and inpatient, outpatient, or total encounters in the first year of training. Resident continuity clinic and total encounters were not associated with change in PGY-3 ITE score. We identified a positive association between hospital and subspecialty encounters during the second year of IM training and subsequent ITE score, such that each additional 50 encounters were associated with an increase of 1 % correct in PGY-3 ITE score after controlling for previous ITE performance and continuity clinic encounters. We did not find a correlation for volume of encounters and medical knowledge for IM PGY-1 residents or the pediatric cohort.

  4. Estimating Gestational Age With Sonography: Regression-Derived Formula Versus the Fetal Biometric Average.

    Science.gov (United States)

    Cawyer, Chase R; Anderson, Sarah B; Szychowski, Jeff M; Neely, Cherry; Owen, John

    2018-03-01

    To compare the accuracy of a new regression-derived formula developed from the National Fetal Growth Studies data to the common alternative method that uses the average of the gestational ages (GAs) calculated for each fetal biometric measurement (biparietal diameter, head circumference, abdominal circumference, and femur length). This retrospective cross-sectional study identified nonanomalous singleton pregnancies that had a crown-rump length plus at least 1 additional sonographic examination with complete fetal biometric measurements. With the use of the crown-rump length to establish the referent estimated date of delivery, each method's (National Institute of Child Health and Human Development regression versus Hadlock average [Radiology 1984; 152:497-501]), error at every examination was computed. Error, defined as the difference between the crown-rump length-derived GA and each method's predicted GA (weeks), was compared in 3 GA intervals: 1 (14 weeks-20 weeks 6 days), 2 (21 weeks-28 weeks 6 days), and 3 (≥29 weeks). In addition, the proportion of each method's examinations that had errors outside prespecified (±) day ranges was computed by using odds ratios. A total of 16,904 sonograms were identified. The overall and prespecified GA range subset mean errors were significantly smaller for the regression compared to the average (P < .01), and the regression had significantly lower odds of observing examinations outside the specified range of error in GA intervals 2 (odds ratio, 1.15; 95% confidence interval, 1.01-1.31) and 3 (odds ratio, 1.24; 95% confidence interval, 1.17-1.32) than the average method. In a contemporary unselected population of women dated by a crown-rump length-derived GA, the National Institute of Child Health and Human Development regression formula produced fewer estimates outside a prespecified margin of error than the commonly used Hadlock average; the differences were most pronounced for GA estimates at 29 weeks and later.

  5. An examination of bullying in georgia schools: demographic and school climate factors associated with willingness to intervene in bullying situations.

    Science.gov (United States)

    Goldammer, Lori; Swahn, Monica H; Strasser, Sheryl M; Ashby, Jeffrey S; Meyers, Joel

    2013-08-01

    Research dedicated to identification of precursors to cases of aggravated bullying in schools has led to enhanced knowledge of risk factors for both victimization and perpetration. However, characteristics among those who are more likely to intervene in such situations are less understood. The purpose of this study is to examine the associations between demographic characteristics, school climate and psychosocial factors, and willingness to intervene in a bullying situation among middle and high school students in Georgia. We computed analyses using cross-sectional data from the Georgia Student Health Survey II (GSHS 2006) administered to public school students in grades 6, 8, 10, and 12 (n=175,311). We used logistic regression analyses to determine the demographic, school climate and psychosocial factors associated with a willingness to intervene in a bullying situation. Students who were white and who were girls were most likely to report willingness to intervene in bullying situations. Several school-climate factors, such as feeling safe at school, liking school, feeling successful at school and perceiving clear rules at school, were associated with willingness to intervene, while youth who reported binge drinking were less willing to intervene. These findings, while preliminary, indicate that girls, students who are white, and students who experience a relatively positive school climate and adaptive psychosocial factors are more likely to report that they would intervene in bullying situations. These findings may guide how bullying is addressed in schools and underscore the importance of safe school climates.

  6. Association between Travel Times and Food Procurement Practices among Female Supplemental Nutrition Assistance Program Participants in Eastern North Carolina

    Science.gov (United States)

    Jilcott, Stephanie B.; Moore, Justin B.; Wall-Bassett, Elizabeth D.; Liu, Haiyong; Saelens, Brian E.

    2011-01-01

    Objective: To examine associations between self-reported vehicular travel behaviors, perceived stress, food procurement practices, and body mass index among female Supplemental Nutrition Assistance Program (SNAP) participants. Analysis: The authors used correlation and regression analyses to examine cross-sectional associations between travel time…

  7. Harmonic regression of Landsat time series for modeling attributes from national forest inventory data

    Science.gov (United States)

    Wilson, Barry T.; Knight, Joseph F.; McRoberts, Ronald E.

    2018-03-01

    Imagery from the Landsat Program has been used frequently as a source of auxiliary data for modeling land cover, as well as a variety of attributes associated with tree cover. With ready access to all scenes in the archive since 2008 due to the USGS Landsat Data Policy, new approaches to deriving such auxiliary data from dense Landsat time series are required. Several methods have previously been developed for use with finer temporal resolution imagery (e.g. AVHRR and MODIS), including image compositing and harmonic regression using Fourier series. The manuscript presents a study, using Minnesota, USA during the years 2009-2013 as the study area and timeframe. The study examined the relative predictive power of land cover models, in particular those related to tree cover, using predictor variables based solely on composite imagery versus those using estimated harmonic regression coefficients. The study used two common non-parametric modeling approaches (i.e. k-nearest neighbors and random forests) for fitting classification and regression models of multiple attributes measured on USFS Forest Inventory and Analysis plots using all available Landsat imagery for the study area and timeframe. The estimated Fourier coefficients developed by harmonic regression of tasseled cap transformation time series data were shown to be correlated with land cover, including tree cover. Regression models using estimated Fourier coefficients as predictor variables showed a two- to threefold increase in explained variance for a small set of continuous response variables, relative to comparable models using monthly image composites. Similarly, the overall accuracies of classification models using the estimated Fourier coefficients were approximately 10-20 percentage points higher than the models using the image composites, with corresponding individual class accuracies between six and 45 percentage points higher.

  8. Patterns of medicinal plant use: an examination of the Ecuadorian Shuar medicinal flora using contingency table and binomial analyses.

    Science.gov (United States)

    Bennett, Bradley C; Husby, Chad E

    2008-03-28

    Botanical pharmacopoeias are non-random subsets of floras, with some taxonomic groups over- or under-represented. Moerman [Moerman, D.E., 1979. Symbols and selectivity: a statistical analysis of Native American medical ethnobotany, Journal of Ethnopharmacology 1, 111-119] introduced linear regression/residual analysis to examine these patterns. However, regression, the commonly-employed analysis, suffers from several statistical flaws. We use contingency table and binomial analyses to examine patterns of Shuar medicinal plant use (from Amazonian Ecuador). We first analyzed the Shuar data using Moerman's approach, modified to better meet requirements of linear regression analysis. Second, we assessed the exact randomization contingency table test for goodness of fit. Third, we developed a binomial model to test for non-random selection of plants in individual families. Modified regression models (which accommodated assumptions of linear regression) reduced R(2) to from 0.59 to 0.38, but did not eliminate all problems associated with regression analyses. Contingency table analyses revealed that the entire flora departs from the null model of equal proportions of medicinal plants in all families. In the binomial analysis, only 10 angiosperm families (of 115) differed significantly from the null model. These 10 families are largely responsible for patterns seen at higher taxonomic levels. Contingency table and binomial analyses offer an easy and statistically valid alternative to the regression approach.

  9. [Association between daily lifestyle and the risk of metabolic syndrome among young adults in Japan. An analysis of Kobe city young adult health examination data].

    Science.gov (United States)

    Soga, Youji; Shirai, Chika; Ijichi, Akihiro

    2013-02-01

    Appropriate lifestyle modifications through health guidance and other methods are known to be effective in preventing lifestyle-related diseases. Furthermore, early intervention is key. To examine the association between daily lifestyle and the risk of metabolic syndrome among young adults in Japan, we analyzed data from the Kobe City Young Adult Health Examination. We examined 4,912 adults aged 30 to 39 years to identify the association between daily lifestyle and the risk of metabolic syndrome. Daily lifestyle was assessed from 11 lifestyle-related items in the questionnaire administered during the health exam. The Standard Health Exam and Guidance Program by the Ministry of Health and Labor was used to determine the risks of abdominal obesity, hypertension, diabetes, and hypercholesterolemia. Having a risk related to metabolic syndrome was defined as having a risk of abdominal obesity combined with a risk of hypertension, diabetes, or hypercholesterolemia. We also evaluated the stages of behavioral change in those who possessed a risk of metabolic syndrome, as well as their willingness to receive health guidance. Eating quickly had a significantly greater association with-risk of metabolic syndrome, for both sexes, than eating slowly or at a normal pace. For women, smoking, skipping breakfast more than three days a week, and eating supper within two hours before going to bed for more than three days a week were associated with risk of metabolic syndrome. A multiple regression analysis showed that skipping breakfast (P adults in their thirties in Kobe, irregular eating habits seemed to be associated with risk of metabolic syndrome. Furthermore, their intention to/awareness of the need to change their behavior and their willingness to receive health guidance were rather strong. Thus, for the "Tokutei kenshin (specific national health checkup system)" to achieve its objective of preventing lifestyle-related diseases more effectively than at present, the target

  10. Examining Associations between Reading Motivation and Inference Generation beyond Reading Comprehension Skill

    Science.gov (United States)

    Clinton, Virginia

    2015-01-01

    The purpose of this study was to examine the associations between reading motivation and inference generation while reading. Undergraduate participants (N = 69) read two science articles while thinking aloud, completed a standardized reading comprehension assessment, and self reported their habitual reading motivation. Findings indicate that…

  11. Is Dental Utilization Associated with Oral Health Literacy?

    Science.gov (United States)

    Burgette, J M; Lee, J Y; Baker, A D; Vann, W F

    2016-02-01

    The objectives of this study were to examine the pattern of association between dental utilization and oral health literacy (OHL). As part of the Carolina Oral Health Literacy Project, clients in the Women, Infants, and Children's Special Supplemental Nutrition Program completed a structured 30-min in-person interview conducted by 2 trained interviewers at 9 sites in 7 counties in North Carolina. Data were collected on clients' OHL, sociodemographics, dental utilization, self-efficacy, and dental knowledge. The outcome, OHL, was measured with a dental word recognition test (30-item Rapid Estimate of Adult Literacy in Dentistry). Descriptive and multiple linear regression methods were used to examine the distribution of OHL and its association with covariates. After adjusting for age, education, race, marital status, self-efficacy, and dental knowledge, multiple linear regression showed that dental utilization was not a significant predictor of OHL (P > 0.05). Under the conditions of this study, dental utilization was not a significant predictor of OHL. © International & American Associations for Dental Research 2015.

  12. Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis.

    Science.gov (United States)

    Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

    2015-01-01

    Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended.

  13. Associations of blood lead, cadmium, and mercury with estimated glomerular filtration rate in the Korean general population: Analysis of 2008-2010 Korean National Health and Nutrition Examination Survey data

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Yangho [Department of Occupational and Environmental Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan (Korea, Republic of); Lee, Byung-Kook, E-mail: bklee@sch.ac.kr [Institute of Environmental and Occupational Medicine, Soonchunhyang University 646 Eupnae-ri, Shinchang-myun, Asan-si, Choongnam 336-745 (Korea, Republic of)

    2012-10-15

    Introduction: The objective of this study was to evaluate associations between blood lead, cadmium, and mercury levels with estimated glomerular filtration rate in a general population of South Korean adults. Methods: This was a cross-sectional study based on data obtained in the Korean National Health and Nutrition Examination Survey (KNHANES) (2008-2010). The final analytical sample consisted of 5924 participants. Estimated glomerular filtration rate (eGFR) was calculated using the MDRD Study equation as an indicator of glomerular function. Results: In multiple linear regression analysis of log2-transformed blood lead as a continuous variable on eGFR, after adjusting for covariates including cadmium and mercury, the difference in eGFR levels associated with doubling of blood lead were -2.624 mL/min per 1.73 m Superscript-Two (95% CI: -3.803 to -1.445). In multiple linear regression analysis using quartiles of blood lead as the independent variable, the difference in eGFR levels comparing participants in the highest versus the lowest quartiles of blood lead was -3.835 mL/min per 1.73 m Superscript-Two (95% CI: -5.730 to -1.939). In a multiple linear regression analysis using blood cadmium and mercury, as continuous or categorical variables, as independent variables, neither metal was a significant predictor of eGFR. Odds ratios (ORs) and 95% CI values for reduced eGFR calculated for log2-transformed blood metals and quartiles of the three metals showed similar trends after adjustment for covariates. Discussion: In this large, representative sample of South Korean adults, elevated blood lead level was consistently associated with lower eGFR levels and with the prevalence of reduced eGFR even in blood lead levels below 10 {mu}g/dL. In conclusion, elevated blood lead level was associated with lower eGFR in a Korean general population, supporting the role of lead as a risk factor for chronic kidney disease.

  14. Conjoined legs: Sirenomelia or caudal regression syndrome?

    Directory of Open Access Journals (Sweden)

    Sakti Prasad Das

    2013-01-01

    Full Text Available Presence of single umbilical persistent vitelline artery distinguishes sirenomelia from caudal regression syndrome. We report a case of a12-year-old boy who had bilateral umbilical arteries presented with fusion of both legs in the lower one third of leg. Both feet were rudimentary. The right foot had a valgus rocker-bottom deformity. All toes were present but rudimentary. The left foot showed absence of all toes. Physical examination showed left tibia vara. The chest evaluation in sitting revealed pigeon chest and elevated right shoulder. Posterior examination of the trunk showed thoracic scoliosis with convexity to right. The patient was operated and at 1 year followup the boy had two separate legs with a good aesthetic and functional results.

  15. Conjoined legs: Sirenomelia or caudal regression syndrome?

    Science.gov (United States)

    Das, Sakti Prasad; Ojha, Niranjan; Ganesh, G Shankar; Mohanty, Ram Narayan

    2013-07-01

    Presence of single umbilical persistent vitelline artery distinguishes sirenomelia from caudal regression syndrome. We report a case of a12-year-old boy who had bilateral umbilical arteries presented with fusion of both legs in the lower one third of leg. Both feet were rudimentary. The right foot had a valgus rocker-bottom deformity. All toes were present but rudimentary. The left foot showed absence of all toes. Physical examination showed left tibia vara. The chest evaluation in sitting revealed pigeon chest and elevated right shoulder. Posterior examination of the trunk showed thoracic scoliosis with convexity to right. The patient was operated and at 1 year followup the boy had two separate legs with a good aesthetic and functional results.

  16. Learning and Study Strategies Inventory subtests and factors as predictors of National Board of Chiropractic Examiners Part 1 examination performance.

    Science.gov (United States)

    Schutz, Christine M; Dalton, Leanne; Tepe, Rodger E

    2013-01-01

    This study was designed to extend research on the relationship between chiropractic students' learning and study strategies and national board examination performance. Sixty-nine first trimester chiropractic students self-administered the Learning and Study Strategies Inventory (LASSI). Linear trends tests (for continuous variables) and Mantel-Haenszel trend tests (for categorical variables) were utilized to determine if the 10 LASSI subtests and 3 factors predicted low, medium and high levels of National Board of Chiropractic Examiners (NBCE) Part 1 scores. Multiple regression was performed to predict overall mean NBCE examination scores using the 3 LASSI factors as predictor variables. Four LASSI subtests (Anxiety, Concentration, Selecting Main Ideas, Test Strategies) and one factor (Goal Orientation) were significantly associated with NBCE examination levels. One factor (Goal Orientation) was a significant predictor of overall mean NBCE examination performance. Learning and study strategies are predictive of NBCE Part 1 examination performance in chiropractic students. The current study found LASSI subtests Anxiety, Concentration, Selecting Main Ideas, and Test Strategies, and the Goal-Orientation factor to be significant predictors of NBCE scores. The LASSI may be useful to educators in preparing students for academic success. Further research is warranted to explore the effects of learning and study strategies training on GPA and NBCE performance.

  17. A longitudinal examination of factors predicting anxiety during the transition to middle school

    Science.gov (United States)

    Grills-Taquechel, Amie E.; Norton, Peter; Ollendick, Thomas H.

    2010-01-01

    The transition from elementary to middle or junior high school is commonly regarded as a period of stress and turmoil for young adolescents, and has been associated with changes in anxiety and other psychological problems. However, less is known about risk and resilience factors that may predict these changes. This study examined changes in anxiety, as well as predictors of these changes among 77, predominantly Caucasian (88%), male and female (52%) adolescents from Grades 6 to 8. Repeated measures analysis of variance was conducted to examine the predicted grade and gender differences. Multiple regression analyses were conducted to examine the prediction of eighth grade anxiety symptoms by sixth grade self-worth, perceived social acceptance, and social support, as well as the potential moderating role of gender in these relations. Results suggested a significant decrease in anxiety, particularly social anxiety, over this period for boys but not girls. Examination of predictors of changes in anxiety suggested that, in general, global self-worth, social acceptance, and gender were each associated with overall and social anxiety. Findings are integrated with extant literature on developmental changes associated with anxiety and school transitions and clinical implications of these findings are discussed. PMID:20711893

  18. An introduction to using Bayesian linear regression with clinical data.

    Science.gov (United States)

    Baldwin, Scott A; Larson, Michael J

    2017-11-01

    Statistical training psychology focuses on frequentist methods. Bayesian methods are an alternative to standard frequentist methods. This article provides researchers with an introduction to fundamental ideas in Bayesian modeling. We use data from an electroencephalogram (EEG) and anxiety study to illustrate Bayesian models. Specifically, the models examine the relationship between error-related negativity (ERN), a particular event-related potential, and trait anxiety. Methodological topics covered include: how to set up a regression model in a Bayesian framework, specifying priors, examining convergence of the model, visualizing and interpreting posterior distributions, interval estimates, expected and predicted values, and model comparison tools. We also discuss situations where Bayesian methods can outperform frequentist methods as well has how to specify more complicated regression models. Finally, we conclude with recommendations about reporting guidelines for those using Bayesian methods in their own research. We provide data and R code for replicating our analyses. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Regression dilution bias: tools for correction methods and sample size calculation.

    Science.gov (United States)

    Berglund, Lars

    2012-08-01

    Random errors in measurement of a risk factor will introduce downward bias of an estimated association to a disease or a disease marker. This phenomenon is called regression dilution bias. A bias correction may be made with data from a validity study or a reliability study. In this article we give a non-technical description of designs of reliability studies with emphasis on selection of individuals for a repeated measurement, assumptions of measurement error models, and correction methods for the slope in a simple linear regression model where the dependent variable is a continuous variable. Also, we describe situations where correction for regression dilution bias is not appropriate. The methods are illustrated with the association between insulin sensitivity measured with the euglycaemic insulin clamp technique and fasting insulin, where measurement of the latter variable carries noticeable random error. We provide software tools for estimation of a corrected slope in a simple linear regression model assuming data for a continuous dependent variable and a continuous risk factor from a main study and an additional measurement of the risk factor in a reliability study. Also, we supply programs for estimation of the number of individuals needed in the reliability study and for choice of its design. Our conclusion is that correction for regression dilution bias is seldom applied in epidemiological studies. This may cause important effects of risk factors with large measurement errors to be neglected.

  20. Regression analysis of a chemical reaction fouling model

    International Nuclear Information System (INIS)

    Vasak, F.; Epstein, N.

    1996-01-01

    A previously reported mathematical model for the initial chemical reaction fouling of a heated tube is critically examined in the light of the experimental data for which it was developed. A regression analysis of the model with respect to that data shows that the reference point upon which the two adjustable parameters of the model were originally based was well chosen, albeit fortuitously. (author). 3 refs., 2 tabs., 2 figs

  1. Asymptotic theory for regressions with smoothly changing parameters

    DEFF Research Database (Denmark)

    Hillebrand, Eric; Medeiros, Marcelo; Xu, Junyue

    2013-01-01

    We derive asymptotic properties of the quasi maximum likelihood estimator of smooth transition regressions when time is the transition variable. The consistency of the estimator and its asymptotic distribution are examined. It is shown that the estimator converges at the usual pT-rate and has...... an asymptotically normal distribution. Finite sample properties of the estimator are explored in simulations. We illustrate with an application to US inflation and output data....

  2. Is one's usual dinner companion associated with greater odds of depression? Using data from the 2014 Korean National Health and Nutrition Examination Survey.

    Science.gov (United States)

    Lee, Sang Ah; Park, Eun-Cheol; Ju, Yeong Jun; Nam, Jin Young; Kim, Tae Hyun

    2016-09-01

    Support from one's family has been reported to have a positive effect on depression severity. Hence, family dinnertimes, when whole family can gather together, can be effective to depression by providing support from family. We investigate the association between the dinner companion and depression, and the differences in this association by gender, living arrangement and household composition. We used the Korea National Health and Nutrition Examination Survey 2014 data. A total of 4,181 individuals were included. We classified participants by their dinner companions as follows: dinner with family, dinner with others and eating alone. Depression was measured by using the 9-item Patient Health Questionnaire. Logistic regression analysis was used to investigate the association. Those who ate dinner alone (odds ratio (OR): 1.53, 95% confidence interval (CI): 1.04-2.25) had higher depression rate compared to those who had dinner with family. The subgroup analysis indicated that men, those who live with others and those living in a second-generation household who ate dinner alone had greater odds of having depressive symptoms. Those who usually eat dinner alone have greater odds of developing depression compared to those who have dinner with their family. As such, family dinnertimes may help to alleviate depressive moods. © The Author(s) 2016.

  3. Profile-driven regression for modeling and runtime optimization of mobile networks

    DEFF Research Database (Denmark)

    McClary, Dan; Syrotiuk, Violet; Kulahci, Murat

    2010-01-01

    Computer networks often display nonlinear behavior when examined over a wide range of operating conditions. There are few strategies available for modeling such behavior and optimizing such systems as they run. Profile-driven regression is developed and applied to modeling and runtime optimization...... of throughput in a mobile ad hoc network, a self-organizing collection of mobile wireless nodes without any fixed infrastructure. The intermediate models generated in profile-driven regression are used to fit an overall model of throughput, and are also used to optimize controllable factors at runtime. Unlike...

  4. Demonstration of a Fiber Optic Regression Probe

    Science.gov (United States)

    Korman, Valentin; Polzin, Kurt A.

    2010-01-01

    empirically anchoring any analysis geared towards lifetime qualification. Erosion rate data over an operating envelope could also be useful in the modeling detailed physical processes. The sensor has been embedded in many regressing media for the purposes of proof-of-concept testing. A gross demonstration of its capabilities was performed using a sanding wheel to remove layers of metal. A longer-term demonstration measurement involved the placement of the sensor in a brake pad, monitoring the removal of pad material associated with the normal wear-and-tear of driving. It was used to measure the regression rates of the combustable media in small model rocket motors and road flares. Finally, a test was performed using a sand blaster to remove small amounts of material at a time. This test was aimed at demonstrating the unit's present resolution, and is compared with laser profilometry data obtained simultaneously. At the lowest resolution levels, this unit should be useful in locally quantifying the erosion rates of the channel walls in plasma thrusters. .

  5. Association of individual and community factors with C-reactive protein and 25-hydroxyvitamin D: Evidence from the National Health and Nutrition Examination Survey (NHANES

    Directory of Open Access Journals (Sweden)

    Weiwen Chai

    2016-12-01

    Full Text Available Many individual and community/neighborhood factors may contribute to inflammation and vitamin D deficiency leading to the development of chronic diseases. This study examined the associations of serum C-reactive protein (CRP and 25-hydroxyvitamin D [25(OHD] levels with individual and community/neighborhood (tract-level or county-level factors using a nationally representative sample from 2001–2006 National Health and Nutrition Examination Survey (NHANES. Data from the 2001–2006 waves of the continuous NHANES was merged with the 2000 census and other neighborhood data sources constructed using geographic information system. Associations between multilevel factors and biomarker levels were assessed using multilevel random-intercept regression models. 6643 participants aged 19–65 (3402 men and 3241 women were included in the analysis. Family income-to-needs ratio was inversely associated with CRP (P=0.002 and positively associated with 25(OHD levels (P=0.0003. County crime rates were positively associated with CRP (P=0.007 and inversely associated with 25(OHD levels (P=0.0002. The associations with income-to-needs ratio were significant in men [CRP, P=0.005; 25(OHD, P=0.005] but not in women. For county crime rates, the association was only significant in women for CRP (P=0.004 and was significant in both men (P=0.01 and women (P=0.001 for 25(OHD. Additionally, overall CRP was positively associated with age (P<0.0001, female sex (P<0.0001, Hispanic race/ethnicity (P=0.0001, current smokers (P<0.0001, body mass index (BMI, P<0.0001, and participants who were US-born (P=0.02. Non-Hispanic black (P<0.0001 and Hispanic race/ethnicity (P<0.0001, current smoker (P=0.047, and higher BMI (P<0.0001 were associated with lower serum 25(OHD levels. No significant associations were observed between other community/neighborhood variables and serum CRP and 25(OHD levels. The current results suggest that family income-to-needs ratio and county crime rate may

  6. On the Occurrence of Standardized Regression Coefficients Greater than One.

    Science.gov (United States)

    Deegan, John, Jr.

    1978-01-01

    It is demonstrated here that standardized regression coefficients greater than one can legitimately occur. Furthermore, the relationship between the occurrence of such coefficients and the extent of multicollinearity present among the set of predictor variables in an equation is examined. Comments on the interpretation of these coefficients are…

  7. Pathways-driven sparse regression identifies pathways and genes associated with high-density lipoprotein cholesterol in two Asian cohorts.

    Directory of Open Access Journals (Sweden)

    Matt Silver

    2013-11-01

    Full Text Available Standard approaches to data analysis in genome-wide association studies (GWAS ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait's genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK

  8. Pathways-Driven Sparse Regression Identifies Pathways and Genes Associated with High-Density Lipoprotein Cholesterol in Two Asian Cohorts

    Science.gov (United States)

    Silver, Matt; Chen, Peng; Li, Ruoying; Cheng, Ching-Yu; Wong, Tien-Yin; Tai, E-Shyong; Teo, Yik-Ying; Montana, Giovanni

    2013-01-01

    Standard approaches to data analysis in genome-wide association studies (GWAS) ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs) or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait's genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK signalling and immune

  9. Common pitfalls in statistical analysis: Linear regression analysis

    Directory of Open Access Journals (Sweden)

    Rakesh Aggarwal

    2017-01-01

    Full Text Available In a previous article in this series, we explained correlation analysis which describes the strength of relationship between two continuous variables. In this article, we deal with linear regression analysis which predicts the value of one continuous variable from another. We also discuss the assumptions and pitfalls associated with this analysis.

  10. The Association between Stress Level in Daily Life and Age at Natural Menopause in Korean Women: Outcomes of the Korean National Health and Nutrition Examination Survey in 2010-2012.

    Science.gov (United States)

    Choi, Byoung-O; Lee, Yeon-Ji; Choi, Ji-Ho; Cho, Se-Wook; Im, Hyun-Jung; An, Jee-Eun

    2015-11-01

    Although several risk factors associated with reduced age at natural menopause (ANM) have been investigated, the results are inconsistent. Excessive stress, which leads to elevation of stress hormones, can also negatively affect reproductive ability, including by accelerating menopause. However, a direct association between stress level and ANM has not yet been demonstrated. Therefore, the object of this study was to investigate the association between stress level and ANM in Korean women. Study participants were Korean women between 40 and 70 years old who were in natural menopause during the 5th Korean National Health and Nutrition Examination Survey (n=3,176). The level of stress in daily life was estimated based on data from the mental health topics of the survey. We used the t-test and one-way analysis of variance to analyze the correlation between stress level and ANM. Regression (β) coefficients calculated by multiple regression analysis were used to estimate various factors affecting ANM. Women who experienced a high level of stress in daily life had a lower mean ANM than women with a low stress level (50.17±3.7 and 50.58±3.5 years, respectively), with a statistically significant correlation (Page, body mass index, menstrual regularity, and personal income (Page who are in natural menopause, there is a statistically significant correlation between stress level and ANM. In particular, women who experience a high level of stress in daily life have reduced ANM.

  11. Regression and regression analysis time series prediction modeling on climate data of quetta, pakistan

    International Nuclear Information System (INIS)

    Jafri, Y.Z.; Kamal, L.

    2007-01-01

    Various statistical techniques was used on five-year data from 1998-2002 of average humidity, rainfall, maximum and minimum temperatures, respectively. The relationships to regression analysis time series (RATS) were developed for determining the overall trend of these climate parameters on the basis of which forecast models can be corrected and modified. We computed the coefficient of determination as a measure of goodness of fit, to our polynomial regression analysis time series (PRATS). The correlation to multiple linear regression (MLR) and multiple linear regression analysis time series (MLRATS) were also developed for deciphering the interdependence of weather parameters. Spearman's rand correlation and Goldfeld-Quandt test were used to check the uniformity or non-uniformity of variances in our fit to polynomial regression (PR). The Breusch-Pagan test was applied to MLR and MLRATS, respectively which yielded homoscedasticity. We also employed Bartlett's test for homogeneity of variances on a five-year data of rainfall and humidity, respectively which showed that the variances in rainfall data were not homogenous while in case of humidity, were homogenous. Our results on regression and regression analysis time series show the best fit to prediction modeling on climatic data of Quetta, Pakistan. (author)

  12. Periodontitis in coronary heart disease patients: strong association between bleeding on probing and systemic biomarkers.

    Science.gov (United States)

    Bokhari, Syed Akhtar H; Khan, Ayyaz A; Butt, Arshad K; Hanif, Mohammad; Izhar, Mateen; Tatakis, Dimitris N; Ashfaq, Mohammad

    2014-11-01

    Few studies have examined the relationship of individual periodontal parameters with individual systemic biomarkers. This study assessed the possible association between specific clinical parameters of periodontitis and systemic biomarkers of coronary heart disease risk in coronary heart disease patients with periodontitis. Angiographically proven coronary heart disease patients with periodontitis (n = 317), aged >30 years and without other systemic illness were examined. Periodontal clinical parameters of bleeding on probing (BOP), probing depth (PD), and clinical attachment level (CAL) and systemic levels of high-sensitivity C-reactive protein (CRP), fibrinogen (FIB) and white blood cells (WBC) were noted and analyzed to identify associations through linear and stepwise multiple regression analyses. Unadjusted linear regression showed significant associations between periodontal and systemic parameters; the strongest association (r = 0.629; p periodontal and systemic inflammation marker, respectively. Stepwise regression analysis models revealed that BOP was a predictor of systemic CRP levels (p periodontal parameter significantly associated with each systemic parameter (CRP, FIB, and WBC). In coronary heart disease patients with periodontitis, BOP is strongly associated with systemic CRP levels; this association possibly reflects the potential significance of the local periodontal inflammatory burden for systemic inflammation. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  13. Linear regression in astronomy. I

    Science.gov (United States)

    Isobe, Takashi; Feigelson, Eric D.; Akritas, Michael G.; Babu, Gutti Jogesh

    1990-01-01

    Five methods for obtaining linear regression fits to bivariate data with unknown or insignificant measurement errors are discussed: ordinary least-squares (OLS) regression of Y on X, OLS regression of X on Y, the bisector of the two OLS lines, orthogonal regression, and 'reduced major-axis' regression. These methods have been used by various researchers in observational astronomy, most importantly in cosmic distance scale applications. Formulas for calculating the slope and intercept coefficients and their uncertainties are given for all the methods, including a new general form of the OLS variance estimates. The accuracy of the formulas was confirmed using numerical simulations. The applicability of the procedures is discussed with respect to their mathematical properties, the nature of the astronomical data under consideration, and the scientific purpose of the regression. It is found that, for problems needing symmetrical treatment of the variables, the OLS bisector performs significantly better than orthogonal or reduced major-axis regression.

  14. Diet Quality Associated with Total Sodium Intake among US Adults Aged ≥18 Years—National Health and Nutrition Examination Survey, 2009–2012

    Directory of Open Access Journals (Sweden)

    Carla I. Mercado

    2017-10-01

    Full Text Available Diet quality or macronutrient composition of total daily sodium intake (dNa <2300 mg/day in the United States (US is unknown. Using data from 2011–2014 NHANES (National Health and Nutrition Examination Survey, we examined 24-h dietary recalls (n = 10,142 from adults aged ≥18 years and investigated how diet composition and quality are associated with dNa. Diet quality was assessed using components of macronutrients and Healthy Eating Index 2010 (HEI-2010. Associations were tested using linear regression analysis adjusted for total energy (kcal, age, gender, and race/ethnicity. One-day dNa in the lower quartiles were more likely reported among women, older adults (≥65 years old, and lower quartiles of total energy (kcal (p-values ≤ 0.001. With increasing dNa, there was an increase in the mean protein, fiber, and total fat densities, while total carbohydrates densities decreased. As dNa increased, meat protein, refined grains, dairy, and total vegetables, greens and beans densities increased; while total fruit and whole fruit densities decreased. Modified HEI-2010 total score (total score without sodium component increased as dNa increased (adjusted coefficient: 0.11, 95% confidence interval = 0.07, 0.15. Although diet quality, based on modified HEI-2010 total score, increased on days with greater dNa, there is much room for improvement with mean diet quality of about half of the optimal level.

  15. Sarcopenia Is Independently Associated with Cardiovascular Disease in Older Korean Adults: The Korea National Health and Nutrition Examination Survey (KNHANES) from 2009

    Science.gov (United States)

    Chin, Sang Ouk; Rhee, Sang Youl; Chon, Suk; Hwang, You-Cheol; Jeong, In-Kyung; Oh, Seungjoon; Ahn, Kyu Jeung; Chung, Ho Yeon; Woo, Jeong-taek; Kim, Sung-Woon; Kim, Jin-Woo; Kim, Young Seol; Ahn, Hong-Yup

    2013-01-01

    Background The association between sarcopenia and cardiovascular disease (CVD) in elderly people has not been adequately assessed. The aim of this study was to investigate whether CVD is more prevalent in subjects with sarcopenia independent of other well-established cardiovascular risk factors in older Korean adults. Method This study utilized the representative Korean population data from the Korea National Health and Nutrition Examination Survey (KNHANES) which was conducted in 2009. Subjects older than 65 years of age with appendicular skeletal muscle mass (ASM) determined by dual energy X-ray absorptiometry were selected. The prevalence of sarcopenia in the older Korean adults was investigated, and it was determined whether sarcopenia is associated with CVD independent of other well-known risk factors. Results 1,578 subjects aged 65 years and older with the data for ASM were selected, and the overall prevalence of sarcopenia was 30.3% in men and 29.3% in women. Most of the risk factors for CVD such as age, waist circumference, body mass index, fasting plasma glucose and total cholesterol showed significant negative correlations with the ratio between appendicular skeletal muscle mass and body weight. Multiple logistic regression analysis demonstrated that sarcopenia was associated with CVD independent of other well-documented risk factors, renal function and medications (OR, 1.768; 95% CI, 1.075–2.909, P = 0.025). Conclusions Sarcopenia was associated with the presence of CVD independent of other cardiovascular risk factors after adjusting renal function and medications. PMID:23533671

  16. Sarcopenia is independently associated with cardiovascular disease in older Korean adults: the Korea National Health and Nutrition Examination Survey (KNHANES from 2009.

    Directory of Open Access Journals (Sweden)

    Sang Ouk Chin

    Full Text Available BACKGROUND: The association between sarcopenia and cardiovascular disease (CVD in elderly people has not been adequately assessed. The aim of this study was to investigate whether CVD is more prevalent in subjects with sarcopenia independent of other well-established cardiovascular risk factors in older Korean adults. METHOD: This study utilized the representative Korean population data from the Korea National Health and Nutrition Examination Survey (KNHANES which was conducted in 2009. Subjects older than 65 years of age with appendicular skeletal muscle mass (ASM determined by dual energy X-ray absorptiometry were selected. The prevalence of sarcopenia in the older Korean adults was investigated, and it was determined whether sarcopenia is associated with CVD independent of other well-known risk factors. RESULTS: 1,578 subjects aged 65 years and older with the data for ASM were selected, and the overall prevalence of sarcopenia was 30.3% in men and 29.3% in women. Most of the risk factors for CVD such as age, waist circumference, body mass index, fasting plasma glucose and total cholesterol showed significant negative correlations with the ratio between appendicular skeletal muscle mass and body weight. Multiple logistic regression analysis demonstrated that sarcopenia was associated with CVD independent of other well-documented risk factors, renal function and medications (OR, 1.768; 95% CI, 1.075-2.909, P = 0.025. CONCLUSIONS: Sarcopenia was associated with the presence of CVD independent of other cardiovascular risk factors after adjusting renal function and medications.

  17. The association between long working hours and the metabolic syndrome: evidences from the 5th Korean National Health and Nutrition Examination Survey of 2010 and 2012.

    Science.gov (United States)

    Jeong, Jae Uk; Jeon, Man Joong; Sakong, Joon

    2014-01-01

    This study was conducted in order to evaluate the association between the working hours of Korean employees and the metabolic syndrome and the effects of long working hours on metabolic syndrome based on the 5th Korean National Health and Nutrition Examination Survey (2010-2012). Based on the 5th Korean National Health and Nutrition Examination Survey (2010-2012), 4,456 Korean employees without shift work, aged over 15, who work 30 hours or more per week were targeted in this study. The association between the general characteristics, including age, smoking, alcohol drinking, exercise, and the metabolic syndrome criteria defined by International Diabetes Federation (IDF) and weekly working hours were analyzed. In addition, the association between weekly working hours and the metabolic syndrome of the subjects stratified by gender was analyzed through multiple logistic regression analyses and generalized linear mixed model after adjusting the general characteristics. In the results of stratified analysis by gender, in male subjects, in comparison with the 30-39 weekly working hours group, there were no significant adjusted odds ratios to the other working hours groups. In female subjects, in comparison with the 30-39 weekly working hours group, there were no significant adjusted odds ratios to the other working hours groups. In addition, no trend associations were observed among weekly working hour groups in both stratified genders. No significant differences in prevalence of metabolic syndrome of the subjects stratified by gender were found according to weekly increasing working hours. However, due to some limitations of this study, further prospective studies may be necessary for verification.

  18. Where are weather-suicide associations valid? An examination of nine US counties with varying seasonality

    Science.gov (United States)

    Dixon, P. Grady; Kalkstein, Adam J.

    2018-05-01

    There has been much research on the associations between weather variables and suicide rates. However, the state of understanding has remained rather stagnant due to many contradictory findings. The purpose of this project is to examine a larger database of suicides that includes a longer and more recent period of record (1975-2010) across numerous locations in the USA. In all, we examine nine total counties (and the primary city associated with them) with a special effort made to compare locations with varying degrees of temperature seasonality: Cook (Chicago), Fulton (Atlanta), King (Seattle), Los Angeles (Los Angeles), Maricopa (Phoenix), Miami-Dade (Miami), Philadelphia (Philadelphia), Salt Lake (Salt Lake City), and St. Louis (St. Louis). We first examine the unique seasonal cycle in suicides evident in each locale and then use distributed lag nonlinear modeling (DLNM) to relate the suicide data to daily surface temperatures. Results suggest that a late spring/summer peak generally exists in suicide rates, and above average temperatures are associated with increased suicide risk in almost all study counties. Further, it appears that these associations can be found in both mid-latitude and sub-tropical climate types.

  19. Stochastic search, optimization and regression with energy applications

    Science.gov (United States)

    Hannah, Lauren A.

    Designing clean energy systems will be an important task over the next few decades. One of the major roadblocks is a lack of mathematical tools to economically evaluate those energy systems. However, solutions to these mathematical problems are also of interest to the operations research and statistical communities in general. This thesis studies three problems that are of interest to the energy community itself or provide support for solution methods: R&D portfolio optimization, nonparametric regression and stochastic search with an observable state variable. First, we consider the one stage R&D portfolio optimization problem to avoid the sequential decision process associated with the multi-stage. The one stage problem is still difficult because of a non-convex, combinatorial decision space and a non-convex objective function. We propose a heuristic solution method that uses marginal project values---which depend on the selected portfolio---to create a linear objective function. In conjunction with the 0-1 decision space, this new problem can be solved as a knapsack linear program. This method scales well to large decision spaces. We also propose an alternate, provably convergent algorithm that does not exploit problem structure. These methods are compared on a solid oxide fuel cell R&D portfolio problem. Next, we propose Dirichlet Process mixtures of Generalized Linear Models (DPGLM), a new method of nonparametric regression that accommodates continuous and categorical inputs, and responses that can be modeled by a generalized linear model. We prove conditions for the asymptotic unbiasedness of the DP-GLM regression mean function estimate. We also give examples for when those conditions hold, including models for compactly supported continuous distributions and a model with continuous covariates and categorical response. We empirically analyze the properties of the DP-GLM and why it provides better results than existing Dirichlet process mixture regression

  20. Correlation of the National Board of Medical Examiners Emergency Medicine Advanced Clinical Examination Given in July to Intern American Board of Emergency Medicine in-training Examination Scores: A Predictor of Performance?

    Science.gov (United States)

    Hiller, Katherine; Franzen, Doug; Heitz, Corey; Emery, Matthew; Poznanski, Stacy

    2015-11-01

    There is great variation in the knowledge base of Emergency Medicine (EM) interns in July. The first objective knowledge assessment during residency does not occur until eight months later, in February, when the American Board of EM (ABEM) administers the in-training examination (ITE). In 2013, the National Board of Medical Examiners (NBME) released the EM Advanced Clinical Examination (EM-ACE), an assessment intended for fourth-year medical students. Administration of the EM-ACE to interns at the start of residency may provide an earlier opportunity to assess the new EM residents' knowledge base. The primary objective of this study was to determine the correlation of the NBME EM-ACE, given early in residency, with the EM ITE. Secondary objectives included determination of the correlation of the United States Medical Licensing Examination (USMLE) Step 1 or 2 scores with early intern EM-ACE and ITE scores and the effect, if any, of clinical EM experience on examination correlation. This was a multi-institutional, observational study. Entering EM interns at six residencies took the EM-ACE in July 2013 and the ABEM ITE in February 2014. We collected scores for the EM-ACE and ITE, age, gender, weeks of clinical EM experience in residency prior to the ITE, and USMLE Step 1 and 2 scores. Pearson's correlation and linear regression were performed. Sixty-two interns took the EM-ACE and the ITE. The Pearson's correlation coefficient between the ITE and the EM-ACE was 0.62. R-squared was 0.5 (adjusted 0.4). The coefficient of determination was 0.41 (95% CI [0.3-0.8]). For every increase of one in the scaled EM-ACE score, we observed a 0.4% increase in the EM in-training score. In a linear regression model using all available variables (EM-ACE, gender, age, clinical exposure to EM, and USMLE Step 1 and Step 2 scores), only the EM-ACE score was significantly associated with the ITE (pcorrelation with ITE. Clinical EM experience prior to the in-training exam did not affect the

  1. Combining Alphas via Bounded Regression

    Directory of Open Access Journals (Sweden)

    Zura Kakushadze

    2015-11-01

    Full Text Available We give an explicit algorithm and source code for combining alpha streams via bounded regression. In practical applications, typically, there is insufficient history to compute a sample covariance matrix (SCM for a large number of alphas. To compute alpha allocation weights, one then resorts to (weighted regression over SCM principal components. Regression often produces alpha weights with insufficient diversification and/or skewed distribution against, e.g., turnover. This can be rectified by imposing bounds on alpha weights within the regression procedure. Bounded regression can also be applied to stock and other asset portfolio construction. We discuss illustrative examples.

  2. Accuracy of Bayes and Logistic Regression Subscale Probabilities for Educational and Certification Tests

    Science.gov (United States)

    Rudner, Lawrence

    2016-01-01

    In the machine learning literature, it is commonly accepted as fact that as calibration sample sizes increase, Naïve Bayes classifiers initially outperform Logistic Regression classifiers in terms of classification accuracy. Applied to subtests from an on-line final examination and from a highly regarded certification examination, this study shows…

  3. Bayesian approach to errors-in-variables in regression models

    Science.gov (United States)

    Rozliman, Nur Aainaa; Ibrahim, Adriana Irawati Nur; Yunus, Rossita Mohammad

    2017-05-01

    In many applications and experiments, data sets are often contaminated with error or mismeasured covariates. When at least one of the covariates in a model is measured with error, Errors-in-Variables (EIV) model can be used. Measurement error, when not corrected, would cause misleading statistical inferences and analysis. Therefore, our goal is to examine the relationship of the outcome variable and the unobserved exposure variable given the observed mismeasured surrogate by applying the Bayesian formulation to the EIV model. We shall extend the flexible parametric method proposed by Hossain and Gustafson (2009) to another nonlinear regression model which is the Poisson regression model. We shall then illustrate the application of this approach via a simulation study using Markov chain Monte Carlo sampling methods.

  4. Cross-sectional associations of active transport, employment status and objectively measured physical activity: analyses from the National Health and Nutrition Examination Survey.

    Science.gov (United States)

    Yang, Lin; Hu, Liang; Hipp, J Aaron; Imm, Kellie R; Schutte, Rudolph; Stubbs, Brendon; Colditz, Graham A; Smith, Lee

    2018-05-05

    To investigate associations between active transport, employment status and objectively measured moderate-to-vigorous physical activity (MVPA) in a representative sample of US adults. Cross-sectional analyses of data from the National Health and Nutrition Examination Survey. A total of 5180 adults (50.2 years old, 49.0% men) were classified by levels of active transportation and employment status. Outcome measure was weekly time spent in MVPA as recorded by the Actigraph accelerometer. Associations between active transport, employment status and objectively measured MVPA were examined using multivariable linear regression models adjusted for age, body mass index, race and ethnicity, education level, marital status, smoking status, working hour duration (among the employed only) and self-reported leisure time physical activity. Patterns of active transport were similar between the employed (n=2897) and unemployed (n=2283), such that 76.0% employed and 77.5% unemployed engaged in no active transport. For employed adults, those engaging in high levels of active transport (≥90 min/week) had higher amount of MVPA than those who did not engage in active transport. This translated to 40.8 (95% CI 15.7 to 65.9) additional minutes MVPA per week in men and 57.9 (95% CI 32.1 to 83.7) additional minutes MVPA per week in women. Among the unemployed adults, higher levels of active transport were associated with more MVPA among men (44.8 min/week MVPA, 95% CI 9.2 to 80.5) only. Findings from the present study support interventions to promote active transport to increase population level physical activity. Additional strategies are likely required to promote physical activity among unemployed women. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  5. Fraternity Membership and Sexual Aggression: An Examination of Mediators of the Association

    Science.gov (United States)

    Kingree, Jeffrey B.; Thompson, Martie P.

    2013-01-01

    Objective: This prospective study examined attitudes (ie, hostility toward women, acceptance of rape myths), peer influences (ie, peer pressure to have sex, peer approval of forced sex), and risky behaviors (ie, high-risk alcohol use, number of sexual partners) as possible mediators of the association between fraternity membership and sexual…

  6. Informant Effects on Behavioral and Academic Associations: A Latent Variable Longitudinal Examination

    Science.gov (United States)

    Konold, Timothy R.; Shukla, Kathan D.

    2014-01-01

    Discrepancies among informants' ratings of a given child's behavior complicate the study of linkages between child behavior and academic achievement. In the current study, we examined the potential moderating effect of informant type on associations between behavior and two types of achievement in a longitudinal growth model that…

  7. riskRegression

    DEFF Research Database (Denmark)

    Ozenne, Brice; Sørensen, Anne Lyngholm; Scheike, Thomas

    2017-01-01

    In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interface...... for predicting the covariate specific absolute risks, their confidence intervals, and their confidence bands based on right censored time to event data. We provide explicit formulas for our implementation of the estimator of the (stratified) baseline hazard function in the presence of tied event times. As a by...... functionals. The software presented here is implemented in the riskRegression package....

  8. A Skew-t space-varying regression model for the spectral analysis of resting state brain activity.

    Science.gov (United States)

    Ismail, Salimah; Sun, Wenqi; Nathoo, Farouk S; Babul, Arif; Moiseev, Alexader; Beg, Mirza Faisal; Virji-Babul, Naznin

    2013-08-01

    It is known that in many neurological disorders such as Down syndrome, main brain rhythms shift their frequencies slightly, and characterizing the spatial distribution of these shifts is of interest. This article reports on the development of a Skew-t mixed model for the spatial analysis of resting state brain activity in healthy controls and individuals with Down syndrome. Time series of oscillatory brain activity are recorded using magnetoencephalography, and spectral summaries are examined at multiple sensor locations across the scalp. We focus on the mean frequency of the power spectral density, and use space-varying regression to examine associations with age, gender and Down syndrome across several scalp regions. Spatial smoothing priors are incorporated based on a multivariate Markov random field, and the markedly non-Gaussian nature of the spectral response variable is accommodated by the use of a Skew-t distribution. A range of models representing different assumptions on the association structure and response distribution are examined, and we conduct model selection using the deviance information criterion. (1) Our analysis suggests region-specific differences between healthy controls and individuals with Down syndrome, particularly in the left and right temporal regions, and produces smoothed maps indicating the scalp topography of the estimated differences.

  9. Regression of electrocardiographic left ventricular hypertrophy or strain is associated with lower incidence of cardiovascular morbidity and mortality in hypertensive patients independent of blood pressure reduction - A LIFE review.

    Science.gov (United States)

    Bang, Casper N; Devereux, Richard B; Okin, Peter M

    2014-01-01

    Cornell product criteria, Sokolow-Lyon voltage criteria and electrocardiographic (ECG) strain (secondary ST-T abnormalities) are markers for left ventricular hypertrophy (LVH) and adverse prognosis in population studies. However, the relationship of regression of ECG LVH and strain during antihypertensive therapy to cardiovascular (CV) risk was unclear before the Losartan Intervention for Endpoint Reduction in Hypertension (LIFE) study. We reviewed findings on ECG LVH regression and strain over time in 9193 hypertensive patients with ECG LVH at baseline enrolled in the LIFE study. The composite endpoint of CV death, nonfatal MI, or stroke occurred in 1096 patients during 4.8±0.9years follow-up. In Cox multivariable models adjusting for randomized treatment, known risk factors including in-treatment blood pressure, and for severity ECG LVH by Cornell product and Sokolow-Lyon voltage, baseline ECG strain was associated with a 33% higher risk of the LIFE composite endpoint (HR. 1.33, 95% CI [1.11-1.59]). Development of new ECG strain between baseline and year-1 was associated with a 2-fold increased risk of the composite endpoint (HR. 2.05, 95% CI [1.51-2.78]), whereas the risk associated with regression or persistence of ECG strain was attenuated and no longer statistically significant (both p>0.05). After controlling for treatment with losartan or atenolol, for baseline Framingham risk score, Cornell product, and Sokolow-Lyon voltage, and for baseline and in-treatment systolic and diastolic blood pressure, 1 standard deviation (SD) lower in-treatment Cornell product was associated with a 14.5% decrease in the composite endpoint (HR. 0.86, 95% CI [0.82-0.90]). In a parallel analysis, 1 SD lower in-treatment Sokolow-Lyon voltage was associated with a 16.6% decrease in the composite endpoint (HR. 0.83, 95% CI [0.78-0.88]). The LIFE study shows that evaluation of both baseline and in-study ECG LVH defined by Cornell product criteria, Sokolow-Lyon voltage criteria or

  10. Associations of blood lead, cadmium, and mercury with estimated glomerular filtration rate in the Korean general population: Analysis of 2008–2010 Korean National Health and Nutrition Examination Survey data

    International Nuclear Information System (INIS)

    Kim, Yangho; Lee, Byung-Kook

    2012-01-01

    Introduction: The objective of this study was to evaluate associations between blood lead, cadmium, and mercury levels with estimated glomerular filtration rate in a general population of South Korean adults. Methods: This was a cross-sectional study based on data obtained in the Korean National Health and Nutrition Examination Survey (KNHANES) (2008–2010). The final analytical sample consisted of 5924 participants. Estimated glomerular filtration rate (eGFR) was calculated using the MDRD Study equation as an indicator of glomerular function. Results: In multiple linear regression analysis of log2-transformed blood lead as a continuous variable on eGFR, after adjusting for covariates including cadmium and mercury, the difference in eGFR levels associated with doubling of blood lead were −2.624 mL/min per 1.73 m² (95% CI: −3.803 to −1.445). In multiple linear regression analysis using quartiles of blood lead as the independent variable, the difference in eGFR levels comparing participants in the highest versus the lowest quartiles of blood lead was −3.835 mL/min per 1.73 m² (95% CI: −5.730 to −1.939). In a multiple linear regression analysis using blood cadmium and mercury, as continuous or categorical variables, as independent variables, neither metal was a significant predictor of eGFR. Odds ratios (ORs) and 95% CI values for reduced eGFR calculated for log2-transformed blood metals and quartiles of the three metals showed similar trends after adjustment for covariates. Discussion: In this large, representative sample of South Korean adults, elevated blood lead level was consistently associated with lower eGFR levels and with the prevalence of reduced eGFR even in blood lead levels below 10 μg/dL. In conclusion, elevated blood lead level was associated with lower eGFR in a Korean general population, supporting the role of lead as a risk factor for chronic kidney disease.

  11. Sparse Regression by Projection and Sparse Discriminant Analysis

    KAUST Repository

    Qi, Xin

    2015-04-03

    © 2015, © American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America. Recent years have seen active developments of various penalized regression methods, such as LASSO and elastic net, to analyze high-dimensional data. In these approaches, the direction and length of the regression coefficients are determined simultaneously. Due to the introduction of penalties, the length of the estimates can be far from being optimal for accurate predictions. We introduce a new framework, regression by projection, and its sparse version to analyze high-dimensional data. The unique nature of this framework is that the directions of the regression coefficients are inferred first, and the lengths and the tuning parameters are determined by a cross-validation procedure to achieve the largest prediction accuracy. We provide a theoretical result for simultaneous model selection consistency and parameter estimation consistency of our method in high dimension. This new framework is then generalized such that it can be applied to principal components analysis, partial least squares, and canonical correlation analysis. We also adapt this framework for discriminant analysis. Compared with the existing methods, where there is relatively little control of the dependency among the sparse components, our method can control the relationships among the components. We present efficient algorithms and related theory for solving the sparse regression by projection problem. Based on extensive simulations and real data analysis, we demonstrate that our method achieves good predictive performance and variable selection in the regression setting, and the ability to control relationships between the sparse components leads to more accurate classification. In supplementary materials available online, the details of the algorithms and theoretical proofs, and R codes for all simulation studies are provided.

  12. Composite marginal quantile regression analysis for longitudinal adolescent body mass index data.

    Science.gov (United States)

    Yang, Chi-Chuan; Chen, Yi-Hau; Chang, Hsing-Yi

    2017-09-20

    Childhood and adolescenthood overweight or obesity, which may be quantified through the body mass index (BMI), is strongly associated with adult obesity and other health problems. Motivated by the child and adolescent behaviors in long-term evolution (CABLE) study, we are interested in individual, family, and school factors associated with marginal quantiles of longitudinal adolescent BMI values. We propose a new method for composite marginal quantile regression analysis for longitudinal outcome data, which performs marginal quantile regressions at multiple quantile levels simultaneously. The proposed method extends the quantile regression coefficient modeling method introduced by Frumento and Bottai (Biometrics 2016; 72:74-84) to longitudinal data accounting suitably for the correlation structure in longitudinal observations. A goodness-of-fit test for the proposed modeling is also developed. Simulation results show that the proposed method can be much more efficient than the analysis without taking correlation into account and the analysis performing separate quantile regressions at different quantile levels. The application to the longitudinal adolescent BMI data from the CABLE study demonstrates the practical utility of our proposal. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  13. Asymptotic Theory for Regressions with Smoothly Changing Parameters

    DEFF Research Database (Denmark)

    Hillebrand, Eric Tobias; Medeiros, Marcelo C.; Xu, Junyue

    We derive asymptotic properties of the quasi maximum likelihood estimator of smooth transition regressions when time is the transition variable. The consistency of the estimator and its asymptotic distribution are examined. It is shown that the estimator converges at the usual square-root-of-T rate...... and has an asymptotically normal distribution. Finite sample properties of the estimator are explored in simulations. We illustrate with an application to US inflation and output data....

  14. Association of Individual and Neighborhood Factors with Home Food Availability: Evidence from the National Health and Nutrition Examination Survey.

    Science.gov (United States)

    Chai, Weiwen; Fan, Jessie X; Wen, Ming

    2018-05-01

    Accumulating evidence suggests the important role of the home food environment in an individual's dietary intake. This study examined the associations of individual and neighborhood-level factors with the availability of healthy and unhealthy foods in the home using a nationally representative sample from the 2007 to 2008 and 2009 to 2010 National Health and Nutrition Examination Surveys (NHANES). A cross-sectional study design was used with NHANES merged with the 2000 census data. Food availability was measured through self-report questionnaire regarding the frequency of foods or drinks available in the home. The analysis included 8,975 participants aged 19 to 65 years. Associations of individual and neighborhood factors with home food availability (always or most of the time available) were assessed using logistic regression modeling accounting for NHANES' complex survey design and weights. Individual-level and neighborhood-level factors were simultaneously included in the analysis. Family income-to-needs ratio was positively associated with the availability of dark green vegetables (odds ratio [OR]=1.07; 95% CI=1.00 to 1.13), fat-free or low-fat milk (OR=1.16; 95% CI=1.07 to 1.25), and salty snacks (OR=1.12; 95% CI=1.04 to 1.20) in the home. College graduates were more likely to have fruits (OR=1.96, 95% CI=1.48 to 2.60), vegetables (OR=1.48; 95% CI=1.16 to 1.88), and fat-free or low-fat milk (OR=1.81; 95% CI=1.55 to 2.12) and less likely to have salty snacks (OR=0.77; 95% CI=0.63 to 0.95) and sugary drinks (OR=0.46, 95% CI=0.37 to 0.57) available compared with non-college graduates. Tract socioeconomic status (SES) scores were positively associated with fruit (OR=1.15; 95% CI=1.02 to 1.29), vegetable (OR=1.14; 95% CI=1.03 to 1.26), and fat-free or low-fat milk (OR=1.25; 95% CI=1.10 to 1.42) availability. Urban residents were associated with greater availability of fruits (OR=1.47; 95% CI=1.05 to 2.08) and fat-free or low-fat milk (OR=1.33; 95% CI=1.02 to 1

  15. Shift Work Is Associated with Metabolic Syndrome in Young Female Korean Workers

    OpenAIRE

    Yu, Kyoung Hwa; Yi, Yu Hyeon; Kim, Yun Jin; Cho, Byung Mann; Lee, Sang Yeoup; Lee, Jeong Gyu; Jeong, Dong Wook; Ji, So Yeon

    2017-01-01

    Background Shift work is associated with health problems, including metabolic syndrome. This study investigated the association between shift work and metabolic syndrome in young workers. Methods A total of 3,317 subjects aged 20?40 years enrolled in the 2011?2012 Korean National Health and Nutrition Examination Survey were divided into shift and day workers. We conducted a cross-sectional study and calculated odds ratios using multivariate logistic regression analysis in order to examine the...

  16. A Methodological Approach to Assessing the Health Impact of Environmental Chemical Mixtures: PCBs and Hypertension in the National Health and Nutrition Examination Survey

    Directory of Open Access Journals (Sweden)

    Paul White

    2011-11-01

    Full Text Available We describe an approach to examine the association between exposure to chemical mixtures and a health outcome, using as our case study polychlorinated biphenyls (PCBs and hypertension. The association between serum PCB and hypertension among participants in the 1999–2004 National Health and Nutrition Examination Survey was examined. First, unconditional multivariate logistic regression was used to estimate odds ratios and associated 95% confidence intervals. Next, correlation and multicollinearity among PCB congeners was evaluated, and clustering analyses performed to determine groups of related congeners. Finally, a weighted sum was constructed to represent the relative importance of each congener in relation to hypertension risk. PCB serum concentrations varied by demographic characteristics, and were on average higher among those with hypertension. Logistic regression results showed mixed findings by congener and class. Further analyses identified groupings of correlated PCBs. Using a weighted sum approach to equalize different ranges and potencies, PCBs 66, 101, 118, 128 and 187 were significantly associated with increased risk of hypertension. Epidemiologic data were used to demonstrate an approach to evaluating the association between a complex environmental exposure and health outcome. The complexity of analyzing a large number of related exposures, where each may have different potency and range, are addressed in the context of the association between hypertension risk and exposure to PCBs.

  17. Regression in autistic spectrum disorders.

    Science.gov (United States)

    Stefanatos, Gerry A

    2008-12-01

    A significant proportion of children diagnosed with Autistic Spectrum Disorder experience a developmental regression characterized by a loss of previously-acquired skills. This may involve a loss of speech or social responsitivity, but often entails both. This paper critically reviews the phenomena of regression in autistic spectrum disorders, highlighting the characteristics of regression, age of onset, temporal course, and long-term outcome. Important considerations for diagnosis are discussed and multiple etiological factors currently hypothesized to underlie the phenomenon are reviewed. It is argued that regressive autistic spectrum disorders can be conceptualized on a spectrum with other regressive disorders that may share common pathophysiological features. The implications of this viewpoint are discussed.

  18. Associations of lifestyle factors (smoking, alcohol consumption, diet and physical activity) with type 2 diabetes among American adults from National Health and Nutrition Examination Survey (NHANES) 2005-2014.

    Science.gov (United States)

    Liu, Ying; Wang, Kesheng; Maisonet, Mildred; Wang, Liang; Zheng, Shimin

    2017-09-01

    Over the long term, unhealthy lifestyles can lead to many health problems, especially type 2 diabetes (T2D). The aim of the present study was to determine associations between lifestyle factors (smoking, alcohol consumption, physical activity, and diet) and T2D in American adults (aged ≥20 years) in a nationally representative sample. Data for 12 987 American adults participating in the National Health and Nutrition Examination Survey 2005-2014 were evaluated. Weighted multiple logistic regression models were used to examine associations between the four lifestyle factors and T2D after adjusting for demographics and socioeconomic status (SES). Prevalence trends for T2D were examined using Cochran-Armitage tests. There was a significant increasing prevalence trend for T2D among American adults. Smokers and individuals consuming >12 alcoholic drinks in the past year were less likely to report having T2D than non-smokers (odds ratio [OR] 0.41; 95% confidence interval [CI] 0.35-0.48) and those consuming diet were more likely to report having T2D than those eating an excellent diet (OR 1.18; 95% CI 1.02-1.41). All these relationships remained significant after adjustment for demographics and SES. All four lifestyle factors were significantly associated with T2D among American adults. The findings of the present study provide useful information for healthcare providers that may help them promote specific lifestyle modifications. © 2016 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and John Wiley & Sons Australia, Ltd.

  19. Re-examining the link between prenatal maternal anxiety and child emotional difficulties, using a sibling design.

    Science.gov (United States)

    Bekkhus, Mona; Lee, Yunsung; Nordhagen, Rannveig; Magnus, Per; Samuelsen, Sven O; Borge, Anne I H

    2018-02-01

    Prenatal exposure to maternal anxiety has been associated with child emotional difficulties in a number of epidemiological studies. One key concern, however, is that this link is vulnerable to confounding by pleiotropic genes or environmental family factors. Data on 82 383 mothers and children from the population-based Mother and Child Cohort Study and data on 21 980 siblings were used in this study. Mothers filled out questionnaires for each unique pregnancy, for infant difficulties at 6 months and for emotional difficulties at 36 months. The link between prenatal maternal anxiety and child difficulties were examined using logistic regression analyses and multiple linear regression analyses for the full study sample and the sibling sample. In the conventional full-cohort analyses, prenatal exposure to maternal anxiety was associated with child difficulties at both 6 months [odds ratio (OR) = 2.1 (1.94-2.27)] and 36 months [OR = 2.72 (2.47-2.99)]. The findings were essentially the same whether we examined difficulties at 6 months or at 36 months. However, these associations were no longer present once we controlled for potential social and genetic confounders in the sibling comparison analyses, either at 6 months [OR = 1.32 (0.91-1.90)] or at 36 months [OR = 1.28 (0.63-2.60)]. Findings from multiple regression analyses with continuous measures were essentially the same. Our finding lends little support for there being an independent prenatal effect on child emotional difficulties; rather, our findings suggest that the link between prenatal maternal anxiety and child difficulties could be confounded by pleiotropic genes or environmental family factors. © The Author 2017; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association

  20. Prediction of Mind-Wandering with Electroencephalogram and Non-linear Regression Modeling.

    Science.gov (United States)

    Kawashima, Issaku; Kumano, Hiroaki

    2017-01-01

    Mind-wandering (MW), task-unrelated thought, has been examined by researchers in an increasing number of articles using models to predict whether subjects are in MW, using numerous physiological variables. However, these models are not applicable in general situations. Moreover, they output only binary classification. The current study suggests that the combination of electroencephalogram (EEG) variables and non-linear regression modeling can be a good indicator of MW intensity. We recorded EEGs of 50 subjects during the performance of a Sustained Attention to Response Task, including a thought sampling probe that inquired the focus of attention. We calculated the power and coherence value and prepared 35 patterns of variable combinations and applied Support Vector machine Regression (SVR) to them. Finally, we chose four SVR models: two of them non-linear models and the others linear models; two of the four models are composed of a limited number of electrodes to satisfy model usefulness. Examination using the held-out data indicated that all models had robust predictive precision and provided significantly better estimations than a linear regression model using single electrode EEG variables. Furthermore, in limited electrode condition, non-linear SVR model showed significantly better precision than linear SVR model. The method proposed in this study helps investigations into MW in various little-examined situations. Further, by measuring MW with a high temporal resolution EEG, unclear aspects of MW, such as time series variation, are expected to be revealed. Furthermore, our suggestion that a few electrodes can also predict MW contributes to the development of neuro-feedback studies.

  1. Prediction of Mind-Wandering with Electroencephalogram and Non-linear Regression Modeling

    Directory of Open Access Journals (Sweden)

    Issaku Kawashima

    2017-07-01

    Full Text Available Mind-wandering (MW, task-unrelated thought, has been examined by researchers in an increasing number of articles using models to predict whether subjects are in MW, using numerous physiological variables. However, these models are not applicable in general situations. Moreover, they output only binary classification. The current study suggests that the combination of electroencephalogram (EEG variables and non-linear regression modeling can be a good indicator of MW intensity. We recorded EEGs of 50 subjects during the performance of a Sustained Attention to Response Task, including a thought sampling probe that inquired the focus of attention. We calculated the power and coherence value and prepared 35 patterns of variable combinations and applied Support Vector machine Regression (SVR to them. Finally, we chose four SVR models: two of them non-linear models and the others linear models; two of the four models are composed of a limited number of electrodes to satisfy model usefulness. Examination using the held-out data indicated that all models had robust predictive precision and provided significantly better estimations than a linear regression model using single electrode EEG variables. Furthermore, in limited electrode condition, non-linear SVR model showed significantly better precision than linear SVR model. The method proposed in this study helps investigations into MW in various little-examined situations. Further, by measuring MW with a high temporal resolution EEG, unclear aspects of MW, such as time series variation, are expected to be revealed. Furthermore, our suggestion that a few electrodes can also predict MW contributes to the development of neuro-feedback studies.

  2. Effect of Abdominal Visceral Fat Change on Regression of Erosive Esophagitis: Prospective Cohort Study.

    Science.gov (United States)

    Nam, Su Youn; Kim, Young Woo; Park, Bum Joon; Ryu, Kum Hei; Kim, Hyun Boem

    2018-05-04

    Although abdominal visceral fat has been associated with erosive esophagitis in cross-sectional studies, there are few data on the longitudinal effect. We evaluated the effects of abdominal visceral fat change on the regression of erosive esophagitis in a prospective cohort study. A total of 163 participants with erosive esophagitis at baseline were followed up at 34 months and underwent esophagogastroduodenoscopy and computed tomography at both baseline and follow-up. The longitudinal effects of abdominal visceral fat on the regression of erosive esophagitis were evaluated using relative risk (RR) and 95% confidence intervals (CIs). Regression was observed in approximately 49% of participants (n=80). The 3rd (RR, 0.13; 95% CI, 0.02 to 0.71) and 4th quartiles (RR, 0.07; 95% CI, 0.01 to 0.38) of visceral fat at follow-up were associated with decreased regression of erosive esophagitis. The highest quartile of visceral fat change reduced the probability of the regression of erosive esophagitis compared to the lowest quartile (RR, 0.10; 95% CI, 0.03 to 0.28). Each trend showed a dose-dependent pattern (p for trend fat at follow-up and a greater increase in visceral fat reduced the regression of erosive esophagitis in a dose-dependent manner.

  3. Semiparametric regression analysis of interval-censored competing risks data.

    Science.gov (United States)

    Mao, Lu; Lin, Dan-Yu; Zeng, Donglin

    2017-09-01

    Interval-censored competing risks data arise when each study subject may experience an event or failure from one of several causes and the failure time is not observed directly but rather is known to lie in an interval between two examinations. We formulate the effects of possibly time-varying (external) covariates on the cumulative incidence or sub-distribution function of competing risks (i.e., the marginal probability of failure from a specific cause) through a broad class of semiparametric regression models that captures both proportional and non-proportional hazards structures for the sub-distribution. We allow each subject to have an arbitrary number of examinations and accommodate missing information on the cause of failure. We consider nonparametric maximum likelihood estimation and devise a fast and stable EM-type algorithm for its computation. We then establish the consistency, asymptotic normality, and semiparametric efficiency of the resulting estimators for the regression parameters by appealing to modern empirical process theory. In addition, we show through extensive simulation studies that the proposed methods perform well in realistic situations. Finally, we provide an application to a study on HIV-1 infection with different viral subtypes. © 2017, The International Biometric Society.

  4. Linear regression in astronomy. II

    Science.gov (United States)

    Feigelson, Eric D.; Babu, Gutti J.

    1992-01-01

    A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.

  5. Is energy imparted a good measure of the radiation risk associated with CT examinations

    International Nuclear Information System (INIS)

    Huda, W.

    1984-01-01

    The dose distribution in a Rando phantom has been measured for typical EMI 5005 CT scans of the head, chest, abdomen and pelvis. These dose distributions have been used to generate quantitative estimates of the somatic and genetic radiation risks associated with these CT examinations and also to measure the total energy imparted during each scan. A comparison has been made between the radiation risk estimates and the energy imparted measurements. The energy imparted measurements are not a good indicator of the somatic and/or genetic risks when one type of CT scan is compared with another. However, for a given type of scan, the energy imparted may be a reasonable indicator of the relative somatic risks associated with different CT examinations. Considerable care should be taken when interpreting and using any measured value of energy imparted in a radiological examination since published values of the risk per unit energy imparted can significantly underestimate the radiation risk. (author)

  6. Land use regression modeling of oxidative potential of fine particles, NO2, PM2.5 mass and association to type two diabetes mellitus

    Science.gov (United States)

    Hellack, Bryan; Sugiri, Dorothea; Schins, Roel P. F.; Schikowski, Tamara; Krämer, Ursula; Kuhlbusch, Thomas A. J.; Hoffmann, Barbara

    2017-12-01

    While land use regression models (LUR) are commonly used, e.g. for the prediction of spatially variable air pollutant mass concentrations, they are scarcely used for predicting the oxidative potential (OP), a suggested unifying predictor of health effects. Therefore a LUR model was developed to examine if long-term OP of fine particulate exposure can be reasonably predicted by LUR modeling and whether it is related to health effects in a study region comprised of urban and rural areas. Four 14-day sampling periods over 1 year at 40 sites in the western Ruhr Area and adjacent northern rural area, Germany, in 2002/2003 were conducted and annual Nitrogen Dioxide (NO2), fine particles (PM2.5), and OP were calculated. LUR models were developed to estimate spatially-resolved annual OP, NO2 and PM2.5 concentrations. The model performance was checked by leave-one-out cross validation (LOOCV) and cox regression was used to analyze the association of modeled residential OP and NO2 with incident type 2 diabetes mellitus (T2DM) in 1784 elderly women during a mean follow-up of 16 years (baseline 1985-1994). The measured OP and NO2 concentrations were moderately correlated (rSpearman 0.57). The LUR models explained 62% and 92% of the OP and NO2 variance (adjusted LOOCV R2 57% and 90%). PM10 emission from combustion in a 5000 m buffer was the most important predictor for OP and NO2. Modeled pollutants were highly correlated (rSpearman 0.87). Model quality for OP was sensitive to the inclusion of a single influential measurement site. For PM2.5 mass only an insufficient model with a low explained variance of 22% (adjusted R2) was developed so no health effects analyses were conducted with estimated PM2.5. Increases in OP and NO2 were associated with an increase in risk of T2DM by a hazard ratio of 1.38 (95% CI 1.06-1.80) and 1.39 (95% CI 1.07-1.81) per interquartile range of OP and NO2, respectively. We conclude that spatially-resolved OP can be predicted by LUR modeling, but

  7. Multiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular Malaysia.

    Science.gov (United States)

    Ng, Kar Yong; Awang, Norhashidah

    2018-01-06

    Frequent haze occurrences in Malaysia have made the management of PM 10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM 10 variation and good forecast of PM 10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM 10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM 10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM 10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.

  8. A Matlab program for stepwise regression

    Directory of Open Access Journals (Sweden)

    Yanhong Qi

    2016-03-01

    Full Text Available The stepwise linear regression is a multi-variable regression for identifying statistically significant variables in the linear regression equation. In present study, we presented the Matlab program of stepwise regression.

  9. Multiple Imputation of a Randomly Censored Covariate Improves Logistic Regression Analysis.

    Science.gov (United States)

    Atem, Folefac D; Qian, Jing; Maye, Jacqueline E; Johnson, Keith A; Betensky, Rebecca A

    2016-01-01

    Randomly censored covariates arise frequently in epidemiologic studies. The most commonly used methods, including complete case and single imputation or substitution, suffer from inefficiency and bias. They make strong parametric assumptions or they consider limit of detection censoring only. We employ multiple imputation, in conjunction with semi-parametric modeling of the censored covariate, to overcome these shortcomings and to facilitate robust estimation. We develop a multiple imputation approach for randomly censored covariates within the framework of a logistic regression model. We use the non-parametric estimate of the covariate distribution or the semiparametric Cox model estimate in the presence of additional covariates in the model. We evaluate this procedure in simulations, and compare its operating characteristics to those from the complete case analysis and a survival regression approach. We apply the procedures to an Alzheimer's study of the association between amyloid positivity and maternal age of onset of dementia. Multiple imputation achieves lower standard errors and higher power than the complete case approach under heavy and moderate censoring and is comparable under light censoring. The survival regression approach achieves the highest power among all procedures, but does not produce interpretable estimates of association. Multiple imputation offers a favorable alternative to complete case analysis and ad hoc substitution methods in the presence of randomly censored covariates within the framework of logistic regression.

  10. Examining patterns of association with defensive information processing about colorectal cancer screening.

    Science.gov (United States)

    McQueen, Amy; Swank, Paul R; Vernon, Sally W

    2014-11-01

    To reduce negative psychological affect from information or behavior that is inconsistent with one's positive self-concept, individuals use a variety of defensive strategies. It is unknown whether correlates differ across defenses. We examined correlates of four levels of defensive information processing about colorectal cancer screening. Cross-sectional surveys were completed by a convenience sample of 287 adults aged 50-75 years. Defenses measures were more consistently associated with individual differences (especially avoidant coping styles); however, situational variables involving health-care providers also were important. Future research should examine changes in defenses after risk communication and their relative impact on colorectal cancer screening. © The Author(s) 2013.

  11. Association between Caregiving, Meaning in Life, and Life Satisfaction beyond 50 in an Asian Sample: Age as a Moderator

    Science.gov (United States)

    Ang, Rebecca P.; O, Jiaqing

    2012-01-01

    The association between caregiving, meaning in life, and life satisfaction was examined in sample of 519 older Asian adults beyond 50 years of age. Two hierarchical multiple regression analyses were conducted to examine age as moderator of the associations between caregiving, meaning in life, and life satisfaction. Age moderated the association…

  12. An Original Stepwise Multilevel Logistic Regression Analysis of Discriminatory Accuracy

    DEFF Research Database (Denmark)

    Merlo, Juan; Wagner, Philippe; Ghith, Nermin

    2016-01-01

    BACKGROUND AND AIM: Many multilevel logistic regression analyses of "neighbourhood and health" focus on interpreting measures of associations (e.g., odds ratio, OR). In contrast, multilevel analysis of variance is rarely considered. We propose an original stepwise analytical approach that disting...

  13. HIV/AIDS Related Knowledge and Perceived Risk Associated with ...

    African Journals Online (AJOL)

    Using data from the 2004 National Survey of Adolescents in Uganda, logistic regression models were fitted to examine the odds that HIV/AIDS related knowledge and perceived risk of HIV infection are associated with condom use among adolescents. After including demographic measures, findings indicated that correct ...

  14. Quantile regression theory and applications

    CERN Document Server

    Davino, Cristina; Vistocco, Domenico

    2013-01-01

    A guide to the implementation and interpretation of Quantile Regression models This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods. The main focus of this book is to provide the reader with a comprehensivedescription of the main issues concerning quantile regression; these include basic modeling, geometrical interpretation, estimation and inference for quantile regression, as well as issues on validity of the model, diagnostic tools. Each methodological aspect is explored and

  15. Fungible weights in logistic regression.

    Science.gov (United States)

    Jones, Jeff A; Waller, Niels G

    2016-06-01

    In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  16. Arcuate Fasciculus in Autism Spectrum Disorder Toddlers with Language Regression

    Directory of Open Access Journals (Sweden)

    Zhang Lin

    2018-03-01

    Full Text Available Language regression is observed in a subset of toddlers with autism spectrum disorder (ASD as initial symptom. However, such a phenomenon has not been fully explored, partly due to the lack of definite diagnostic evaluation methods and criteria. Materials and Methods: Fifteen toddlers with ASD exhibiting language regression and fourteen age-matched typically developing (TD controls underwent diffusion tensor imaging (DTI. DTI parameters including fractional anisotropy (FA, average fiber length (AFL, tract volume (TV and number of voxels (NV were analyzed by Neuro 3D in Siemens syngo workstation. Subsequently, the data were analyzed by using IBM SPSS Statistics 22. Results: Compared with TD children, a significant reduction of FA along with an increase in TV and NV was observed in ASD children with language regression. Note that there were no significant differences between ASD and TD children in AFL of the arcuate fasciculus (AF. Conclusions: These DTI changes in the AF suggest that microstructural anomalies of the AF white matter may be associated with language deficits in ASD children exhibiting language regression starting from an early age.

  17. Association between socioeconomic status and oral health behaviors: The 2008-2010 Korea national health and nutrition examination survey.

    Science.gov (United States)

    Park, Jun-Beom; Han, Kyungdo; Park, Yong-Gyu; Ko, Youngkyung

    2016-10-01

    Socioeconomic status (SES) has been reported to be associated with oral health behavior. Therefore, the present study was conducted to assess the relationship between SES and oral health behaviors in a large sample of the Korean population. Data from the Korea National Health and Nutrition Examination Survey, which was conducted between 2008 and 2010 by the Division of Chronic Disease Surveillance under the Korea Centers for Disease Control and Prevention and the Korean Ministry of Health and Welfare, were used in the present study. Daily tooth brushing frequency and the use of secondary oral products according to demographic variables and anthropometric characteristics of the participants were assessed. Multivariate logistic regression analyses were used to analyze the associations between daily tooth brushing frequency and the use of secondary oral products, and SES, urban/rural residence, body mass index (BMI), alcohol intake and smoking. An association between SES and tooth brushing frequency and the use of secondary oral products was detected after adjustment. Following adjustment for age, gender, BMI, smoking, drinking, exercise, energy intake, fat intake, periodontal treatment needs and education or income, the adjusted odds ratios and 95% confidence intervals (CI) of tooth brushing ≥3 per day in the highest income group were 1.264 (95% CI, 1.094-1.460) and 2.686 (95% CI, 2.286-3.155) for highest education level group. The adjusted odds ratios for the use of secondary oral products in the highest income and highest education groups were 1.835 (95% CI, 1.559-2.161) and 5.736 (95% CI, 4.734-6.951), respectively, after adjustment for age, gender, smoking, BMI, exercise, calorie intake, periodontal treatment requirements or income. The present study demonstrated an association between SES and oral health behaviors in a large sample of the Korean population. Within the limits of the present study, income and education were suggested as potential risk indicators

  18. Climate Impacts on Chinese Corn Yields: A Fractional Polynomial Regression Model

    NARCIS (Netherlands)

    Kooten, van G.C.; Sun, Baojing

    2012-01-01

    In this study, we examine the effect of climate on corn yields in northern China using data from ten districts in Inner Mongolia and two in Shaanxi province. A regression model with a flexible functional form is specified, with explanatory variables that include seasonal growing degree days,

  19. Spontaneous regression of retinopathy of prematurity:incidence and predictive factors

    Directory of Open Access Journals (Sweden)

    Rui-Hong Ju

    2013-08-01

    Full Text Available AIM:To evaluate the incidence of spontaneous regression of changes in the retina and vitreous in active stage of retinopathy of prematurity(ROP and identify the possible relative factors during the regression.METHODS: This was a retrospective, hospital-based study. The study consisted of 39 premature infants with mild ROP showed spontaneous regression (Group A and 17 with severe ROP who had been treated before naturally involuting (Group B from August 2008 through May 2011. Data on gender, single or multiple pregnancy, gestational age, birth weight, weight gain from birth to the sixth week of life, use of oxygen in mechanical ventilation, total duration of oxygen inhalation, surfactant given or not, need for and times of blood transfusion, 1,5,10-min Apgar score, presence of bacterial or fungal or combined infection, hyaline membrane disease (HMD, patent ductus arteriosus (PDA, duration of stay in the neonatal intensive care unit (NICU and duration of ROP were recorded.RESULTS: The incidence of spontaneous regression of ROP with stage 1 was 86.7%, and with stage 2, stage 3 was 57.1%, 5.9%, respectively. With changes in zone Ⅲ regression was detected 100%, in zoneⅡ 46.2% and in zoneⅠ 0%. The mean duration of ROP in spontaneous regression group was 5.65±3.14 weeks, lower than that of the treated ROP group (7.34±4.33 weeks, but this difference was not statistically significant (P=0.201. GA, 1min Apgar score, 5min Apgar score, duration of NICU stay, postnatal age of initial screening and oxygen therapy longer than 10 days were significant predictive factors for the spontaneous regression of ROP (P<0.05. Retinal hemorrhage was the only independent predictive factor the spontaneous regression of ROP (OR 0.030, 95%CI 0.001-0.775, P=0.035.CONCLUSION:This study showed most stage 1 and 2 ROP and changes in zone Ⅲ can spontaneously regression in the end. Retinal hemorrhage is weakly inversely associated with the spontaneous regression.

  20. Are learning strategies linked to academic performance among adolescents in two States in India? A tobit regression analysis.

    Science.gov (United States)

    Areepattamannil, Shaljan

    2014-01-01

    The results of the fourth cycle of the Program for International Student Assessment (PISA) revealed that an unacceptably large number of adolescent students in two states in India-Himachal Pradesh and Tamil Nadu-have failed to acquire basic skills in reading, mathematics, and science (Walker, 2011). Drawing on data from the PISA 2009 database and employing multivariate left-censored to bit regression as a data analytic strategy, the present study, therefore, examined whether or not the learning strategies-memorization, elaboration, and control strategies-of adolescent students in Himachal Pradesh (N = 1,616; Mean age = 15.81 years) and Tamil Nadu (N = 3,210; Mean age = 15.64 years) were linked to their performance on the PISA 2009 reading, mathematics, and science assessments. Tobit regression analyses, after accounting for student demographic characteristics, revealed that the self-reported use of control strategies was significantly positively associated with reading, mathematical, and scientific literacy of adolescents in Himachal Pradesh and Tamil Nadu. While the self-reported use of elaboration strategies was not significantly associated with reading literacy among adolescents in Himachal Pradesh and Tamil Nadu, it was significantly positively associated with mathematical literacy among adolescents in Himachal Pradesh and Tamil Nadu. Moreover, the self-reported use of elaboration strategies was significantly and positively linked to scientific literacy among adolescents in Himachal Pradesh alone. The self-reported use of memorization strategies was significantly negatively associated with reading, mathematical, and scientific literacy in Tamil Nadu, while it was significantly negatively associated with mathematical and scientific literacy alone in Himachal Pradesh. Implications of these findings are discussed.

  1. Estimation of organ doses and risk of cancer associated with CT examination

    International Nuclear Information System (INIS)

    Ahmed, Nagla Nooraldaim

    2017-11-01

    The purpose of this study to estimate the organ closes and risk of cancer associated with CT examinations in Khartoum state, where the study conducted in three hospitals; Alzytouna , royal scan and Royal Care. From April to November 2017, and the data collected from 120 patients, 40 patents from each hospital undergoing CT brain and abdomen examinations. The data were entered to CT - Expo version 2.4 software for calculation the effective dose and organ dose and by Xray risk web site for calculate the risk factor associated with CT examinations. Results have shown the values of effective dose that found 9.73 mSv for all patients and for female and male 9.9 mSv respectively. The effective dose from Brain examinations in three hospitals Alzytouna Royal scan and Royal Care was 16.9 mSv, 3.7 mSv, 3.8 mSv respectively, and from abdomen examinations was 4.2 mSv, 7.6 mSv, 22.2 mSv respectively. Comparing te effective dose from the hospitals, for Ct. Brain in Alzytouna hospital was higher than other hospitals; and for CT Abdomen in Royal Care hospital was higher than other hospitals, but still under the risk levels according to the ICRP report. For organ doses results, the most organs exposed from CT. brain was brain, salivary gland, thyroid gland, Bone marrow, Bone surface, Extra thoracic tissue, Eye lens and oral mucosa received ( 70,2, 66.4,15.04, 10.9, 24.9, 14.8,89.5,65.07) mSv respectively. The most organs exposed from CT. Abdomen were liver, stomach, low, Large intestine, Bladder, Bone surface, upper , Large intestine, spleen, kidney, small intestine and prostate received (16.53, 12.8, 33.43, 41.01,20.5, 38.4, 14.7, 28.9, 37.5,30.5 ) mSv respectively. This study found that te ability of cancer induced i the female was higher from the male; dut to body component of the female. (Author)

  2. An association of health behaviors with depression and metabolic risks: Data from 2007 to 2014 U.S. National Health and Nutrition Examination Survey.

    Science.gov (United States)

    Liu, Ying; Ozodiegwu, Ifeoma D; Yu, Yang; Hess, Rick; Bie, Ronghai

    2017-08-01

    Both depression and metabolic syndrome (MetS) confer an increased risk of developing type 2 diabetes (T2D) and cardiovascular disease. Accumulating evidence suggests healthy behaviors are crucial to maintain, improve and manage chronical disease and mental health; and unhealthy diet and sedentary behavior were found two major risk factors of MetS. The objective of this study was to investigate whether health behaviors (alcohol consumption, smoking, diet and recreational physical activity) are associated with depression and metabolic syndrome simultaneously. This study included 1300 participants aged 20 years and over who had answered mental health-depression screener questions (PHQ-9) and finished examinations and laboratory tests related to five risk factors of MetS during the U.S. National Health and Nutrition Examination Survey (NHANES) 2007-2014. A set of series of weighted logistic regression models were used to investigate the aforementioned relationship. The prevalence of depression among U.S. adults is 15.08%. The two most often reported depression symptoms were "Trouble sleeping or sleeping too much" and "Feeling tired or having little energy", with rates of14.68% and 13.09%, respectively. Participants who engaged in only light physical activity were more likely to have been identified as experiencing depression and MetS than those who engaged in vigorous physical activity with odd ratios 3.18 (95% CI: 1.59, 6.37) and 3.50 (95%CI: 2.17, 5.63), respectively. Individuals in the study having poor diets were more likely to suffer from depression than those eating good diets (OR=2.17, 95%CI: 1.47, 3.22). Physical activity is strongly and inversely associated with depression and MetS. Diet is significantly associated with depression rather than MetS in this study. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Principal component regression analysis with SPSS.

    Science.gov (United States)

    Liu, R X; Kuang, J; Gong, Q; Hou, X L

    2003-06-01

    The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.

  4. Predictors of postoperative outcomes of cubital tunnel syndrome treatments using multiple logistic regression analysis.

    Science.gov (United States)

    Suzuki, Taku; Iwamoto, Takuji; Shizu, Kanae; Suzuki, Katsuji; Yamada, Harumoto; Sato, Kazuki

    2017-05-01

    This retrospective study was designed to investigate prognostic factors for postoperative outcomes for cubital tunnel syndrome (CubTS) using multiple logistic regression analysis with a large number of patients. Eighty-three patients with CubTS who underwent surgeries were enrolled. The following potential prognostic factors for disease severity were selected according to previous reports: sex, age, type of surgery, disease duration, body mass index, cervical lesion, presence of diabetes mellitus, Workers' Compensation status, preoperative severity, and preoperative electrodiagnostic testing. Postoperative severity of disease was assessed 2 years after surgery by Messina's criteria which is an outcome measure specifically for CubTS. Bivariate analysis was performed to select candidate prognostic factors for multiple linear regression analyses. Multiple logistic regression analysis was conducted to identify the association between postoperative severity and selected prognostic factors. Both bivariate and multiple linear regression analysis revealed only preoperative severity as an independent risk factor for poor prognosis, while other factors did not show any significant association. Although conflicting results exist regarding prognosis of CubTS, this study supports evidence from previous studies and concludes early surgical intervention portends the most favorable prognosis. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

  5. Is there still a place for the concept of 'therapeutic regression' in psychoanalysis?

    Science.gov (United States)

    Spurling, Laurence S

    2008-06-01

    The author uses his own failure to find a place for the idea of therapeutic regression in his clinical thinking or practice as the basis for an investigation into its meaning and usefulness. He makes a distinction between three ways the term 'regression' is used in psychoanalytic discourse: as a way of evoking a primitive level of experience; as a reminder in some clinical situations of the value of non-intervention on the part of the analyst; and as a description of a phase of an analytic treatment with some patients where the analyst needs to put aside normal analytic technique in order to foster a regression in the patient. It is this third meaning, which the author terms "therapeutic regression" that this paper examines, principally by means of an extended discussion of two clinical examples of a patient making a so-called therapeutic regression, one given by Winnicott and the other by Masud Khan. The author argues that in these examples the introduction of the concept of therapeutic regression obscures rather than clarifies the clinical process. He concludes that, as a substantial clinical concept, the idea of therapeutic regression has outlived its usefulness. However he also notes that many psychoanalytic writers continue to find a use for the more generic concept of regression, and that the very engagement with the more particular idea of therapeutic regression has value in provoking questions as to what is truly therapeutic in psychoanalytic treatment.

  6. EBV-associated post-transplantation B-cell lymphoproliferative disorder following allogenic stem cell transplantation for acute lymphoblastic leukaemia: tumor regression after reduction of immunosuppression - a case report

    Directory of Open Access Journals (Sweden)

    Niedobitek Gerald

    2010-03-01

    Full Text Available Abstract Epstein-Barr virus (EBV-associated B-cell post-transplantation lymphoproliferative disorder (PTLD is a severe complication following stem cell transplantation. This is believed to occur as a result of iatrogenic immunosuppression leading to a relaxation of T-cell control of EBV infection and thus allowing viral reactivation and proliferation of EBV-infected B-lymphocytes. In support of this notion, reduction of immunosuppressive therapy may lead to regression of PTLD. We present a case of an 18-year-old male developing a monomorphic B-cell PTLD 2 months after receiving an allogenic stem cell transplant for acute lymphoblastic leukemia. Reduction of immunosuppressive therapy led to regression of lymphadenopathy. Nevertheless, the patient died 3 months afterwards due to extensive graft-vs.-host-disease and sepsis. As a diagnostic lymph node biopsy was performed only after reduction of immunosuppressive therapy, we are able to study the histopathological changes characterizing PTLD regression. We observed extensive apoptosis of blast cells, accompanied by an abundant infiltrate comprising predominantly CD8-positive, Granzyme B-positive T-cells. This observation supports the idea that regression of PTLD is mediated by cytotoxic T-cells and is in keeping with the observation that T-cell depletion, represents a major risk factor for the development of PTLD.

  7. QRank: a novel quantile regression tool for eQTL discovery.

    Science.gov (United States)

    Song, Xiaoyu; Li, Gen; Zhou, Zhenwei; Wang, Xianling; Ionita-Laza, Iuliana; Wei, Ying

    2017-07-15

    Over the past decade, there has been a remarkable improvement in our understanding of the role of genetic variation in complex human diseases, especially via genome-wide association studies. However, the underlying molecular mechanisms are still poorly characterized, impending the development of therapeutic interventions. Identifying genetic variants that influence the expression level of a gene, i.e. expression quantitative trait loci (eQTLs), can help us understand how genetic variants influence traits at the molecular level. While most eQTL studies focus on identifying mean effects on gene expression using linear regression, evidence suggests that genetic variation can impact the entire distribution of the expression level. Motivated by the potential higher order associations, several studies investigated variance eQTLs. In this paper, we develop a Quantile Rank-score based test (QRank), which provides an easy way to identify eQTLs that are associated with the conditional quantile functions of gene expression. We have applied the proposed QRank to the Genotype-Tissue Expression project, an international tissue bank for studying the relationship between genetic variation and gene expression in human tissues, and found that the proposed QRank complements the existing methods, and identifies new eQTLs with heterogeneous effects across different quantile levels. Notably, we show that the eQTLs identified by QRank but missed by linear regression are associated with greater enrichment in genome-wide significant SNPs from the GWAS catalog, and are also more likely to be tissue specific than eQTLs identified by linear regression. An R package is available on R CRAN at https://cran.r-project.org/web/packages/QRank . xs2148@cumc.columbia.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  8. Logistic regression models

    CERN Document Server

    Hilbe, Joseph M

    2009-01-01

    This book really does cover everything you ever wanted to know about logistic regression … with updates available on the author's website. Hilbe, a former national athletics champion, philosopher, and expert in astronomy, is a master at explaining statistical concepts and methods. Readers familiar with his other expository work will know what to expect-great clarity.The book provides considerable detail about all facets of logistic regression. No step of an argument is omitted so that the book will meet the needs of the reader who likes to see everything spelt out, while a person familiar with some of the topics has the option to skip "obvious" sections. The material has been thoroughly road-tested through classroom and web-based teaching. … The focus is on helping the reader to learn and understand logistic regression. The audience is not just students meeting the topic for the first time, but also experienced users. I believe the book really does meet the author's goal … .-Annette J. Dobson, Biometric...

  9. Weight-related actual and ideal self-states, discrepancies, and shame, guilt, and pride: examining associations within the process model of self-conscious emotions.

    Science.gov (United States)

    Castonguay, Andree L; Brunet, Jennifer; Ferguson, Leah; Sabiston, Catherine M

    2012-09-01

    The aim of this study was to examine the associations between women's actual:ideal weight-related self-discrepancies and experiences of weight-related shame, guilt, and authentic pride using self-discrepancy (Higgins, 1987) and self-conscious emotion (Tracy & Robins, 2004) theories as guiding frameworks. Participants (N=398) completed self-report questionnaires. Main analyses involved polynomial regressions, followed by the computation and evaluation of response surface values. Actual and ideal weight self-states were related to shame (R2 = .35), guilt (R2 = .25), and authentic pride (R2 = .08). When the discrepancy between actual and ideal weights increased, shame and guilt also increased, while authentic pride decreased. Findings provide partial support for self-discrepancy theory and the process model of self-conscious emotions. Experiencing weight-related self-discrepancies may be important cognitive appraisals related to shame, guilt, and authentic pride. Further research is needed exploring the relations between self-discrepancies and a range of weight-related self-conscious emotions. Copyright © 2012 Elsevier Ltd. All rights reserved.

  10. Application of Social Control Theory to Examine Parent, Teacher, and Close Friend Attachment and Substance Use Initiation among Korean Youth

    Science.gov (United States)

    Han, Yoonsun; Kim, Heejoo; Lee, DongHun

    2016-01-01

    Based on Hirschi's social control theory (1969), this study examined the relationship between attachment (an element of social bonds) and the onset of substance use among South Korean adolescents. Using discrete-time logistic regression, the study investigated how attachment to parents, teachers, and close friends was associated with the timing of…

  11. Semiparametric Allelic Tests for Mapping Multiple Phenotypes: Binomial Regression and Mahalanobis Distance.

    Science.gov (United States)

    Majumdar, Arunabha; Witte, John S; Ghosh, Saurabh

    2015-12-01

    Binary phenotypes commonly arise due to multiple underlying quantitative precursors and genetic variants may impact multiple traits in a pleiotropic manner. Hence, simultaneously analyzing such correlated traits may be more powerful than analyzing individual traits. Various genotype-level methods, e.g., MultiPhen (O'Reilly et al. []), have been developed to identify genetic factors underlying a multivariate phenotype. For univariate phenotypes, the usefulness and applicability of allele-level tests have been investigated. The test of allele frequency difference among cases and controls is commonly used for mapping case-control association. However, allelic methods for multivariate association mapping have not been studied much. In this article, we explore two allelic tests of multivariate association: one using a Binomial regression model based on inverted regression of genotype on phenotype (Binomial regression-based Association of Multivariate Phenotypes [BAMP]), and the other employing the Mahalanobis distance between two sample means of the multivariate phenotype vector for two alleles at a single-nucleotide polymorphism (Distance-based Association of Multivariate Phenotypes [DAMP]). These methods can incorporate both discrete and continuous phenotypes. Some theoretical properties for BAMP are studied. Using simulations, the power of the methods for detecting multivariate association is compared with the genotype-level test MultiPhen's. The allelic tests yield marginally higher power than MultiPhen for multivariate phenotypes. For one/two binary traits under recessive mode of inheritance, allelic tests are found to be substantially more powerful. All three tests are applied to two different real data and the results offer some support for the simulation study. We propose a hybrid approach for testing multivariate association that implements MultiPhen when Hardy-Weinberg Equilibrium (HWE) is violated and BAMP otherwise, because the allelic approaches assume HWE

  12. Logistic regression applied to natural hazards: rare event logistic regression with replications

    Science.gov (United States)

    Guns, M.; Vanacker, V.

    2012-06-01

    Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

  13. Mapping urban environmental noise: a land use regression method.

    Science.gov (United States)

    Xie, Dan; Liu, Yi; Chen, Jining

    2011-09-01

    Forecasting and preventing urban noise pollution are major challenges in urban environmental management. Most existing efforts, including experiment-based models, statistical models, and noise mapping, however, have limited capacity to explain the association between urban growth and corresponding noise change. Therefore, these conventional methods can hardly forecast urban noise at a given outlook of development layout. This paper, for the first time, introduces a land use regression method, which has been applied for simulating urban air quality for a decade, to construct an urban noise model (LUNOS) in Dalian Municipality, Northwest China. The LUNOS model describes noise as a dependent variable of surrounding various land areas via a regressive function. The results suggest that a linear model performs better in fitting monitoring data, and there is no significant difference of the LUNOS's outputs when applied to different spatial scales. As the LUNOS facilitates a better understanding of the association between land use and urban environmental noise in comparison to conventional methods, it can be regarded as a promising tool for noise prediction for planning purposes and aid smart decision-making.

  14. Association of insulin resistance with near peak bone mass in the femur and lumbar spine of Korean adults aged 25-35: The Korean National Health and Nutrition Examination Survey 2008-2010

    Science.gov (United States)

    Choo, Min Soo; Choi, Se Rin; Han, Jun Hyun; Lee, Seong Ho

    2017-01-01

    Objective This study aimed to evaluate the relationship between insulin resistance and the bone mineral density (BMD) of femur and lumbar spine in Korean adults who are expected to exhibit near peak bone mass. Methods Data from the Korean National Health and Nutrition Examination Survey 2008–2010 were analyzed. A total of 2,750 participants aged 25−35 years were included. Insulin resistance was assessed using a homeostatic model assessment of insulin resistance (HOMA-IR) and serum fasting insulin. Results In a multivariate linear regression analysis, the HOMA-IR was significantly inversely associated with the BMD of the total hip (TH, β = −0.052, P = 0.002), femoral neck (FN, β = −0.072, Pinsulin was significantly inversely associated with the BMD of the TH (β = −0.055, P = 0.001), FN (β = −0.072, Pinsulin resistance may be independently and inversely associated with the near peak bone mass of the femur and lumbar spine. PMID:28704413

  15. An examination of environmental correlates with childhood height-for-age in Ghana.

    Science.gov (United States)

    Nikoi, Ebenezer; Anthamatten, Peter

    2013-01-01

    The relationship between a child's environment and nutritional status is difficult to examine yet could offer an important guide to policy. The objective of the present work was to examine individual and environmental correlates with childhood height-for-age in Ghana. Data were derived from the 2008 MEASURE Demographic and Health Survey in Ghana, the 2000 Ghana Population and Housing Census, and the World Wide Fund for Nature's eco-regions database. A generalized linear mixed regression model was used to estimate the effects of individual and environmental correlates on height-for-age. The study examined 2225 Ghanaian children aged 0-59 months. The setting was all districts in Ghana for the year 2008. After accounting for individual characteristics of children, mothers and households, height-for-age was significantly associated with population density. Other significantly associated variables in the final model were the age of the child, vaccination status, the size of the child at birth, months of breast-feeding, mother's BMI, whether the child's mother had health insurance and wealth quintile. In addition to a number of characteristics of the children and their households, the social milieu is important to understanding differences in height-for-age among children in Ghana. The biophysical environment was not associated with height-for-age.

  16. Examining Spatial Variation in the Effects of Japanese Red Pine (Pinus densiflora on Burn Severity Using Geographically Weighted Regression

    Directory of Open Access Journals (Sweden)

    Hyun-Joo Lee

    2017-05-01

    Full Text Available Burn severity has profound impacts on the response of post-fire forest ecosystems to fire events. Numerous previous studies have reported that burn severity is determined by variables such as meteorological conditions, pre-fire forest structure, and fuel characteristics. An underlying assumption of these studies was the constant effects of environmental variables on burn severity over space, and these analyses therefore did not consider the spatial dimension. This study examined spatial variation in the effects of Japanese red pine (Pinus densiflora on burn severity. Specifically, this study investigated the presence of spatially varying relationships between Japanese red pine and burn severity due to changes in slope and elevation. We estimated conventional ordinary least squares (OLS and geographically weighted regression (GWR models and compared them using three criteria; the coefficients of determination (R2, Akaike information criterion for small samples (AICc, and Moran’s I-value. The GWR model performed considerably better than the OLS model in explaining variation in burn severity. The results provided strong evidence that the effect of Japanese red pine on burn severity was not constant but varied spatially. Elevation was a significant factor in the variation in the effects of Japanese red pine on burn severity. The influence of red pine on burn severity was considerably higher in low-elevation areas but became less important than the other variables in high-elevation areas. The results of this study can be applied to location-specific strategies for forest managers and can be adopted to improve fire simulation models to more realistically mimic the nature of fire behavior.

  17. Biostatistics Series Module 6: Correlation and Linear Regression.

    Science.gov (United States)

    Hazra, Avijit; Gogtay, Nithya

    2016-01-01

    Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.

  18. Marginalized zero-inflated negative binomial regression with application to dental caries.

    Science.gov (United States)

    Preisser, John S; Das, Kalyan; Long, D Leann; Divaris, Kimon

    2016-05-10

    The zero-inflated negative binomial regression model (ZINB) is often employed in diverse fields such as dentistry, health care utilization, highway safety, and medicine to examine relationships between exposures of interest and overdispersed count outcomes exhibiting many zeros. The regression coefficients of ZINB have latent class interpretations for a susceptible subpopulation at risk for the disease/condition under study with counts generated from a negative binomial distribution and for a non-susceptible subpopulation that provides only zero counts. The ZINB parameters, however, are not well-suited for estimating overall exposure effects, specifically, in quantifying the effect of an explanatory variable in the overall mixture population. In this paper, a marginalized zero-inflated negative binomial regression (MZINB) model for independent responses is proposed to model the population marginal mean count directly, providing straightforward inference for overall exposure effects based on maximum likelihood estimation. Through simulation studies, the finite sample performance of MZINB is compared with marginalized zero-inflated Poisson, Poisson, and negative binomial regression. The MZINB model is applied in the evaluation of a school-based fluoride mouthrinse program on dental caries in 677 children. Copyright © 2015 John Wiley & Sons, Ltd.

  19. Minimax Regression Quantiles

    DEFF Research Database (Denmark)

    Bache, Stefan Holst

    A new and alternative quantile regression estimator is developed and it is shown that the estimator is root n-consistent and asymptotically normal. The estimator is based on a minimax ‘deviance function’ and has asymptotically equivalent properties to the usual quantile regression estimator. It is......, however, a different and therefore new estimator. It allows for both linear- and nonlinear model specifications. A simple algorithm for computing the estimates is proposed. It seems to work quite well in practice but whether it has theoretical justification is still an open question....

  20. Association of cardiovascular system medications with cognitive function and dementia in older adults living in nursing homes in Australia.

    Science.gov (United States)

    Liu, Enwu; Dyer, Suzanne M; O'Donnell, Lisa Kouladjian; Milte, Rachel; Bradley, Clare; Harrison, Stephanie L; Gnanamanickam, Emmanuel; Whitehead, Craig; Crotty, Maria

    2017-06-01

    To examine associations between cardiovascular system medication use with cognition function and diagnosis of dementia in older adults living in nursing homes in Australia. As part of a cross-sectional study of 17 Australian nursing homes examining quality of life and resource use, we examined the association between cognitive impairment and cardiovascular medication use (identified using the Anatomical Therapeutic Classification System) using general linear regression and logistic regression models. People who were receiving end of life care were excluded. Participants included 541 residents with a mean age of 85.5 years (± 8.5), a mean Psychogeriatric Assessment Scale-Cognitive Impairment (PAS-Cog) score of 13.3 (± 7.7), a prevalence of cardiovascular diseases of 44% and of hypertension of 47%. Sixty-four percent of participants had been diagnosed with dementia and 72% had received cardiovascular system medications within the previous 12 months. Regression models demonstrated the use of cardiovascular medications was associated with lower (better) PAS-Cog scores [Coefficient (β) = -3.7; 95% CI: -5.2 to -2.2; P cardiovascular system medication use and better cognitive status among older adults living in nursing homes. In this population, there may be differential access to health care and treatment of cardiovascular risk factors. This association warrants further investigation in large cohort studies.

  1. Is proximity to alcohol outlets associated with alcohol consumption and alcohol-related harm in Denmark?

    DEFF Research Database (Denmark)

    Kedir, Abdu; Berg-Beckhoff, Gabriele; Stock, Christiane

    2018-01-01

    Background: This study examined the associations between distance from residence to the nearest alcohol outlet with alcohol consumption as well as with alcohol-related harm. Methods: Data on alcohol consumption, alcohol-related harm and sociodemographics were obtained from the 2011 Danish Drug...... and Alcohol Survey (n=5133) with respondents aged 15–79 years. The information on distances from residence to the nearest alcohol outlets was obtained from Statistics Denmark. Multiple logistic and linear regressions were used to examine the association between distances to outlets and alcohol consumption...... whereas alcohol-related harm was analysed using negative binomial regression. Results: Among women it was found that those living closer to alcohol outlets were more likely to report alcohol-related harm (p

  2. Is proximity to alcohol outlets associated with alcohol consumption and alcohol-related harm in Denmark?

    DEFF Research Database (Denmark)

    Seid, Abdu K.; Berg-Beckhoff, Gabriele; Stock, Christiane

    2018-01-01

    Background: This study examined the associations between distance from residence to the nearest alcohol outlet with alcohol consumption as well as with alcohol-related harm. Methods: Data on alcohol consumption, alcohol-related harm and sociodemographics were obtained from the 2011 Danish Drug...... and Alcohol Survey (n = 5133) with respondents aged 15–79 years. The information on distances from residence to the nearest alcohol outlets was obtained from Statistics Denmark. Multiple logistic and linear regressions were used to examine the association between distances to outlets and alcohol consumption...... whereas alcohol-related harm was analysed using negative binomial regression. Results: Among women it was found that those living closer to alcohol outlets were more likely to report alcohol-related harm (p

  3. Regression with Sparse Approximations of Data

    DEFF Research Database (Denmark)

    Noorzad, Pardis; Sturm, Bob L.

    2012-01-01

    We propose sparse approximation weighted regression (SPARROW), a method for local estimation of the regression function that uses sparse approximation with a dictionary of measurements. SPARROW estimates the regression function at a point with a linear combination of a few regressands selected...... by a sparse approximation of the point in terms of the regressors. We show SPARROW can be considered a variant of \\(k\\)-nearest neighbors regression (\\(k\\)-NNR), and more generally, local polynomial kernel regression. Unlike \\(k\\)-NNR, however, SPARROW can adapt the number of regressors to use based...

  4. Regression in left ventricular mass after aortic valve replacement for chronic aortic regurgitation is unrelated to prosthetic valve size.

    Science.gov (United States)

    Brown, Morgan L; Schaff, Hartzell V; Suri, Rakesh M; Li, Zhuo; Sundt, Thoralf M; Dearani, Joseph A; Enriquez-Sarano, Maurice

    2011-08-01

    We examined the role of prosthesis-patient mismatch on left ventricular mass regression after aortic valve replacement for chronic aortic valve regurgitation. We selected patients who had complete preoperative and follow-up echocardiograms with measurement of left ventricular mass. Patients were excluded who had moderate or greater aortic valve stenosis, concomitant coronary artery bypass grafting, or mitral valve procedures. Patients' mean age was 55 ± 17 years; 21% were female. The mean preoperative indexed left ventricular mass was 150 ± 45 g/m(2). Patients with mildly (n = 44; mean indexed mass, 126 ± 15 g/m(2)), moderately (n = 31; mean indexed mass, 168 ± 11 g/m(2)), or severely (n = 15; mean indexed mass, 241 ± 34 g/m(2)) increased preoperative indexed left ventricular mass, were similar, except for lower ejection fractions, larger end-diastolic dimensions, and larger ventricular wall thicknesses in the severely enlarged group (P regression was unrelated to labeled valve size, prosthesis-patient mismatch, or measured indexed effective aortic valve area. A greater preoperative indexed left ventricular mass (P regression. Despite having greater left ventricular mass regression, patients with severe preoperative indexed left ventricular mass did not return to normal values (mean, 142 ± 25 g/m(2)). Left ventricular mass regression after aortic valve replacement for chronic aortic regurgitation is unrelated to indexed prosthetic valve area. Although incomplete, regression is greatest in patients with the largest preoperative indexed left ventricular mass. Copyright © 2011 The American Association for Thoracic Surgery. Published by Mosby, Inc. All rights reserved.

  5. Maternal or neonatal infection: association with neonatal encephalopathy outcomes.

    Science.gov (United States)

    Jenster, Meike; Bonifacio, Sonia L; Ruel, Theodore; Rogers, Elizabeth E; Tam, Emily W; Partridge, John Colin; Barkovich, Anthony James; Ferriero, Donna M; Glass, Hannah C

    2014-07-01

    Perinatal infection may potentiate brain injury among children born preterm. The objective of this study was to examine whether maternal and/or neonatal infection are associated with adverse outcomes among term neonates with encephalopathy. This study is a cohort study of 258 term newborns with encephalopathy whose clinical records were examined for signs of maternal infection (chorioamnionitis) and infant infection (sepsis). Multivariate regression was used to assess associations between infection, pattern, and severity of injury on neonatal magnetic resonance imaging, as well as neurodevelopment at 30 mo (neuromotor examination, or Bayley Scales of Infant Development, second edition mental development index encephalopathy, chorioamnionitis was associated with a lower risk of brain injury and adverse outcomes, whereas signs of neonatal sepsis carried an elevated risk. The etiology of encephalopathy and timing of infection and its associated inflammatory response may influence whether infection potentiates or mitigates injury in term newborns.

  6. Logistic regression applied to natural hazards: rare event logistic regression with replications

    Directory of Open Access Journals (Sweden)

    M. Guns

    2012-06-01

    Full Text Available Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

  7. The Association between Overweight and School Policies on Physical Activity: A Multilevel Analysis among Elementary School Youth in the PLAY-On Study

    Science.gov (United States)

    Leatherdale, Scott T.

    2010-01-01

    The objective is to examine school-level program and policy characteristics and student-level behavioural characteristics associated with being overweight. Multilevel logistic regression analysis were used to examine the school- and student-level characteristics associated with the odds of a student being overweight among 1264 Grade 5-8 students…

  8. Meta-regression analysis of the effect of trans fatty acids on low-density lipoprotein cholesterol.

    Science.gov (United States)

    Allen, Bruce C; Vincent, Melissa J; Liska, DeAnn; Haber, Lynne T

    2016-12-01

    We conducted a meta-regression of controlled clinical trial data to investigate quantitatively the relationship between dietary intake of industrial trans fatty acids (iTFA) and increased low-density lipoprotein cholesterol (LDL-C). Previous regression analyses included insufficient data to determine the nature of the dose response in the low-dose region and have nonetheless assumed a linear relationship between iTFA intake and LDL-C levels. This work contributes to the previous work by 1) including additional studies examining low-dose intake (identified using an evidence mapping procedure); 2) investigating a range of curve shapes, including both linear and nonlinear models; and 3) using Bayesian meta-regression to combine results across trials. We found that, contrary to previous assumptions, the linear model does not acceptably fit the data, while the nonlinear, S-shaped Hill model fits the data well. Based on a conservative estimate of the degree of intra-individual variability in LDL-C (0.1 mmoL/L), as an estimate of a change in LDL-C that is not adverse, a change in iTFA intake of 2.2% of energy intake (%en) (corresponding to a total iTFA intake of 2.2-2.9%en) does not cause adverse effects on LDL-C. The iTFA intake associated with this change in LDL-C is substantially higher than the average iTFA intake (0.5%en). Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  9. Regression of Ophthalmopathic Exophthalmos in Graves' Disease After Total Thyroidectomy: a Prospective Study of a Surgical Series.

    Science.gov (United States)

    Bhargav, P R K; Sabaretnam, M; Kumar, S Chandra; Zwalitha, S; Devi, N Vimala

    2017-12-01

    Autoimmune ophthalmopathy is one of the salient clinical features associated with Graves' disease. Exophthalmos is one of the commonest manifestations of Graves' associated ophthalmopathy. It is reported to regress after thyroidectomy favourably compared to radioiodine or antithyroid drug therapy. In this context, we present our experience based on a surgical series of Graves' disease. This is a prospective study of 15 patients of Graves' disease associated with ophthalmopathic exophthalmos. Preoperative and monthly postoperative evaluation of exophthalmos was done with Hertel's exophthalmometer, apart from documenting lid, extra-ocular muscle and orbital involvement. The minimum follow-up of the cohort was 12 months. The female to male ratio was 12:3 and the mean age of the subjects was 33.4 years (18-55). Exophthalmos was bilateral in 13 and unilateral in 2 patients. All the 15 patients underwent total thyroidectomy without any major morbidity. Exophthalmos regressed in 12 patients at a mean follow-up of 15.6 ± 6.4 months (14-38) and was static in 3. None of the cases had worsened ophthalmopathy at the final follow-up. Mean regression of exophthalmos was 2.1 mm (1-5). The regression was statistically significant at P value = 0.035. Surgery has a positive impact on the regression of ophthalmopathic exophthalmos associated with Graves' disease.

  10. The Association between Urinary Sodium Excretion and Metabolic Syndrome in Korean Adults from the 2010–2011 Korean National Health and Nutrition Examination Survey

    Science.gov (United States)

    Seo, Jeong Eun; Lee, Hong Soo; Lee, Sang Wha; Shim, Kyung Won; Byun, A Ri; Kim, Jung Hwa; An, Hee Jeong

    2017-01-01

    Background The sodium intake of Koreans was higher than that recommended by the World Health Organization. Urinary sodium, which is correlated with sodium intake, can be easily calculated by the Tanaka's equation. This study aimed to evaluate the association between urinary sodium and metabolic syndrome in Korean adults using the 2010–2011 Korean National Health and Nutrition Examination Survey (KNHANES). Methods A total of 5,870 participants from the 2010–2011 KNHANES were included in this study. Twenty-four hour urinary sodium was calculated by the Tanaka's equation using spot urine. Participants were divided into tertiles based on urinary sodium levels. The association between urinary sodium and metabolic syndrome was analyzed using multivariate logistic regression analysis. Results The odds ratios (ORs) and 95% confidence intervals (CIs) of metabolic syndrome for the 2nd and 3rd tertile of urinary sodium levels was 1.51 (1.16–1.97) and 1.56 (1.23–1.97) compared to the lowest tertile of urinary sodium in men. The ORs and 95% CIs of metabolic syndrome in women were 1.20 (0.95–1.51) for the 2nd tertile and 2.16 (1.68–2.78) for the 3rd tertile. These associations remained statistically significant, even after adjusting for multiple covariates such as age, education, regular exercise, smoking, and alcohol consumption. Conclusion These findings indicate that urinary sodium is significantly associated with metabolic syndrome in Korean adults. PMID:28775809

  11. Associations between active commuting and physical and mental wellbeing.

    Science.gov (United States)

    Humphreys, David K; Goodman, Anna; Ogilvie, David

    2013-08-01

    To examine whether a relationship exists between active commuting and physical and mental wellbeing. In 2009, cross-sectional postal questionnaire data were collected from a sample of working adults (aged 16 and over) in the Commuting and Health in Cambridge study. Travel behaviour and physical activity were ascertained using the Recent Physical Activity Questionnaire (RPAQ) and a seven-day travel-to-work recall instrument from which weekly time spent in active commuting (walking and cycling) was derived. Physical and mental wellbeing were assessed using the Medical Outcomes Study Short Form survey (SF-8). Associations were tested using multivariable linear regression. An association was observed between physical wellbeing (PCS-8) score and time spent in active commuting after adjustment for other physical activity (adjusted regression coefficients 0.48, 0.79 and 1.21 for 30-149 min/week, 150-224 min/week and ≥ 225 min/week respectively versus mental wellbeing (MCS-8) (p=0.52). Greater time spent actively commuting is associated with higher levels of physical wellbeing. Longitudinal studies should examine the contribution of changing levels of active commuting and other forms of physical activity to overall health and wellbeing. Copyright © 2013 Elsevier Inc. All rights reserved.

  12. The use of cognitive ability measures as explanatory variables in regression analysis.

    Science.gov (United States)

    Junker, Brian; Schofield, Lynne Steuerle; Taylor, Lowell J

    2012-12-01

    Cognitive ability measures are often taken as explanatory variables in regression analysis, e.g., as a factor affecting a market outcome such as an individual's wage, or a decision such as an individual's education acquisition. Cognitive ability is a latent construct; its true value is unobserved. Nonetheless, researchers often assume that a test score , constructed via standard psychometric practice from individuals' responses to test items, can be safely used in regression analysis. We examine problems that can arise, and suggest that an alternative approach, a "mixed effects structural equations" (MESE) model, may be more appropriate in many circumstances.

  13. Performance in the FRCR (UK) Part 2B examination: Analysis of factors associated with success

    International Nuclear Information System (INIS)

    Hawtin, K.E.; Williams, H.R.T.; McKnight, L.; Booth, T.C.

    2014-01-01

    Aim: To assess factors that influence pass rates and examination scores in the Fellowship of the Royal College of Radiologists (FRCR) 2B examination. Materials and methods: 2238 attempts at the FRCR 2B examination were evaluated between Spring 2006 and Spring 2010. Pass rates and examination scores were analysed by gender and ethnicity, and the influence of factors such as radiology training (UK versus non-UK), sitting (Spring versus Autumn), and the presence of an undergraduate or postgraduate degree were examined. Results: 1571 candidates made 2238 examination attempts, with an overall pass rate of 59.4% (63.1% at first attempt). 66.2% entrants were male; 48.8% attempts were by candidates from a UK radiology training scheme. UK candidates were significantly more likely to pass than non-UK candidates (p < 0.0001). White candidates were more likely to pass at first or second attempt than non-white candidates (p < 0.0001), but when restricted to UK entrants ethnicity did not influence success at first attempt. Overall, females were more successful than males (p < 0.001). Presence of an undergraduate (p = 0.19) or postgraduate (p = 0.80) degree did not affect pass rate at first attempt for UK candidates. However, logistic regression demonstrated that the only significant factor influencing pass rates at first attempt was whether radiology training was undertaken in the UK (p < 0.0001). A trend towards increased pass rates in autumn sittings was seen (p = 0.06), but ethnicity (p = 0.99) and gender (p = 0.41) were not significant factors. Conclusion: The FRCR 2B examination is non-discriminatory for UK candidates with respect to gender and ethnicity. Poorer performance of non-UK trained candidates is a consistent outcome in the literature. - Highlights: • Factors influencing pass rates and scores in FRCR 2B examination were assessed. • UK candidates are more likely to pass than non-UK candidates. • There is no effect of gender or ethnicity on UK

  14. Examining the Matthew effect on the motivation and ability to stay at work after heart disease.

    Science.gov (United States)

    Meland, Eivind; Grønhaug, Siri; Oystese, Kristin; Mildestvedt, Thomas

    2011-07-01

    Cardiac rehabilitation should safeguard that socioeconomic factors or other differences that affect people's cardiovascular health are not further aggravated after healthcare treatment. The study examines whether socioeconomic status, emotional problems, or the severity of disease affect people's ability to continue to work after heart disease. We also examined if these effects can be explained by differences in motivational factors. 217 patients (41 women) from the Krokeide Rehabilitation Centre in Bergen participated. Multiple linear regression analysis was used to examine motivational differences, and logistic regression analysis was used to examine whether socioeconomic factors or other differences affected people's ability to continue to work after heart disease. Self-efficacy for future work strongly impacted the likelihood of being incapacitated for work during the 2-year follow-up. The household's total income and emotional problems were statistically significant related to patients dropping out from work in the course of the observation. The association between emotional problems and future work was mediated by motivational problems. The relation between income and future incapacity for work could not be explained by motivational factors. The study shows a clear Matthew effect on people's ability to continue to work after heart disease as low-income groups and people with emotional problems are more at risk of dropping out of work. This Matthew effect was, however, only explained by the motivational difficulties for the association between emotional distress and dropping out of work and not for the impact of household income on the likelihood of leaving work.

  15. The relationship between clinician turnover and adolescent treatment outcomes: An examination from the client perspective

    Science.gov (United States)

    Garner, Bryan R.; Funk, Rodney R.; Hunter, Brooke D.

    2012-01-01

    The turnover of substance use disorder (SUD) treatment staff has been assumed to adversely impact treatment effectiveness, yet only limited research has empirically examined this assumption. Representing an extension of prior organizational-level analyses of the impact of staff turnover on client outcomes, this study examined the impact of SUD clinician turnover on adolescent treatment outcomes using a client perspective. Multilevel regression analysis did reveal that relative to those adolescents who did not experience clinician turnover, adolescents who experienced both direct and indirect clinician turnover reported a significantly higher percentage of days using alcohol or drugs at 6-month follow-up. However, clinician turnover was not found to have significant associations (negative or positive) with the other five treatment outcomes examined (e.g., substance-related problems, involvement in illegal activity). Thus, consistent with our prior findings, the current study provides additional evidence that turnover of SUD clinicians is not necessarily associated with adverse treatment outcomes. PMID:23083980

  16. Post-processing through linear regression

    Science.gov (United States)

    van Schaeybroeck, B.; Vannitsem, S.

    2011-03-01

    Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS) method, a new time-dependent Tikhonov regularization (TDTR) method, the total least-square method, a new geometric-mean regression (GM), a recently introduced error-in-variables (EVMOS) method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified. These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise). At long lead times the regression schemes (EVMOS, TDTR) which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.

  17. Examining Youth Dual and Polytobacco Use with E-Cigarettes

    Directory of Open Access Journals (Sweden)

    Youn Ok Lee

    2018-04-01

    Full Text Available E-cigarettes and other non-cigarette tobacco products are increasingly popular among youth. Little is known to inform public health efforts to reduce youth use. We examined psychosocial correlates of single and multiple tobacco product use among youth e-cigarette users. Data were from the 2014 Florida Youth Tobacco Survey (N = 69,923, a representative sample of Florida middle and high school students. Associations between combinations of e-cigarette, cigarette and other tobacco product (OTP use and psychosocial variables were examined using multinomial logistic regression with an analytic sample of N = 2756. Most e-cigarette-using youth used at least one other product (81%. Perceiving cigarettes as easy to quit was significantly associated with greater likelihood of combined e-cigarette/OTP use (relative risk ratio (RRR = 2.51, p < 0.001 and combined e-cigarette/cigarette/OTP use (RRR = 3.20, p < 0.0001. Thinking you will be smoking cigarettes in 5 years was associated with product combinations that include cigarettes. Tobacco company marketing receptivity was associated with multiple product user types. Given that specific psychosocial factors put youth at risk for concurrent use of e-cigarettes with tobacco products, public health efforts should address polytobacco use specifically, instead of individual product use. Youth perceptions about the ease of quitting cigarettes, intentions to continue smoking cigarettes and receptivity to tobacco company marketing are promising areas for messaging aimed at reducing e-cigarette polytobacco product use.

  18. Examining Youth Dual and Polytobacco Use with E-Cigarettes.

    Science.gov (United States)

    Lee, Youn Ok; Pepper, Jessica K; MacMonegle, Anna J; Nonnemaker, James M; Duke, Jennifer C; Porter, Lauren

    2018-04-08

    E-cigarettes and other non-cigarette tobacco products are increasingly popular among youth. Little is known to inform public health efforts to reduce youth use. We examined psychosocial correlates of single and multiple tobacco product use among youth e-cigarette users. Data were from the 2014 Florida Youth Tobacco Survey ( N = 69,923), a representative sample of Florida middle and high school students. Associations between combinations of e-cigarette, cigarette and other tobacco product (OTP) use and psychosocial variables were examined using multinomial logistic regression with an analytic sample of N = 2756. Most e-cigarette-using youth used at least one other product (81%). Perceiving cigarettes as easy to quit was significantly associated with greater likelihood of combined e-cigarette/OTP use (relative risk ratio (RRR) = 2.51, p < 0.001) and combined e-cigarette/cigarette/OTP use (RRR = 3.20, p < 0.0001). Thinking you will be smoking cigarettes in 5 years was associated with product combinations that include cigarettes. Tobacco company marketing receptivity was associated with multiple product user types. Given that specific psychosocial factors put youth at risk for concurrent use of e-cigarettes with tobacco products, public health efforts should address polytobacco use specifically, instead of individual product use. Youth perceptions about the ease of quitting cigarettes, intentions to continue smoking cigarettes and receptivity to tobacco company marketing are promising areas for messaging aimed at reducing e-cigarette polytobacco product use.

  19. Active commuting among K-12 educators: a study examining walking and biking to work.

    Science.gov (United States)

    Bopp, Melissa; Hastmann, Tanis J; Norton, Alyssa N

    2013-01-01

    Walking and biking to work, active commuting (AC) is associated with many health benefits, though rates of AC remain low in the US. K-12 educators represent a significant portion of the workforce, and employee health and associated costs may have significant economic impact. Therefore, the purpose of this study was to examine the current rates of AC and factors associated with AC among K-12 educators. A volunteer sample of K-12 educators (n = 437) was recruited to participate in an online survey. Participants responded about AC patterns and social ecological influences on AC (individual, interpersonal, institutional, community, and environmental factors). t-tests and ANOVAs examined trends in AC, and Pearson correlations examined the relationship between AC and dependent variables. Multiple regression analysis determined the relative influence of individual, interpersonal, institutional, community, and environmental levels on AC. Participants actively commuted 0.51 ± 1.93 times/week. There were several individual, interpersonal, institutional, community, and environmental factors significantly related to AC. The full model explained 60.8% of the variance in AC behavior. This study provides insight on the factors that determine K-12 educators mode of commute and provide some insight for employee wellness among this population.

  20. Active Commuting among K-12 Educators: A Study Examining Walking and Biking to Work

    Directory of Open Access Journals (Sweden)

    Melissa Bopp

    2013-01-01

    Full Text Available Background. Walking and biking to work, active commuting (AC is associated with many health benefits, though rates of AC remain low in the US. K-12 educators represent a significant portion of the workforce, and employee health and associated costs may have significant economic impact. Therefore, the purpose of this study was to examine the current rates of AC and factors associated with AC among K-12 educators. Methods. A volunteer sample of K-12 educators ( was recruited to participate in an online survey. Participants responded about AC patterns and social ecological influences on AC (individual, interpersonal, institutional, community, and environmental factors. -tests and ANOVAs examined trends in AC, and Pearson correlations examined the relationship between AC and dependent variables. Multiple regression analysis determined the relative influence of individual, interpersonal, institutional, community, and environmental levels on AC. Results. Participants actively commuted times/week. There were several individual, interpersonal, institutional, community, and environmental factors significantly related to AC. The full model explained 60.8% of the variance in AC behavior. Conclusions. This study provides insight on the factors that determine K-12 educators mode of commute and provide some insight for employee wellness among this population.

  1. Unemployment and psychosocial outcomes to age 30: A fixed-effects regression analysis.

    Science.gov (United States)

    Fergusson, David M; McLeod, Geraldine F; Horwood, L John

    2014-08-01

    We aimed to examine the associations between exposure to unemployment and psychosocial outcomes over the period from 16 to 30 years, using data from a well-studied birth cohort. Data were collected over the course of the Christchurch Health and Development Study, a longitudinal study of a birth cohort of 1265 children, born in Christchurch in 1977, who have been studied to age 30. Assessments of unemployment and psychosocial outcomes (mental health, substance abuse/dependence, criminal offending, adverse life events and life satisfaction) were obtained at ages 18, 21, 25 and 30. Prior to adjustment, an increasing duration of unemployment was associated with significant increases in the risk of all psychosocial outcomes. These associations were adjusted for confounding using conditional, fixed-effects regression techniques. The analyses showed significant (p unemployment and major depression (p = 0.05), alcohol abuse/dependence (p = 0.043), illicit substance abuse/dependence (p = 0.017), property/violent offending (p unemployment. The findings suggested that the association between unemployment and psychosocial outcomes was likely to involve a causal process in which unemployment led to increased risks of adverse psychosocial outcomes. Effect sizes were estimated using attributable risk; exposure to unemployment accounted for between 4.2 and 14.0% (median 10.8%) of the risk of experiencing the significant psychosocial outcomes. The findings of this study suggest that exposure to unemployment had small but pervasive effects on psychosocial adjustment in adolescence and young adulthood. © The Royal Australian and New Zealand College of Psychiatrists 2014.

  2. Regression modeling methods, theory, and computation with SAS

    CERN Document Server

    Panik, Michael

    2009-01-01

    Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs.The text presents the popular ordinary least squares (OLS) approach before introducing many alternative regression methods. It covers nonparametric regression, logistic regression (including Poisson regression), Bayesian regression, robust regression, fuzzy regression, random coefficients regression,

  3. Better Autologistic Regression

    Directory of Open Access Journals (Sweden)

    Mark A. Wolters

    2017-11-01

    Full Text Available Autologistic regression is an important probability model for dichotomous random variables observed along with covariate information. It has been used in various fields for analyzing binary data possessing spatial or network structure. The model can be viewed as an extension of the autologistic model (also known as the Ising model, quadratic exponential binary distribution, or Boltzmann machine to include covariates. It can also be viewed as an extension of logistic regression to handle responses that are not independent. Not all authors use exactly the same form of the autologistic regression model. Variations of the model differ in two respects. First, the variable coding—the two numbers used to represent the two possible states of the variables—might differ. Common coding choices are (zero, one and (minus one, plus one. Second, the model might appear in either of two algebraic forms: a standard form, or a recently proposed centered form. Little attention has been paid to the effect of these differences, and the literature shows ambiguity about their importance. It is shown here that changes to either coding or centering in fact produce distinct, non-nested probability models. Theoretical results, numerical studies, and analysis of an ecological data set all show that the differences among the models can be large and practically significant. Understanding the nature of the differences and making appropriate modeling choices can lead to significantly improved autologistic regression analyses. The results strongly suggest that the standard model with plus/minus coding, which we call the symmetric autologistic model, is the most natural choice among the autologistic variants.

  4. The Association of Family Influence and Initial Interest in Science

    Science.gov (United States)

    Dabney, Katherine P.; Chakraverty, Devasmita; Tai, Robert H.

    2013-01-01

    With recent attention to improving scientific workforce development and student achievement, there has been a rise in effort to understand and encourage student engagement in physical science. This study examines the association of family influence and initial interest in science through multiple and logistic regression models. Research questions…

  5. Serum Folate Shows an Inverse Association with Blood Pressure in a Cohort of Chinese Women of Childbearing Age: A Cross-Sectional Study.

    Directory of Open Access Journals (Sweden)

    Minxue Shen

    Full Text Available It has been reported that higher folate intake from food and supplementation is associated with decreased blood pressure (BP. The association between serum folate concentration and BP has been examined in few studies. We aim to examine the association between serum folate and BP levels in a cohort of young Chinese women.We used the baseline data from a pre-conception cohort of women of childbearing age in Liuyang, China, for this study. Demographic data were collected by structured interview. Serum folate concentration was measured by immunoassay, and homocysteine, blood glucose, triglyceride and total cholesterol were measured through standardized clinical procedures. Multiple linear regression and principal component regression model were applied in the analysis.A total of 1,532 healthy normotensive non-pregnant women were included in the final analysis. The mean concentration of serum folate was 7.5 ± 5.4 nmol/L and 55% of the women presented with folate deficiency (< 6.8 nmol/L. Multiple linear regression and principal component regression showed that serum folate levels were inversely associated with systolic and diastolic BP, after adjusting for demographic, anthropometric, and biochemical factors.Serum folate is inversely associated with BP in non-pregnant women of childbearing age with high prevalence of folate deficiency.

  6. Semiparametric regression during 2003–2007

    KAUST Repository

    Ruppert, David; Wand, M.P.; Carroll, Raymond J.

    2009-01-01

    Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.

  7. Unbalanced Regressions and the Predictive Equation

    DEFF Research Database (Denmark)

    Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo

    Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness in the theoreti......Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness...

  8. Nicotine dependence matters: examining longitudinal association between smoking and physical activity among Canadian adults.

    Science.gov (United States)

    Azagba, Sunday; Asbridge, Mark

    2013-11-01

    A number of studies point to the inverse relationship between physical activity and smoking; however, none has examined the role of nicotine dependence in physical activity participation among smokers. This study examined whether levels of nicotine dependence modify the association between leisure time physical activity and smoking status. The study used longitudinal data on 6795 adults from the Canadian National Population Health Survey (2004-2010). Generalized estimating equations were used to examine the association between physical activity, smoking, and nicotine dependence. We found that nicotine dependent smokers were significantly less likely to be physically active compared to non-smokers. Specifically, using the Fagerstrom Test for Nicotine Dependence, nicotine dependent smokers (OR 0.65, 95% CI 0.55-0.76) were less likely to be physically active while no significant difference was found for non-dependent smokers (OR 0.90, 95% CI 0.80-1.02) compared to non-smokers. Nicotine dependence matters in shaping engagement in physical activity among daily smokers. Efforts directed at promoting smoking cessation through nicotine dependence treatment intervention may provide additional benefits to health and well-being through an increased participation in physical activity. © 2013.

  9. An Investigation of the Fit of Linear Regression Models to Data from an SAT[R] Validity Study. Research Report 2011-3

    Science.gov (United States)

    Kobrin, Jennifer L.; Sinharay, Sandip; Haberman, Shelby J.; Chajewski, Michael

    2011-01-01

    This study examined the adequacy of a multiple linear regression model for predicting first-year college grade point average (FYGPA) using SAT[R] scores and high school grade point average (HSGPA). A variety of techniques, both graphical and statistical, were used to examine if it is possible to improve on the linear regression model. The results…

  10. Risk factors for violence in psychosis: systematic review and meta-regression analysis of 110 studies.

    Directory of Open Access Journals (Sweden)

    Katrina Witt

    Full Text Available Previous reviews on risk and protective factors for violence in psychosis have produced contrasting findings. There is therefore a need to clarify the direction and strength of association of risk and protective factors for violent outcomes in individuals with psychosis.We conducted a systematic review and meta-analysis using 6 electronic databases (CINAHL, EBSCO, EMBASE, Global Health, PsycINFO, PUBMED and Google Scholar. Studies were identified that reported factors associated with violence in adults diagnosed, using DSM or ICD criteria, with schizophrenia and other psychoses. We considered non-English language studies and dissertations. Risk and protective factors were meta-analysed if reported in three or more primary studies. Meta-regression examined sources of heterogeneity. A novel meta-epidemiological approach was used to group similar risk factors into one of 10 domains. Sub-group analyses were then used to investigate whether risk domains differed for studies reporting severe violence (rather than aggression or hostility and studies based in inpatient (rather than outpatient settings.There were 110 eligible studies reporting on 45,533 individuals, 8,439 (18.5% of whom were violent. A total of 39,995 (87.8% were diagnosed with schizophrenia, 209 (0.4% were diagnosed with bipolar disorder, and 5,329 (11.8% were diagnosed with other psychoses. Dynamic (or modifiable risk factors included hostile behaviour, recent drug misuse, non-adherence with psychological therapies (p values<0.001, higher poor impulse control scores, recent substance misuse, recent alcohol misuse (p values<0.01, and non-adherence with medication (p value <0.05. We also examined a number of static factors, the strongest of which were criminal history factors. When restricting outcomes to severe violence, these associations did not change materially. In studies investigating inpatient violence, associations differed in strength but not direction.Certain dynamic risk

  11. Association of Magnesium Intake with High Blood Pressure in Korean Adults: Korea National Health and Nutrition Examination Survey 2007–2009

    Science.gov (United States)

    Choi, Mi-Kyeong; Bae, Yun Jung

    2015-01-01

    Background Magnesium is known to lower the risk of cardiovascular disease. However, studies on its relationship with hypertension, a single and common cause of various chronic diseases, are limited and their findings are not consistent. The purpose of the present study is to identify the relationship between magnesium intake and high blood pressure (HBP) risk in Koreans. Methods This research is a cross-sectional study based on the 2007~2009 Korean National Health and Nutritional Examination Survey data. This study investigated 11,685 adults aged over 20 to examine their general characteristics, anthropometry and blood pressure. Daily magnesium intake was analyzed using the 24-hour dietary recall method. To calculate the odds ratio (OR) of HBP risk (130/85 mmHg or over) according to the quartile of magnesium intake (mg/1000kcal) together with its 95% confidence interval (CI), multivariable logistic regression analysis was performed. Results No significant association between dietary magnesium intake and the risk of HBP was found. In obese women, particularly, after adjusting relevant factors, the adjusted odds ratio of HBP prevalence in the highest magnesium intake quartile was 0.40 compared with the lowest magnesium intake quartile (95% CI = 0.25~0.63, P for trend = 0.0014). Women, especially obese women, were found to have a negative relationship of magnesium intake with HBP. Conclusions The present results indicate that sufficient magnesium intake could be useful in decreasing the high blood pressure risk of obese women. PMID:26075385

  12. Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?

    Science.gov (United States)

    Lin, Yingzhi; Deng, Xiangzheng; Li, Xing; Ma, Enjun

    2014-12-01

    Spatially explicit simulation of land use change is the basis for estimating the effects of land use and cover change on energy fluxes, ecology and the environment. At the pixel level, logistic regression is one of the most common approaches used in spatially explicit land use allocation models to determine the relationship between land use and its causal factors in driving land use change, and thereby to evaluate land use suitability. However, these models have a drawback in that they do not determine/allocate land use based on the direct relationship between land use change and its driving factors. Consequently, a multinomial logistic regression method was introduced to address this flaw, and thereby, judge the suitability of a type of land use in any given pixel in a case study area of the Jiangxi Province, China. A comparison of the two regression methods indicated that the proportion of correctly allocated pixels using multinomial logistic regression was 92.98%, which was 8.47% higher than that obtained using logistic regression. Paired t-test results also showed that pixels were more clearly distinguished by multinomial logistic regression than by logistic regression. In conclusion, multinomial logistic regression is a more efficient and accurate method for the spatial allocation of land use changes. The application of this method in future land use change studies may improve the accuracy of predicting the effects of land use and cover change on energy fluxes, ecology, and environment.

  13. Interpretation of commonly used statistical regression models.

    Science.gov (United States)

    Kasza, Jessica; Wolfe, Rory

    2014-01-01

    A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

  14. Linear regression

    CERN Document Server

    Olive, David J

    2017-01-01

    This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...

  15. Regression modeling of ground-water flow

    Science.gov (United States)

    Cooley, R.L.; Naff, R.L.

    1985-01-01

    Nonlinear multiple regression methods are developed to model and analyze groundwater flow systems. Complete descriptions of regression methodology as applied to groundwater flow models allow scientists and engineers engaged in flow modeling to apply the methods to a wide range of problems. Organization of the text proceeds from an introduction that discusses the general topic of groundwater flow modeling, to a review of basic statistics necessary to properly apply regression techniques, and then to the main topic: exposition and use of linear and nonlinear regression to model groundwater flow. Statistical procedures are given to analyze and use the regression models. A number of exercises and answers are included to exercise the student on nearly all the methods that are presented for modeling and statistical analysis. Three computer programs implement the more complex methods. These three are a general two-dimensional, steady-state regression model for flow in an anisotropic, heterogeneous porous medium, a program to calculate a measure of model nonlinearity with respect to the regression parameters, and a program to analyze model errors in computed dependent variables such as hydraulic head. (USGS)

  16. Examining the Association Between Different Aspects of Socioeconomic Status, Race, and Disability in Hawaii.

    Science.gov (United States)

    Seto, Jason; Davis, James; Taira, Deborah Ann

    2018-02-20

    Socioeconomic status and race/ethnicity are known to be associated with health disparities. This study used data (2010-2014) from the American Community Survey. Respondents over age 30 from Hawaii were included (n = 44,921). Outcome variables were self-reported disability in vision, hearing, ambulatory function, self-care, independent living, or cognitive function. Four measures of socioeconomic status were personal income, average income for the area, income inequality for area, and education. This study used multivariable logistic regression to predict disability by race/ethnicity and socioeconomic status, controlling for age and gender. All four measures of socioeconomic status were significant predictors of at least one type of disability after adjustment for age, gender, and other measures of socioeconomic status. Higher education was significantly related to having every type of disability. Similarly, people with high personal income were less likely to have each type of disability than those with middle income, and those with low income were more likely to have all disabilities except hearing. Income inequality was significantly associated with half the disabilities. Low area income was significantly associated with increased vision-related disability, while high income was associated with less likelihood of hearing-related disability. Native Hawaiians were significantly more likely to report having a disability than Filipinos and Chinese for all six types of disability, Japanese for four, and whites for two, after adjustment. These results suggest that in order to reduce health disparities for Native Hawaiians, as well as other ethnic groups, a range of socioeconomic factors need to be addressed.

  17. Examining the association between attention deficit hyperactivity disorder and substance use disorders: A familial risk analysis.

    Science.gov (United States)

    Yule, Amy M; Martelon, MaryKate; Faraone, Stephen V; Carrellas, Nicholas; Wilens, Timothy E; Biederman, Joseph

    2017-02-01

    The main aim of this study was to use familial risk analysis to examine the association between attention deficit hyperactivity disorder (ADHD) and substance use disorders (SUDs) attending to sex effects and the specificity of alcohol and drug use disorder risks. Subjects were derived from two longitudinal case-control family studies of probands aged 6-17 years with and without DSM-III-R ADHD of both sexes and their first degree relatives followed from childhood onto young adult years. Cox proportional hazard models were used to estimate rates of ADHD and SUDs (any SUD, alcohol dependence, and drug dependence). Logistic regression was used to test both co-segregation and assortative mating. Our sample included 404 probands (ADHD: 112 boys and 96 girls; Control: 105 boys and 91 girls) and their 1336 relatives. SUDs in probands increased the risk for SUDs in relatives irrespective of ADHD status. The risk for dependence to drug or alcohol in relatives was non-specific. There was evidence that even in the absence of a SUD in the proband, ADHD by itself increased the risk of SUDs in relatives. Proband sex did not moderate the familial relationship between ADHD and SUDs. There was evidence of co-segregation between ADHD and SUD. Findings indicate that various independent pathways are involved in the transmission of SUD in ADHD and that these risks were not moderated by proband sex. ADHD children and siblings should benefit from preventive and early intervention strategies to decrease their elevated risk for developing a SUD. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Predicting exposure-response associations of ambient particulate matter with mortality in 73 Chinese cities

    International Nuclear Information System (INIS)

    Madaniyazi, Lina; Guo, Yuming; Chen, Renjie; Kan, Haidong; Tong, Shilu

    2016-01-01

    Estimating the burden of mortality associated with particulates requires knowledge of exposure-response associations. However, the evidence on exposure-response associations is limited in many cities, especially in developing countries. In this study, we predicted associations of particulates smaller than 10 μm in aerodynamic diameter (PM_1_0) with mortality in 73 Chinese cities. The meta-regression model was used to test and quantify which city-specific characteristics contributed significantly to the heterogeneity of PM_1_0-mortality associations for 16 Chinese cities. Then, those city-specific characteristics with statistically significant regression coefficients were treated as independent variables to build multivariate meta-regression models. The model with the best fitness was used to predict PM_1_0-mortality associations in 73 Chinese cities in 2010. Mean temperature, PM_1_0 concentration and green space per capita could best explain the heterogeneity in PM_1_0-mortality associations. Based on city-specific characteristics, we were able to develop multivariate meta-regression models to predict associations between air pollutants and health outcomes reasonably well. - Highlights: • The heterogeneity was examined in PM_1_0-mortality associations among Chinese cities. • Temperature, PM_1_0 and green space could best explain the heterogeneity. • PM_1_0-mortality associations were predicted for 73 Chinese cities. - This study provides a practical way to assess exposure-response associations and evaluate the burden of mortality in areas with insufficient data.

  19. Post-processing through linear regression

    Directory of Open Access Journals (Sweden)

    B. Van Schaeybroeck

    2011-03-01

    Full Text Available Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS method, a new time-dependent Tikhonov regularization (TDTR method, the total least-square method, a new geometric-mean regression (GM, a recently introduced error-in-variables (EVMOS method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified.

    These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise. At long lead times the regression schemes (EVMOS, TDTR which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.

  20. A comparison of random forest regression and multiple linear regression for prediction in neuroscience.

    Science.gov (United States)

    Smith, Paul F; Ganesh, Siva; Liu, Ping

    2013-10-30

    Regression is a common statistical tool for prediction in neuroscience. However, linear regression is by far the most common form of regression used, with regression trees receiving comparatively little attention. In this study, the results of conventional multiple linear regression (MLR) were compared with those of random forest regression (RFR), in the prediction of the concentrations of 9 neurochemicals in the vestibular nucleus complex and cerebellum that are part of the l-arginine biochemical pathway (agmatine, putrescine, spermidine, spermine, l-arginine, l-ornithine, l-citrulline, glutamate and γ-aminobutyric acid (GABA)). The R(2) values for the MLRs were higher than the proportion of variance explained values for the RFRs: 6/9 of them were ≥ 0.70 compared to 4/9 for RFRs. Even the variables that had the lowest R(2) values for the MLRs, e.g. ornithine (0.50) and glutamate (0.61), had much lower proportion of variance explained values for the RFRs (0.27 and 0.49, respectively). The RSE values for the MLRs were lower than those for the RFRs in all but two cases. In general, MLRs seemed to be superior to the RFRs in terms of predictive value and error. In the case of this data set, MLR appeared to be superior to RFR in terms of its explanatory value and error. This result suggests that MLR may have advantages over RFR for prediction in neuroscience with this kind of data set, but that RFR can still have good predictive value in some cases. Copyright © 2013 Elsevier B.V. All rights reserved.

  1. Logistic regression applied to natural hazards: rare event logistic regression with replications

    OpenAIRE

    Guns, M.; Vanacker, Veerle

    2012-01-01

    Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logisti...

  2. A consistent framework for Horton regression statistics that leads to a modified Hack's law

    Science.gov (United States)

    Furey, P.R.; Troutman, B.M.

    2008-01-01

    A statistical framework is introduced that resolves important problems with the interpretation and use of traditional Horton regression statistics. The framework is based on a univariate regression model that leads to an alternative expression for Horton ratio, connects Horton regression statistics to distributional simple scaling, and improves the accuracy in estimating Horton plot parameters. The model is used to examine data for drainage area A and mainstream length L from two groups of basins located in different physiographic settings. Results show that confidence intervals for the Horton plot regression statistics are quite wide. Nonetheless, an analysis of covariance shows that regression intercepts, but not regression slopes, can be used to distinguish between basin groups. The univariate model is generalized to include n > 1 dependent variables. For the case where the dependent variables represent ln A and ln L, the generalized model performs somewhat better at distinguishing between basin groups than two separate univariate models. The generalized model leads to a modification of Hack's law where L depends on both A and Strahler order ??. Data show that ?? plays a statistically significant role in the modified Hack's law expression. ?? 2008 Elsevier B.V.

  3. Unique Associations between Peer Relations and Social Anxiety in Early Adolescence

    Science.gov (United States)

    Flanagan, Kelly S.; Erath, Stephen A.; Bierman, Karen L.

    2008-01-01

    This study examined the unique associations between feelings of social anxiety and multiple dimensions of peer relations (positive peer nominations, peer- and self-reported peer victimization, and self-reported friendship quality) among 383 sixth- and seventh-grade students. Hierarchical regression analysis provided evidence for the unique…

  4. Associations between bar patron alcohol intoxication and tobacco smoking.

    Science.gov (United States)

    Rossheim, Matthew E; Thombs, Dennis L; O'Mara, Ryan J; Bastian, Nicholas; Suzuki, Sumihiro

    2013-11-01

    To examine the event-specific relationship between alcohol intoxication and nighttime tobacco smoking among college bar patrons. In this secondary analysis of existing data, we examined event-specific associations between self-report measures of tobacco smoking and breath alcohol concentration (BrAC) readings obtained from 424 patrons exiting on-premise drinking establishments. In a multivariable logistic regression analysis, acute alcohol intoxication was positively associated with same-night incidents of smoking tobacco, adjusting for the effects of established smoking practices and other potential confounders. This investigation is the first known study using data collected in an on-premise drinking setting to link alcohol intoxication to specific incidents of tobacco smoking.

  5. A Seemingly Unrelated Poisson Regression Model

    OpenAIRE

    King, Gary

    1989-01-01

    This article introduces a new estimator for the analysis of two contemporaneously correlated endogenous event count variables. This seemingly unrelated Poisson regression model (SUPREME) estimator combines the efficiencies created by single equation Poisson regression model estimators and insights from "seemingly unrelated" linear regression models.

  6. Impact of aortic prosthesis-patient mismatch on left ventricular mass regression.

    Science.gov (United States)

    Alassal, Mohamed A; Ibrahim, Bedir M; Elsadeck, Nabil

    2014-06-01

    Prostheses used for aortic valve replacement may be small in relation to body size, causing prosthesis-patient mismatch and delaying left ventricular mass regression. This study examined the effect of prosthesis-patient mismatch on regression of left ventricular mass after aortic valve replacement. We prospectively studied 96 patients undergoing aortic valve replacement between 2007 and 2012. Mean and peak gradients and indexed effective orifice area were measured by transthoracic echocardiography at 3 and 6 months postoperatively. Patient-prosthesis mismatch was defined as indexed effective orifice area ≤0.85 cm(2)·m(-2). Moderate prosthesis-patient mismatch was present in 25% of patients. There were no significant differences in demographic and operative data between patients with and without prosthesis-patient mismatch. Left ventricular dimensions, posterior wall thickness, transvalvular gradients, and left ventricular mass decreased significantly after aortic valve replacement in both groups. The interventricular septal diameter and left ventricular mass index regression, and left ventricular ejection fraction were better in patients without prosthesis-patient mismatch. There was a significant positive correlation between the postoperative indexed effective orifice area of each valve prosthesis and the rate of left ventricular mass regression. Prosthesis-patient mismatch leads to higher transprosthetic gradients and impaired left ventricular mass regression. A small-sized valve prosthesis does not necessarily result in prosthesis-patient mismatch, and may be perfectly adequate in patient with small body size. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  7. Challenges Associated with Estimating Utility in Wet Age-Related Macular Degeneration: A Novel Regression Analysis to Capture the Bilateral Nature of the Disease.

    Science.gov (United States)

    Hodgson, Robert; Reason, Timothy; Trueman, David; Wickstead, Rose; Kusel, Jeanette; Jasilek, Adam; Claxton, Lindsay; Taylor, Matthew; Pulikottil-Jacob, Ruth

    2017-10-01

    The estimation of utility values for the economic evaluation of therapies for wet age-related macular degeneration (AMD) is a particular challenge. Previous economic models in wet AMD have been criticized for failing to capture the bilateral nature of wet AMD by modelling visual acuity (VA) and utility values associated with the better-seeing eye only. Here we present a de novo regression analysis using generalized estimating equations (GEE) applied to a previous dataset of time trade-off (TTO)-derived utility values from a sample of the UK population that wore contact lenses to simulate visual deterioration in wet AMD. This analysis allows utility values to be estimated as a function of VA in both the better-seeing eye (BSE) and worse-seeing eye (WSE). VAs in both the BSE and WSE were found to be statistically significant (p regression analysis provides a possible source of utility values to allow future economic models to capture the quality of life impact of changes in VA in both eyes. Novartis Pharmaceuticals UK Limited.

  8. Multinomial logistic regression analysis for differentiating 3 treatment outcome trajectory groups for headache-associated disability.

    Science.gov (United States)

    Lewis, Kristin Nicole; Heckman, Bernadette Davantes; Himawan, Lina

    2011-08-01

    Growth mixture modeling (GMM) identified latent groups based on treatment outcome trajectories of headache disability measures in patients in headache subspecialty treatment clinics. Using a longitudinal design, 219 patients in headache subspecialty clinics in 4 large cities throughout Ohio provided data on their headache disability at pretreatment and 3 follow-up assessments. GMM identified 3 treatment outcome trajectory groups: (1) patients who initiated treatment with elevated disability levels and who reported statistically significant reductions in headache disability (high-disability improvers; 11%); (2) patients who initiated treatment with elevated disability but who reported no reductions in disability (high-disability nonimprovers; 34%); and (3) patients who initiated treatment with moderate disability and who reported statistically significant reductions in headache disability (moderate-disability improvers; 55%). Based on the final multinomial logistic regression model, a dichotomized treatment appointment attendance variable was a statistically significant predictor for differentiating high-disability improvers from high-disability nonimprovers. Three-fourths of patients who initiated treatment with elevated disability levels did not report reductions in disability after 5 months of treatment with new preventive pharmacotherapies. Preventive headache agents may be most efficacious for patients with moderate levels of disability and for patients with high disability levels who attend all treatment appointments. Copyright © 2011 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

  9. Recursive Algorithm For Linear Regression

    Science.gov (United States)

    Varanasi, S. V.

    1988-01-01

    Order of model determined easily. Linear-regression algorithhm includes recursive equations for coefficients of model of increased order. Algorithm eliminates duplicative calculations, facilitates search for minimum order of linear-regression model fitting set of data satisfactory.

  10. Applied regression analysis a research tool

    CERN Document Server

    Pantula, Sastry; Dickey, David

    1998-01-01

    Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool. Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to...

  11. Predictors of Heavy Stethoscope Contamination Following a Physical Examination.

    Science.gov (United States)

    Tschopp, Clément; Schneider, Alexis; Longtin, Yves; Renzi, Gesuele; Schrenzel, Jacques; Pittet, Didier

    2016-06-01

    BACKGROUND The degree of bacterial contamination of stethoscopes can vary significantly following a physical examination. OBJECTIVE To conduct a prospective study to investigate the impact of various environmental and patient characteristics on stethoscope contamination. METHODS Following a standardized examination, the levels of bacterial contamination of 4 regions of the physicians' hands and 2 sections of the stethoscopes, and the presence of different pathogenic bacteria, were assessed. Predictors of heavy stethoscope contamination were identified through multivariate logistic regression. RESULTS In total, 392 surfaces were sampled following examination of 56 patients. The microorganisms most frequently recovered from hands and stethoscopes were Enterococcus spp. (29% and 20%, respectively) and Enterobacteriaceae (16% and 7%, respectively). Staphylococcus aureus (either methicillin susceptible or resistant), extended-spectrum β-lactamase-producing Enterobacteriaceae, and Acinetobacter baumannii were recovered from 4%-9% of the samples from either hands or stethoscopes. There was a correlation between the likelihood of recovering these pathogens from the stethoscopes vs from the physicians' hands (ρ=0.79; P=.04). The level of patient's skin contamination was an independent predictor of contamination of the stethoscope diaphragm (adjusted odds ratio [aOR], 1.001; P=.007) and tube (aOR, 1.001; P=.003). Male sex (aOR, 28.24; P=.01) and reception of a bed bath (aOR, 7.52; P=.048) were also independently associated with heavy tube contamination. CONCLUSIONS Stethoscope contamination following a single physical examination is not negligible and is associated with the level of contamination of the patient's skin. Prevention of pathogen dissemination is needed. Infect Control Hosp Epidemiol 2016;37:673-679.

  12. Pulmonary and Critical Care In-Service Training Examination Score as a Predictor of Board Certification Examination Performance.

    Science.gov (United States)

    Kempainen, Robert R; Hess, Brian J; Addrizzo-Harris, Doreen J; Schaad, Douglas C; Scott, Craig S; Carlin, Brian W; Shaw, Robert C; Duhigg, Lauren; Lipner, Rebecca S

    2016-04-01

    Most trainees in combined pulmonary and critical care medicine fellowship programs complete in-service training examinations (ITEs) that test knowledge in both disciplines. Whether ITE scores predict performance on the American Board of Internal Medicine Pulmonary Disease Certification Examination and Critical Care Medicine Certification Examination is unknown. To determine whether pulmonary and critical care medicine ITE scores predict performance on subspecialty board certification examinations independently of trainee demographics, program director competency ratings, fellowship program characteristics, and prior medical knowledge assessments. First- and second-year fellows who were enrolled in the study between 2008 and 2012 completed a questionnaire encompassing demographics and fellowship training characteristics. These data and ITE scores were matched to fellows' subsequent scores on subspecialty certification examinations, program director ratings, and previous scores on their American Board of Internal Medicine Internal Medicine Certification Examination. Multiple linear regression and logistic regression were used to identify independent predictors of subspecialty certification examination scores and likelihood of passing the examinations, respectively. Of eligible fellows, 82.4% enrolled in the study. The ITE score for second-year fellows was matched to their certification examination scores, which yielded 1,484 physicians for pulmonary disease and 1,331 for critical care medicine. Second-year fellows' ITE scores (β = 0.24, P ITE odds ratio, 1.12 [95% confidence interval, 1.07-1.16]; Internal Medicine Certification Examination odds ratio, 1.01 [95% confidence interval, 1.01-1.02]). Similar results were obtained for predicting Critical Care Medicine Certification Examination scores and for passing the examination. The predictive value of ITE scores among first-year fellows on the subspecialty certification examinations was comparable to second

  13. Standards for Standardized Logistic Regression Coefficients

    Science.gov (United States)

    Menard, Scott

    2011-01-01

    Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…

  14. [Application of negative binomial regression and modified Poisson regression in the research of risk factors for injury frequency].

    Science.gov (United States)

    Cao, Qingqing; Wu, Zhenqiang; Sun, Ying; Wang, Tiezhu; Han, Tengwei; Gu, Chaomei; Sun, Yehuan

    2011-11-01

    To Eexplore the application of negative binomial regression and modified Poisson regression analysis in analyzing the influential factors for injury frequency and the risk factors leading to the increase of injury frequency. 2917 primary and secondary school students were selected from Hefei by cluster random sampling method and surveyed by questionnaire. The data on the count event-based injuries used to fitted modified Poisson regression and negative binomial regression model. The risk factors incurring the increase of unintentional injury frequency for juvenile students was explored, so as to probe the efficiency of these two models in studying the influential factors for injury frequency. The Poisson model existed over-dispersion (P Poisson regression and negative binomial regression model, was fitted better. respectively. Both showed that male gender, younger age, father working outside of the hometown, the level of the guardian being above junior high school and smoking might be the results of higher injury frequencies. On a tendency of clustered frequency data on injury event, both the modified Poisson regression analysis and negative binomial regression analysis can be used. However, based on our data, the modified Poisson regression fitted better and this model could give a more accurate interpretation of relevant factors affecting the frequency of injury.

  15. An examination of the environmental, driver and vehicle factors associated with the serious and fatal crashes of older rural drivers.

    Science.gov (United States)

    Thompson, J P; Baldock, M R J; Mathias, J L; Wundersitz, L N

    2013-01-01

    Motor vehicle crashes involving rural drivers aged 75 years and over are more than twice as likely to result in a serious or fatal injury as those involving their urban counterparts. The current study examined some of the reasons for this using a database of police-reported crashes (2004-2008) to identify the environmental (lighting, road and weather conditions, road layout, road surface, speed limit), driver (driver error, crash type), and vehicle (vehicle age) factors that are associated with the crashes of older rural drivers. It also determined whether these same factors are associated with an increased likelihood of serious or fatal injury in younger drivers for whom frailty does not contribute to the resulting injury severity. A number of environmental (i.e., undivided, unsealed, curved and inclined roads, and areas with a speed limit of 100km/h or greater) and driver (i.e., collision with a fixed object and rolling over) factors were more frequent in the crashes of older rural drivers and additionally associated with increased injury severity in younger drivers. Moreover, when these environmental factors were entered into a logistic regression model to predict whether older drivers who were involved in crashes did or did not sustain a serious or fatal injury, it was found that each factor independently increased the likelihood of a serious or fatal injury. Changes, such as the provision of divided and sealed roads, greater protection from fixed roadside objects, and reduced speed limits, appear to be indicated in order to improve the safety of the rural driving environment for drivers of all ages. Additionally, older rural drivers should be encouraged to reduce their exposure to these risky circumstances. Copyright © 2012 Elsevier Ltd. All rights reserved.

  16. Logistic regression for dichotomized counts.

    Science.gov (United States)

    Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W

    2016-12-01

    Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.

  17. Parents' Reports of Children's Internalizing Symptoms: Associations with Parents' Mental Health Symptoms and Substance Use Disorder.

    Science.gov (United States)

    Kelley, Michelle L; Bravo, Adrian J; Hamrick, Hannah C; Braitman, Abby L; White, Tyler D; Jenkins, Jennika

    2017-06-01

    This brief report examined the unique associations between parents' ratings of child internalizing symptoms and their own depression and anxiety in families with parental substance use disorder (SUD). Further, we examined whether parental SUD (father only, mother only, both parents) was related to discrepancy in mothers' and fathers' reports of children's internalizing symptoms. Participants were 97 triads (fathers, mothers) in which one or both parents met criteria for SUD. Polynomial regression analyses were conducted to examine whether father-mother reports of child internalizing symptoms had unique associations with parents' own symptoms of depression and anxiety while controlling for child gender, child age, and SUD diagnoses. Controlling for fathers' symptoms and other covariates, mothers experiencing more depression and anxiety symptoms reported more symptoms of child internalizing symptoms than did fathers. Mothers' and fathers' SUD was associated with higher anxiety symptoms among mothers after controlling for other variables. A second set of polynomial regressions examined whether father-mother reports of child internalizing symptoms had unique associations with parents' SUD diagnoses while controlling for child gender and child age. After controlling for mothers' symptoms and other covariates, parents' reports of children's internalizing symptoms were not significantly associated with either parent's SUD or parental SUD interactions (i.e., both parents have SUD diagnoses). Taken together, mothers' ratings of children's internalizing symptoms may be accounted for, in part, by her reports of depression and anxiety symptoms.

  18. Associations between formative practice quizzes and summative examination outcomes in a medical anatomy course.

    Science.gov (United States)

    McNulty, John A; Espiritu, Baltazar R; Hoyt, Amy E; Ensminger, David C; Chandrasekhar, Arcot J

    2015-01-01

    Formative practice quizzes have become common resources for self-evaluation and focused reviews of course content in the medical curriculum. We conducted two separate studies to (1) compare the effects of a single or multiple voluntary practice quizzes on subsequent summative examinations and (2) examine when students are most likely to use practice quizzes relative to the summative examinations. In the first study, providing a single on-line practice quiz followed by instructor feedback had no effect on examination average grades compared to the previous year or student performances on similar questions. However, there were significant correlations between student performance on each practice quiz and each summative examination (r = 0.42 and r = 0.24). When students were provided multiple practice quizzes with feedback (second study), there were weak correlations between the frequency of use and performance on each summative examination (r = 0.17 and r = 0.07). The frequency with which students accessed the practice quizzes was greatest the day before each examination. In both studies, there was a decline in the level of student utilization of practice quizzes over time. We conclude that practice quizzes provide some predictive value for performances on summative examinations. Second, making practice quizzes available for longer periods prior to summative examinations does not promote the use of the quizzes as a study strategy because students appear to use them mostly to assess knowledge one to two days prior to examinations. © 2014 American Association of Anatomists.

  19. Bayesian ARTMAP for regression.

    Science.gov (United States)

    Sasu, L M; Andonie, R

    2013-10-01

    Bayesian ARTMAP (BA) is a recently introduced neural architecture which uses a combination of Fuzzy ARTMAP competitive learning and Bayesian learning. Training is generally performed online, in a single-epoch. During training, BA creates input data clusters as Gaussian categories, and also infers the conditional probabilities between input patterns and categories, and between categories and classes. During prediction, BA uses Bayesian posterior probability estimation. So far, BA was used only for classification. The goal of this paper is to analyze the efficiency of BA for regression problems. Our contributions are: (i) we generalize the BA algorithm using the clustering functionality of both ART modules, and name it BA for Regression (BAR); (ii) we prove that BAR is a universal approximator with the best approximation property. In other words, BAR approximates arbitrarily well any continuous function (universal approximation) and, for every given continuous function, there is one in the set of BAR approximators situated at minimum distance (best approximation); (iii) we experimentally compare the online trained BAR with several neural models, on the following standard regression benchmarks: CPU Computer Hardware, Boston Housing, Wisconsin Breast Cancer, and Communities and Crime. Our results show that BAR is an appropriate tool for regression tasks, both for theoretical and practical reasons. Copyright © 2013 Elsevier Ltd. All rights reserved.

  20. Mechanisms of neuroblastoma regression

    Science.gov (United States)

    Brodeur, Garrett M.; Bagatell, Rochelle

    2014-01-01

    Recent genomic and biological studies of neuroblastoma have shed light on the dramatic heterogeneity in the clinical behaviour of this disease, which spans from spontaneous regression or differentiation in some patients, to relentless disease progression in others, despite intensive multimodality therapy. This evidence also suggests several possible mechanisms to explain the phenomena of spontaneous regression in neuroblastomas, including neurotrophin deprivation, humoral or cellular immunity, loss of telomerase activity and alterations in epigenetic regulation. A better understanding of the mechanisms of spontaneous regression might help to identify optimal therapeutic approaches for patients with these tumours. Currently, the most druggable mechanism is the delayed activation of developmentally programmed cell death regulated by the tropomyosin receptor kinase A pathway. Indeed, targeted therapy aimed at inhibiting neurotrophin receptors might be used in lieu of conventional chemotherapy or radiation in infants with biologically favourable tumours that require treatment. Alternative approaches consist of breaking immune tolerance to tumour antigens or activating neurotrophin receptor pathways to induce neuronal differentiation. These approaches are likely to be most effective against biologically favourable tumours, but they might also provide insights into treatment of biologically unfavourable tumours. We describe the different mechanisms of spontaneous neuroblastoma regression and the consequent therapeutic approaches. PMID:25331179

  1. Non-trauma-associated additional findings in whole-body CT examinations in patients with multiple trauma

    International Nuclear Information System (INIS)

    Hoffstetter, P.; Herold, T.; Daneschnejad, M.; Zorger, N.; Jung, E.M.; Feuerbach, S.; Schreyer, A.G.

    2008-01-01

    Purpose: whole-body CT scans for patients with multiple trauma represent an increasingly accepted first diagnostic tool. The multidetector approach in particular provides appropriate diagnostic algorithms for detecting nearly all relevant traumatic findings in a short time with a high grade of sensitivity and specificity. Non-trauma-associated additional findings are commonly depicted based on these CT examinations. The aim of this study is to evaluate the number and quality of these additional findings in consecutive patients with multiple trauma. Materials and methods: between 3/04 and 8/06 we scanned 304 patients according to our dedicated multiple trauma protocol. The examination protocol includes a head scan without intravenous contrast followed by a whole-body scan including the neck, thorax and abdomen acquired by a 16-row CT Scanner (Siemens, Sensation 16). The CT scans were retrospectively analyzed by two radiologists with respect to non-trauma-associated findings. Lesions were assessed according to their clinical relevance (highly relevant, moderately relevant, not relevant). For patients with highly relevant findings, additional follow-up research was performed. Results: The average age was 43 years (range 3 - 92). 236 of the patients were male (77.6%), 68 female (22.4%). 153 patients (50.3%) had additional non-trauma-associated findings. In 20 cases (6.6%) lesions with high clinical relevance were detected (e.g. carcinoma of the kidney or the ovary). In 71 patients (23.4%) findings with moderate relevance were described. In 63 patients (20.7%) additional findings without major relevance were diagnosed. Conclusion: Whole-body CT scans of patients randomized by a trauma show a considerable number of non-trauma-associated additional findings. In about 30% of cases, these findings are clinically relevant because further diagnostic workup or treatment in the short or medium-term is needed. The results of these analyses emphasize the diagnostic value of CT

  2. Using the Ridge Regression Procedures to Estimate the Multiple Linear Regression Coefficients

    Science.gov (United States)

    Gorgees, HazimMansoor; Mahdi, FatimahAssim

    2018-05-01

    This article concerns with comparing the performance of different types of ordinary ridge regression estimators that have been already proposed to estimate the regression parameters when the near exact linear relationships among the explanatory variables is presented. For this situations we employ the data obtained from tagi gas filling company during the period (2008-2010). The main result we reached is that the method based on the condition number performs better than other methods since it has smaller mean square error (MSE) than the other stated methods.

  3. Resource Loss and Depressive Symptoms Following Hurricane Katrina: A Principal Component Regression Study

    OpenAIRE

    Liang L; Hayashi K; Bennett P; Johnson T. J; Aten J. D

    2015-01-01

    To understand the relationship between the structure of resource loss and depression after disaster exposure, the components of resource loss and the impact of these resource loss components on depression was examined among college students (N=654) at two universities who were affected by Hurricane Katrina. The component of resource loss was analyzed by principal component analysis first. Gender, social relationship loss, and financial loss were then examined with the regression model on depr...

  4. Multicollinearity and Regression Analysis

    Science.gov (United States)

    Daoud, Jamal I.

    2017-12-01

    In regression analysis it is obvious to have a correlation between the response and predictor(s), but having correlation among predictors is something undesired. The number of predictors included in the regression model depends on many factors among which, historical data, experience, etc. At the end selection of most important predictors is something objective due to the researcher. Multicollinearity is a phenomena when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase [8]. Increased standard errors means that the coefficients for some or all independent variables may be found to be significantly different from In other words, by overinflating the standard errors, multicollinearity makes some variables statistically insignificant when they should be significant. In this paper we focus on the multicollinearity, reasons and consequences on the reliability of the regression model.

  5. Panel Smooth Transition Regression Models

    DEFF Research Database (Denmark)

    González, Andrés; Terasvirta, Timo; Dijk, Dick van

    We introduce the panel smooth transition regression model. This new model is intended for characterizing heterogeneous panels, allowing the regression coefficients to vary both across individuals and over time. Specifically, heterogeneity is allowed for by assuming that these coefficients are bou...

  6. Iron deficiency is associated with increased levels of blood cadmium in the Korean general population: Analysis of 2008–2009 Korean National Health and Nutrition Examination Survey data

    International Nuclear Information System (INIS)

    Lee, Byung-Kook; Kim, Yangho

    2012-01-01

    Introduction: We present data from the Korean National Health and Nutrition Examination Survey 2008–2009 on the distribution of blood cadmium levels and their association with iron deficiency in a representative sample of the adult Korean population. Methods: Serum ferritin was categorized into three levels: low (serum ferritin <15.0 μg/L), low normal (15.0–30.0 μg/L for women and 15.0–50.0 for men), and normal (≥30.0 μg/L for women and ≥50.0 for men), and its association with blood cadmium level was assessed after adjustment for various demographic and lifestyle factors. Results: Geometric means of blood cadmium in the low serum ferritin group in women, men, and all participants were significantly higher than in the normal group. Additionally, multiple regression analysis after adjusting for various covariates showed that blood cadmium was significantly higher in the low-ferritin group in women, men, and all participants compared with the normal group. We also found an association between serum ferritin and blood cadmium among never-smoking participants. Discussion: We found, similar to other recent population-based studies, an association between iron deficiency and increased blood cadmium in men and women, independent of smoking status. The results of the present study show that iron deficiency is associated with increased levels of blood cadmium in the general population.

  7. Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions.

    Science.gov (United States)

    Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

    2012-05-01

    Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

  8. Using quantile regression to examine the effects of inequality across the mortality distribution in the U.S. counties

    Science.gov (United States)

    Yang, Tse-Chuan; Chen, Vivian Yi-Ju; Shoff, Carla; Matthews, Stephen A.

    2012-01-01

    The U.S. has experienced a resurgence of income inequality in the past decades. The evidence regarding the mortality implications of this phenomenon has been mixed. This study employs a rarely used method in mortality research, quantile regression (QR), to provide insight into the ongoing debate of whether income inequality is a determinant of mortality and to investigate the varying relationship between inequality and mortality throughout the mortality distribution. Analyzing a U.S. dataset where the five-year (1998–2002) average mortality rates were combined with other county-level covariates, we found that the association between inequality and mortality was not constant throughout the mortality distribution and the impact of inequality on mortality steadily increased until the 80th percentile. When accounting for all potential confounders, inequality was significantly and positively related to mortality; however, this inequality–mortality relationship did not hold across the mortality distribution. A series of Wald tests confirmed this varying inequality–mortality relationship, especially between the lower and upper tails. The large variation in the estimated coefficients of the Gini index suggested that inequality had the greatest influence on those counties with a mortality rate of roughly 9.95 deaths per 1000 population (80th percentile) compared to any other counties. Furthermore, our results suggest that the traditional analytic methods that focus on mean or median value of the dependent variable can be, at most, applied to a narrow 20 percent of observations. This study demonstrates the value of QR. Our findings provide some insight as to why the existing evidence for the inequality–mortality relationship is mixed and suggest that analytical issues may play a role in clarifying whether inequality is a robust determinant of population health. PMID:22497847

  9. Variable Selection for Regression Models of Percentile Flows

    Science.gov (United States)

    Fouad, G.

    2017-12-01

    Percentile flows describe the flow magnitude equaled or exceeded for a given percent of time, and are widely used in water resource management. However, these statistics are normally unavailable since most basins are ungauged. Percentile flows of ungauged basins are often predicted using regression models based on readily observable basin characteristics, such as mean elevation. The number of these independent variables is too large to evaluate all possible models. A subset of models is typically evaluated using automatic procedures, like stepwise regression. This ignores a large variety of methods from the field of feature (variable) selection and physical understanding of percentile flows. A study of 918 basins in the United States was conducted to compare an automatic regression procedure to the following variable selection methods: (1) principal component analysis, (2) correlation analysis, (3) random forests, (4) genetic programming, (5) Bayesian networks, and (6) physical understanding. The automatic regression procedure only performed better than principal component analysis. Poor performance of the regression procedure was due to a commonly used filter for multicollinearity, which rejected the strongest models because they had cross-correlated independent variables. Multicollinearity did not decrease model performance in validation because of a representative set of calibration basins. Variable selection methods based strictly on predictive power (numbers 2-5 from above) performed similarly, likely indicating a limit to the predictive power of the variables. Similar performance was also reached using variables selected based on physical understanding, a finding that substantiates recent calls to emphasize physical understanding in modeling for predictions in ungauged basins. The strongest variables highlighted the importance of geology and land cover, whereas widely used topographic variables were the weakest predictors. Variables suffered from a high

  10. Associations of Proatrial Natriuretic Peptide with Components of the Metabolic Syndrome in Adolescents and Young Adults from the General Population

    DEFF Research Database (Denmark)

    Goharian, Tina S; Gøtze, Jens P; Faber, Jens

    2017-01-01

    of cardiovascular disease risk factors in children, adolescents and young adults. We used linear regression analysis to examine the associations, expressed as standardized regression coefficients, of various variables of interest with MR-proANP stratified according to age group, adjusting for age and gender...... (β = -0.14, P different pattern was observed since MR-proANP was not significantly associated with BMI (β = -0.00, P = 0.98), WC (β = -0.01, P = 0.90) and insulin (β = -0.02, P = 0.69). Nevertheless, among the adolescents, MR-proANP was negatively associated...

  11. Associated factors for falls among the community-dwelling older people assessed by annual geriatric health examinations.

    Directory of Open Access Journals (Sweden)

    Chung-Hao Lin

    Full Text Available BACKGROUND: Falls are very common among the older people. Nearly one-third older people living in a community fall each year. However, few studies have examined factors associated with falls in a community-dwelling population of older Taiwanese adults. OBJECTIVES: To identify the associated factors for falls during the previous 12 months among the community-dwelling Taiwanese older people receiving annual geriatric health examinations. PARTICIPANTS: People aged sixty-five years or older, living in the community, assessed by annual geriatric health examinations METHODS: 1377 community-dwellers aged ≥65 years who received annual geriatric health examinations at one hospital in northern Taiwan between March and November of 2008. They were asked about their history of falls during the year prior to their most recent health examination. RESULTS: The average age of the 1377 participants was 74.9±6.8 years, 48.9% of which were women. Three-hundred and thirteen of the participants (22.7% had at least one fall during the previous year. Multivariate analysis showed that odds ratio for the risk of falling was 1.94 (95% CI 1.36-2.76 when the female gender group is compared with the male gender group. The adjusted odds ratios of age and waist circumference were 1.03 (95% CI 1.00-1.06 and 1.03 (95% CI 1.01-1.05 respectively. The adjusted odds ratios of visual acuity, Karnofsky scale, and serum albumin level were 0.34 (95% CI 0.15-0.76, 0.94 (95% CI 0.89-0.98, and 0.37 (95% CI 0.18-0.76 respectively. Larger waist circumference, older age, female gender, poorer visual acuity, lower score on the Karnofsky Performance Scale, and lower serum albumin level were the independent associated factors for falls. CONCLUSION: In addition to other associated factors, waist circumference should be included as a novel risk factor for falls.

  12. Credit Scoring Problem Based on Regression Analysis

    OpenAIRE

    Khassawneh, Bashar Suhil Jad Allah

    2014-01-01

    ABSTRACT: This thesis provides an explanatory introduction to the regression models of data mining and contains basic definitions of key terms in the linear, multiple and logistic regression models. Meanwhile, the aim of this study is to illustrate fitting models for the credit scoring problem using simple linear, multiple linear and logistic regression models and also to analyze the found model functions by statistical tools. Keywords: Data mining, linear regression, logistic regression....

  13. Marginal regression analysis of recurrent events with coarsened censoring times.

    Science.gov (United States)

    Hu, X Joan; Rosychuk, Rhonda J

    2016-12-01

    Motivated by an ongoing pediatric mental health care (PMHC) study, this article presents weakly structured methods for analyzing doubly censored recurrent event data where only coarsened information on censoring is available. The study extracted administrative records of emergency department visits from provincial health administrative databases. The available information of each individual subject is limited to a subject-specific time window determined up to concealed data. To evaluate time-dependent effect of exposures, we adapt the local linear estimation with right censored survival times under the Cox regression model with time-varying coefficients (cf. Cai and Sun, Scandinavian Journal of Statistics 2003, 30, 93-111). We establish the pointwise consistency and asymptotic normality of the regression parameter estimator, and examine its performance by simulation. The PMHC study illustrates the proposed approach throughout the article. © 2016, The International Biometric Society.

  14. Associations between Food Security Status and Dietary Inflammatory Potential within Lower-Income Adults from the United States National Health and Nutrition Examination Survey, Cycles 2007 to 2014.

    Science.gov (United States)

    Bergmans, Rachel S; Palta, Mari; Robert, Stephanie A; Berger, Lawrence M; Ehrenthal, Deborah B; Malecki, Kristen M

    2018-06-01

    Evidence suggests both that chronic inflammation mediates the association of food insecurity with adverse health outcomes and that diet may be a significant source of inflammation among food insecure individuals. To examine whether food security status is associated with dietary inflammatory potential. Cross-sectional data came from the National Health and Nutrition Examination Survey (NHANES), cycles 2007 to 2014 (n=10,630). The analysis sample is representative of noninstitutionalized US adults with an income-to-poverty ratio ≤3.00. Dietary Inflammatory Index (DII) score, calculated using the average of two 24-hour dietary recalls, was the main outcome measure. Type III F tests or χ 2 tests compared population characteristics by food security status, defined using the US Food Security Survey Module. Multivariable linear regression was used to estimate the association between food security status and the DII score and moderation by demographic factors. Survey weighting procedures accounted for the effects of stratification and clustering used in the NHANES study design. When accounting for socioeconomic status, demographic factors, and health status, DII score was higher at greater levels of food insecurity (P=0.0033). Those with very low food security had a 0.31 (95% CI=0.12 to 0.49) higher DII score than those with high food security. Age moderated the association between food security status and DII score (interaction P=0.0103), where the magnitude of the association between DII score and severity of food insecurity was higher for those >65 years than for younger age groups. Food security status may be associated with dietary inflammatory potential, which is hypothesized to play a role in multiple chronic health conditions. Further research is needed to determine the causal nature of this relationship and evaluate how best to implement programs designed to address health disparities within food insecure populations. Copyright © 2018 Academy of Nutrition and

  15. Detection of Cutting Tool Wear using Statistical Analysis and Regression Model

    Science.gov (United States)

    Ghani, Jaharah A.; Rizal, Muhammad; Nuawi, Mohd Zaki; Haron, Che Hassan Che; Ramli, Rizauddin

    2010-10-01

    This study presents a new method for detecting the cutting tool wear based on the measured cutting force signals. A statistical-based method called Integrated Kurtosis-based Algorithm for Z-Filter technique, called I-kaz was used for developing a regression model and 3D graphic presentation of I-kaz 3D coefficient during machining process. The machining tests were carried out using a CNC turning machine Colchester Master Tornado T4 in dry cutting condition. A Kistler 9255B dynamometer was used to measure the cutting force signals, which were transmitted, analyzed, and displayed in the DasyLab software. Various force signals from machining operation were analyzed, and each has its own I-kaz 3D coefficient. This coefficient was examined and its relationship with flank wear lands (VB) was determined. A regression model was developed due to this relationship, and results of the regression model shows that the I-kaz 3D coefficient value decreases as tool wear increases. The result then is used for real time tool wear monitoring.

  16. WASP (Write a Scientific Paper) using Excel - 13: Correlation and Regression.

    Science.gov (United States)

    Grech, Victor

    2018-07-01

    Correlation and regression measure the closeness of association between two continuous variables. This paper explains how to perform these tests in Microsoft Excel and their interpretation, as well as how to apply these tests dynamically using Excel's functions. Copyright © 2018 Elsevier B.V. All rights reserved.

  17. The associations between religion, bereavement and depression among Hong Kong nurses.

    Science.gov (United States)

    Cheung, Teris; Lee, Paul H; Yip, Paul S F

    2017-07-04

    This paper is to examine the associations between religion, bereavement and depression among nursing professionals using a cross-sectional survey design. There is little empirical evidence in Asia suggesting that religion may either increase or lower the likelihood of nursing professionals being depressed. We analyzed the results of a Mental Health Survey soliciting data from 850 Hong Kong nurses (aged 21-59, 178 males) regarding their mental well-being and associated factors, including participants' socio-economic profile and recent life-events. Multiple linear regression analyses examined associations between religion, bereavement and depression. Religious faith is weakly associated with lower self-reported depression in bereavement. Our findings confirm those studies suggesting that religion positively affects mental health and yet healthcare providers have yet to assimilate this insight.

  18. 100% orange juice consumption is associated with better diet quality, improved nutrient adequacy, decreased risk for obesity, and improved biomarkers of health in adults: National Health and Nutrition Examination Survey, 2003-2006.

    Science.gov (United States)

    O'Neil, Carol E; Nicklas, Theresa A; Rampersaud, Gail C; Fulgoni, Victor L

    2012-12-12

    Consumption of 100% orange juice (OJ) has been positively associated with nutrient adequacy and diet quality, with no increased risk of overweight/obesity in children; however, no one has examined these factors in adults. The purpose of this study was to examine the association of 100% OJ consumption with nutrient adequacy, diet quality, and risk factors for metabolic syndrome (MetS) in a nationally representative sample of adults. Data from adults 19+ years of age (n = 8,861) participating in the National Health and Nutrition Examination Survey 2003-2006 were used. The National Cancer Institute method was used to estimate the usual intake (UI) of 100% OJ consumption, selected nutrients, and food groups. Percentages of the population below the Estimated Average Requirement (EAR) or above the Adequate Intake (AI) were determined. Diet quality was measured by the Healthy Eating Index-2005 (HEI-2005). Covariate adjusted logistic regression was used to determine if consumers had a lower odds ratio of being overweight or obese or having risk factors of MetS or MetS. Usual per capita intake of 100% OJ was 50.3 ml/d. Among consumers (n = 2,310; 23.8%), UI was 210.0 ml/d. Compared to non-consumers, consumers had a higher (p juice, whole fruit, and whole grain. Consumers had a lower (p diet.

  19. Unbalanced Regressions and the Predictive Equation

    DEFF Research Database (Denmark)

    Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo

    Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness in the theoreti......Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness...... in the theoretical predictive equation by suggesting a data generating process, where returns are generated as linear functions of a lagged latent I(0) risk process. The observed predictor is a function of this latent I(0) process, but it is corrupted by a fractionally integrated noise. Such a process may arise due...... to aggregation or unexpected level shifts. In this setup, the practitioner estimates a misspecified, unbalanced, and endogenous predictive regression. We show that the OLS estimate of this regression is inconsistent, but standard inference is possible. To obtain a consistent slope estimate, we then suggest...

  20. [From clinical judgment to linear regression model.

    Science.gov (United States)

    Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O

    2013-01-01

    When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R 2 ) indicates the importance of independent variables in the outcome.

  1. Autistic Regression

    Science.gov (United States)

    Matson, Johnny L.; Kozlowski, Alison M.

    2010-01-01

    Autistic regression is one of the many mysteries in the developmental course of autism and pervasive developmental disorders not otherwise specified (PDD-NOS). Various definitions of this phenomenon have been used, further clouding the study of the topic. Despite this problem, some efforts at establishing prevalence have been made. The purpose of…

  2. Ridge regression estimator: combining unbiased and ordinary ridge regression methods of estimation

    Directory of Open Access Journals (Sweden)

    Sharad Damodar Gore

    2009-10-01

    Full Text Available Statistical literature has several methods for coping with multicollinearity. This paper introduces a new shrinkage estimator, called modified unbiased ridge (MUR. This estimator is obtained from unbiased ridge regression (URR in the same way that ordinary ridge regression (ORR is obtained from ordinary least squares (OLS. Properties of MUR are derived. Results on its matrix mean squared error (MMSE are obtained. MUR is compared with ORR and URR in terms of MMSE. These results are illustrated with an example based on data generated by Hoerl and Kennard (1975.

  3. Regression analysis for bivariate gap time with missing first gap time data.

    Science.gov (United States)

    Huang, Chia-Hui; Chen, Yi-Hau

    2017-01-01

    We consider ordered bivariate gap time while data on the first gap time are unobservable. This study is motivated by the HIV infection and AIDS study, where the initial HIV contracting time is unavailable, but the diagnosis times for HIV and AIDS are available. We are interested in studying the risk factors for the gap time between initial HIV contraction and HIV diagnosis, and gap time between HIV and AIDS diagnoses. Besides, the association between the two gap times is also of interest. Accordingly, in the data analysis we are faced with two-fold complexity, namely data on the first gap time is completely missing, and the second gap time is subject to induced informative censoring due to dependence between the two gap times. We propose a modeling framework for regression analysis of bivariate gap time under the complexity of the data. The estimating equations for the covariate effects on, as well as the association between, the two gap times are derived through maximum likelihood and suitable counting processes. Large sample properties of the resulting estimators are developed by martingale theory. Simulations are performed to examine the performance of the proposed analysis procedure. An application of data from the HIV and AIDS study mentioned above is reported for illustration.

  4. Determination of gaussian peaks in gamma spectra by iterative regression

    International Nuclear Information System (INIS)

    Nordemann, D.J.R.

    1987-05-01

    The parameters of the peaks in gamma-ray spectra are determined by a simple iterative regression method. For each peak, the parameters are associated with a gaussian curve (3 parameters) located above a linear continuum (2 parameters). This method may produces the complete result of the calculation of statistical uncertainties and an accuracy higher than others methods. (author) [pt

  5. Demographic and socioeconomic disparity in nutrition: application of a novel Correlated Component Regression approach

    Science.gov (United States)

    Alkerwi, Ala'a; Vernier, Céderic; Sauvageot, Nicolas; Crichton, Georgina E; Elias, Merrill F

    2015-01-01

    Objectives This study aimed to examine the most important demographic and socioeconomic factors associated with diet quality, evaluated in terms of compliance with national dietary recommendations, selection of healthy and unhealthy food choices, energy density and food variety. We hypothesised that different demographic and socioeconomic factors may show disparate associations with diet quality. Study design A nationwide, cross-sectional, population-based study. Participants A total of 1352 apparently healthy and non-institutionalised subjects, aged 18–69 years, participated in the Observation of Cardiovascular Risk Factors in Luxembourg (ORISCAV-LUX) study in 2007–2008. The participants attended the nearest study centre after a telephone appointment, and were interviewed by trained research staff. Outcome measures Diet quality as measured by 5 dietary indicators, namely, recommendation compliance index (RCI), recommended foods score (RFS), non-recommended foods score (non-RFS), energy density score (EDS), and dietary diversity score (DDS). The novel Correlated Component Regression (CCR) technique was used to determine the importance and magnitude of the association of each socioeconomic factor with diet quality, in a global analytic approach. Results Increasing age, being male and living below the poverty threshold were predominant factors associated with eating a high energy density diet. Education level was an important factor associated with healthy and adequate food choices, whereas economic resources were predominant factors associated with food diversity and energy density. Conclusions Multiple demographic and socioeconomic circumstances were associated with different diet quality indicators. Efforts to improve diet quality for high-risk groups need an important public health focus. PMID:25967988

  6. Discriminative Elastic-Net Regularized Linear Regression.

    Science.gov (United States)

    Zhang, Zheng; Lai, Zhihui; Xu, Yong; Shao, Ling; Wu, Jian; Xie, Guo-Sen

    2017-03-01

    In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However, most of the existing linear regression methods exploit the conventional zero-one matrix as the regression targets, which greatly narrows the flexibility of the regression model. Another major limitation of these methods is that the learned projection matrix fails to precisely project the image features to the target space due to their weak discriminative capability. To this end, we present an elastic-net regularized linear regression (ENLR) framework, and develop two robust linear regression models which possess the following special characteristics. First, our methods exploit two particular strategies to enlarge the margins of different classes by relaxing the strict binary targets into a more feasible variable matrix. Second, a robust elastic-net regularization of singular values is introduced to enhance the compactness and effectiveness of the learned projection matrix. Third, the resulting optimization problem of ENLR has a closed-form solution in each iteration, which can be solved efficiently. Finally, rather than directly exploiting the projection matrix for recognition, our methods employ the transformed features as the new discriminate representations to make final image classification. Compared with the traditional linear regression model and some of its variants, our method is much more accurate in image classification. Extensive experiments conducted on publicly available data sets well demonstrate that the proposed framework can outperform the state-of-the-art methods. The MATLAB codes of our methods can be available at http://www.yongxu.org/lunwen.html.

  7. The associations between organizational social capital, perceived health, and employeese performance in two dutch companies

    NARCIS (Netherlands)

    Scheppingen, A.R. van; Vroome, E.M.M. de; Have, K.C.J.M. ten; Bos, E.H.; Zwetsloot, G.I.J.M.; Mechelen, W. van

    2013-01-01

    OBJECTIVE: To examine the associations between organizational (bonding, bridging, and linking) social capital, employees' health, and employees' performance. METHODS: Linear regression on cross-sectional data among 718 employees in two Dutch companies. RESULTS: Organizational social capital was

  8. Neck-focused panic attacks among Cambodian refugees; a logistic and linear regression analysis.

    Science.gov (United States)

    Hinton, Devon E; Chhean, Dara; Pich, Vuth; Um, Khin; Fama, Jeanne M; Pollack, Mark H

    2006-01-01

    Consecutive Cambodian refugees attending a psychiatric clinic were assessed for the presence and severity of current--i.e., at least one episode in the last month--neck-focused panic. Among the whole sample (N=130), in a logistic regression analysis, the Anxiety Sensitivity Index (ASI; odds ratio=3.70) and the Clinician-Administered PTSD Scale (CAPS; odds ratio=2.61) significantly predicted the presence of current neck panic (NP). Among the neck panic patients (N=60), in the linear regression analysis, NP severity was significantly predicted by NP-associated flashbacks (beta=.42), NP-associated catastrophic cognitions (beta=.22), and CAPS score (beta=.28). Further analysis revealed the effect of the CAPS score to be significantly mediated (Sobel test [Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182]) by both NP-associated flashbacks and catastrophic cognitions. In the care of traumatized Cambodian refugees, NP severity, as well as NP-associated flashbacks and catastrophic cognitions, should be specifically assessed and treated.

  9. Concurrent and longitudinal associations between diurnal cortisol and body mass index across adolescence.

    Science.gov (United States)

    Ruttle, Paula L; Javaras, Kristin N; Klein, Marjorie H; Armstrong, Jeffrey M; Burk, Linnea R; Essex, Marilyn J

    2013-06-01

    Childhood and adolescent obesity have reached epidemic levels; however, little is known about the psychobiological underpinnings of obesity in youth and whether these differ from the mechanisms identified in adults. The current study examines concurrent (i.e., measured at the same point in time) and longitudinal (i.e., using earlier cortisol measures to predict later body mass index [BMI]) associations between diurnal cortisol and BMI across adolescence. Adolescent diurnal cortisol was measured over 3 days at each 11, 13, and 15 years. Hierarchical linear modeling was used to extract average measures of predicted morning, afternoon, evening levels of cortisol and the diurnal slope at each assessment. Adolescent BMI (kg/m(2)) was measured at 11, 13, 15, and 18 years. Sex, family socioeconomic status, mother's BMI, pubertal status, and adolescent mental health were examined as possible confounding variables. Linear regressions revealed that blunted patterns of adolescent cortisol were associated with increased measures of BMI across adolescence both concurrently and longitudinally, particularly when examining measures of cortisol in early adolescence. Multinomial logistic regressions extended the linear regression findings beyond BMI scores to encompass categories of obesity. The current study builds on previous research documenting diurnal cortisol-obesity findings in adults by demonstrating similar findings exist both concurrently and longitudinally in adolescents. Findings suggest the association between cortisol and BMI is developmentally influenced and that blunted diurnal cortisol patterns can be identified in overweight individuals at a younger age than previously thought. Copyright © 2013 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  10. Rural-urban difference in the use of annual physical examination among seniors in Shandong, China: a cross-sectional study.

    Science.gov (United States)

    Ge, Dandan; Chu, Jie; Zhou, Chengchao; Qian, Yangyang; Zhang, Li; Sun, Long

    2017-05-23

    Regular physical examination contributes to early detection and timely treatment, which is helpful in promoting healthy behaviors and preventing diseases. The objective of this study is to compare the annual physical examination (APE) use between rural and urban elderly in China. A total of 3,922 participants (60+) were randomly selected from three urban districts and three rural counties in Shandong Province, China, and were interviewed using a standardized questionnaire. We performed unadjusted and adjusted logistic regression models to examine the difference in the utilization of APE between rural and urban elderly. Two adjusted logistic regression models were employed to identify the factors associated with APE use in rural and urban seniors respectively. The utilization rates of APE in rural and urban elderly are 37.4% and 76.2% respectively. Factors including education level, exercise, watching TV, and number of non-communicable chronic conditions, are associated with APE use both in rural and urban elderly. Hospitalization, self-reported economic status, and health insurance are found to be significant (p Urban Resident Basic Medical Insurance (URBMI) (p urban areas. There is a big difference in APE utilization between rural and urban elderly. Interventions targeting identified at-risk subgroups, especially for those rural elderly, are essential to reduce such a gap. To improve health literacy might be helpful to increase the utilization rate of APE among the elderly.

  11. The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics

    Directory of Open Access Journals (Sweden)

    Ronald de Vlaming

    2015-01-01

    Full Text Available In recent years, there has been a considerable amount of research on the use of regularization methods for inference and prediction in quantitative genetics. Such research mostly focuses on selection of markers and shrinkage of their effects. In this review paper, the use of ridge regression for prediction in quantitative genetics using single-nucleotide polymorphism data is discussed. In particular, we consider (i the theoretical foundations of ridge regression, (ii its link to commonly used methods in animal breeding, (iii the computational feasibility, and (iv the scope for constructing prediction models with nonlinear effects (e.g., dominance and epistasis. Based on a simulation study we gauge the current and future potential of ridge regression for prediction of human traits using genome-wide SNP data. We conclude that, for outcomes with a relatively simple genetic architecture, given current sample sizes in most cohorts (i.e., N<10,000 the predictive accuracy of ridge regression is slightly higher than the classical genome-wide association study approach of repeated simple regression (i.e., one regression per SNP. However, both capture only a small proportion of the heritability. Nevertheless, we find evidence that for large-scale initiatives, such as biobanks, sample sizes can be achieved where ridge regression compared to the classical approach improves predictive accuracy substantially.

  12. Categorical regression dose-response modeling

    Science.gov (United States)

    The goal of this training is to provide participants with training on the use of the U.S. EPA’s Categorical Regression soft¬ware (CatReg) and its application to risk assessment. Categorical regression fits mathematical models to toxicity data that have been assigned ord...

  13. School Term vs. School Holiday: Associations with Children?s Physical Activity, Screen-Time, Diet and Sleep

    OpenAIRE

    Staiano, Amanda E.; Broyles, Stephanie T.; Katzmarzyk, Peter T.

    2015-01-01

    This cross-sectional study examined differences in children’s health behaviors during school term (ST) versus school holiday (SH: June–July) and how associations changed when weather characteristics were considered. Children aged 5–18 years (n = 406) from a subtropical climate reported behaviors over 20 months. Multivariable regression models controlling for age, sex, race and body mass index z-score(BMIz ) were used to examine associations between SH and each behavior. A second model include...

  14. A systematic review and meta-regression analysis of mivacurium for tracheal intubation

    NARCIS (Netherlands)

    Vanlinthout, L.E.H.; Mesfin, S.H.; Hens, N.; Vanacker, B.F.; Robertson, E.N.; Booij, L.H.D.J.

    2014-01-01

    We systematically reviewed factors associated with intubation conditions in randomised controlled trials of mivacurium, using random-effects meta-regression analysis. We included 29 studies of 1050 healthy participants. Four factors explained 72.9% of the variation in the probability of excellent

  15. Leisure Activity Patterns and Their Associations with Overweight: A Prospective Study among Adolescents

    Science.gov (United States)

    Lajunen, Hanna-Reetta; Keski-Rahkonen, Anna; Pulkkinen, Lea; Rose, Richard J.; Rissanen, Aila; Kaprio, Jaakko

    2009-01-01

    We examined longitudinal associations between individual leisure activities (television viewing, video viewing, computer games, listening to music, board games, musical instrument playing, reading, arts, crafts, socializing, clubs or scouts, sports, outdoor activities) and being overweight using logistic regression and latent class analysis in a…

  16. Comparison of Classical Linear Regression and Orthogonal Regression According to the Sum of Squares Perpendicular Distances

    OpenAIRE

    KELEŞ, Taliha; ALTUN, Murat

    2016-01-01

    Regression analysis is a statistical technique for investigating and modeling the relationship between variables. The purpose of this study was the trivial presentation of the equation for orthogonal regression (OR) and the comparison of classical linear regression (CLR) and OR techniques with respect to the sum of squared perpendicular distances. For that purpose, the analyses were shown by an example. It was found that the sum of squared perpendicular distances of OR is smaller. Thus, it wa...

  17. Personality traits associated with intrinsic academic motivation in medical students.

    Science.gov (United States)

    Tanaka, Masaaki; Mizuno, Kei; Fukuda, Sanae; Tajima, Seiki; Watanabe, Yasuyoshi

    2009-04-01

    Motivation is one of the most important psychological concepts in education and is related to academic outcomes in medical students. In this study, the relationships between personality traits and intrinsic academic motivation were examined in medical students. The study group consisted of 119 Year 2 medical students at Osaka City University Graduate School of Medicine. They completed questionnaires dealing with intrinsic academic motivation (the Intrinsic Motivation Scale toward Learning) and personality (the Temperament and Character Inventory [TCI]). On simple regression analyses, the TCI dimensions of persistence, self-directedness, co-operativeness and self-transcendence were positively associated with intrinsic academic motivation. On multiple regression analysis adjusted for age and gender, the TCI dimensions of persistence, self-directedness and self-transcendence were positively associated with intrinsic academic motivation. The temperament dimension of persistence and the character dimensions of self-directedness and self-transcendence are associated with intrinsic academic motivation in medical students.

  18. Scrub typhus islands in the Taiwan area and the association between scrub typhus disease and forest land use and farmer population density: geographically weighted regression

    Science.gov (United States)

    2013-01-01

    Background The Taiwan area comprises the main island of Taiwan and several small islands located off the coast of the Southern China. The eastern two-thirds of Taiwan are characterized by rugged mountains covered with tropical and subtropical vegetation. The western region of Taiwan is characterized by flat or gently rolling plains. Geographically, the Taiwan area is diverse in ecology and environment, although scrub typhus threatens local human populations. In this study, we investigate the effects of seasonal and meteorological factors on the incidence of scrub typhus infection among 10 local climate regions. The correlation between the spatial distribution of scrub typhus and cultivated forests in Taiwan, as well as the relationship between scrub typhus incidence and the population density of farm workers is examined. Methods We applied Pearson’s product moment correlation to calculate the correlation between the incidence of scrub typhus and meteorological factors among 10 local climate regions. We used the geographically weighted regression (GWR) method, a type of spatial regression that generates parameters disaggregated by the spatial units of analysis, to detail and map each regression point for the response variables of the standardized incidence ratio (SIR)-district scrub typhus. We also applied the GWR to examine the explanatory variables of types of forest-land use and farm worker density in Taiwan in 2005. Results In the Taiwan Area, scrub typhus endemic areas are located in the southeastern regions and mountainous townships of Taiwan, as well as the Pescadore, Kinmen, and Matou Islands. Among these islands and low-incidence areas in the central western and southwestern regions of Taiwan, we observed a significant correlation between scrub typhus incidence and surface temperature. No similar significant correlation was found in the endemic areas (e.g., the southeastern region and the mountainous area of Taiwan). Precipitation correlates positively

  19. Pathological assessment of liver fibrosis regression

    Directory of Open Access Journals (Sweden)

    WANG Bingqiong

    2017-03-01

    Full Text Available Hepatic fibrosis is the common pathological outcome of chronic hepatic diseases. An accurate assessment of fibrosis degree provides an important reference for a definite diagnosis of diseases, treatment decision-making, treatment outcome monitoring, and prognostic evaluation. At present, many clinical studies have proven that regression of hepatic fibrosis and early-stage liver cirrhosis can be achieved by effective treatment, and a correct evaluation of fibrosis regression has become a hot topic in clinical research. Liver biopsy has long been regarded as the gold standard for the assessment of hepatic fibrosis, and thus it plays an important role in the evaluation of fibrosis regression. This article reviews the clinical application of current pathological staging systems in the evaluation of fibrosis regression from the perspectives of semi-quantitative scoring system, quantitative approach, and qualitative approach, in order to propose a better pathological evaluation system for the assessment of fibrosis regression.

  20. [Evaluation of estimation of prevalence ratio using bayesian log-binomial regression model].

    Science.gov (United States)

    Gao, W L; Lin, H; Liu, X N; Ren, X W; Li, J S; Shen, X P; Zhu, S L

    2017-03-10

    To evaluate the estimation of prevalence ratio ( PR ) by using bayesian log-binomial regression model and its application, we estimated the PR of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea in their infants by using bayesian log-binomial regression model in Openbugs software. The results showed that caregivers' recognition of infant' s risk signs of diarrhea was associated significantly with a 13% increase of medical care-seeking. Meanwhile, we compared the differences in PR 's point estimation and its interval estimation of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea and convergence of three models (model 1: not adjusting for the covariates; model 2: adjusting for duration of caregivers' education, model 3: adjusting for distance between village and township and child month-age based on model 2) between bayesian log-binomial regression model and conventional log-binomial regression model. The results showed that all three bayesian log-binomial regression models were convergence and the estimated PRs were 1.130(95 %CI : 1.005-1.265), 1.128(95 %CI : 1.001-1.264) and 1.132(95 %CI : 1.004-1.267), respectively. Conventional log-binomial regression model 1 and model 2 were convergence and their PRs were 1.130(95 % CI : 1.055-1.206) and 1.126(95 % CI : 1.051-1.203), respectively, but the model 3 was misconvergence, so COPY method was used to estimate PR , which was 1.125 (95 %CI : 1.051-1.200). In addition, the point estimation and interval estimation of PRs from three bayesian log-binomial regression models differed slightly from those of PRs from conventional log-binomial regression model, but they had a good consistency in estimating PR . Therefore, bayesian log-binomial regression model can effectively estimate PR with less misconvergence and have more advantages in application compared with conventional log-binomial regression model.

  1. Correlation of the National Board of Medical Examiners Emergency Medicine Advanced Clinical Examination given in July to intern American Board of Emergency Medicine in-training examination scores, a predictor of performance?

    Directory of Open Access Journals (Sweden)

    Katherine Hiller

    2015-11-01

    Full Text Available Introduction: There is great variation in the knowledge base of Emergency Medicine (EM interns in July. The first objective knowledge assessment during residency does not occur until eight months later, in February, when the American Board of EM (ABEM administers the in-training examination (ITE. In 2013, the National Board of Medical Examiners (NBME released the EM Advanced Clinical Examination (EM-ACE, an assessment intended for fourth-year medical students. Administration of the EM-ACE to interns at the start of residency may provide an earlier opportunity to assess the new EM residents’ knowledge base. The primary objective of this study was to determine the correlation of the NBME EM-ACE, given early in residency, with the EM ITE. Secondary objectives included determination of the correlation of the United States Medical Licensing Examination (USMLE Step 1 or 2 scores with early intern EM-ACE and ITE scores and the effect, if any, of clinical EM experience on examination correlation. Methods: This was a multi-institutional, observational study. Entering EM interns at six residencies took the EM-ACE in July 2013 and the ABEM ITE in February 2014. We collected scores for the EMACE and ITE, age, gender, weeks of clinical EM experience in residency prior to the ITE, and USMLE Step 1 and 2 scores. Pearson’s correlation and linear regression were performed. Results: Sixty-two interns took the EM-ACE and the ITE. The Pearson’s correlation coefficient between the ITE and the EM-ACE was 0.62. R-squared was 0.5 (adjusted 0.4. The coefficient of determination was 0.41 (95% CI [0.3-0.8]. For every increase of one in the scaled EM-ACE score, we observed a 0.4% increase in the EM in-training score. In a linear regression model using all available variables (EM-ACE, gender, age, clinical exposure to EM, and USMLE Step 1 and Step 2 scores, only the EM-ACE score was significantly associated with the ITE (p<0.05. We observed significant colinearity

  2. The Spatial Distribution of Hepatitis C Virus Infections and Associated Determinants--An Application of a Geographically Weighted Poisson Regression for Evidence-Based Screening Interventions in Hotspots.

    Science.gov (United States)

    Kauhl, Boris; Heil, Jeanne; Hoebe, Christian J P A; Schweikart, Jürgen; Krafft, Thomas; Dukers-Muijrers, Nicole H T M

    2015-01-01

    Hepatitis C Virus (HCV) infections are a major cause for liver diseases. A large proportion of these infections remain hidden to care due to its mostly asymptomatic nature. Population-based screening and screening targeted on behavioural risk groups had not proven to be effective in revealing these hidden infections. Therefore, more practically applicable approaches to target screenings are necessary. Geographic Information Systems (GIS) and spatial epidemiological methods may provide a more feasible basis for screening interventions through the identification of hotspots as well as demographic and socio-economic determinants. Analysed data included all HCV tests (n = 23,800) performed in the southern area of the Netherlands between 2002-2008. HCV positivity was defined as a positive immunoblot or polymerase chain reaction test. Population data were matched to the geocoded HCV test data. The spatial scan statistic was applied to detect areas with elevated HCV risk. We applied global regression models to determine associations between population-based determinants and HCV risk. Geographically weighted Poisson regression models were then constructed to determine local differences of the association between HCV risk and population-based determinants. HCV prevalence varied geographically and clustered in urban areas. The main population at risk were middle-aged males, non-western immigrants and divorced persons. Socio-economic determinants consisted of one-person households, persons with low income and mean property value. However, the association between HCV risk and demographic as well as socio-economic determinants displayed strong regional and intra-urban differences. The detection of local hotspots in our study may serve as a basis for prioritization of areas for future targeted interventions. Demographic and socio-economic determinants associated with HCV risk show regional differences underlining that a one-size-fits-all approach even within small geographic

  3. Dynamic Regression Model for Evaluating the Association Between Atmospheric Conditions and Deaths due to Respiratory Diseases in São Paulo, Brazil

    Directory of Open Access Journals (Sweden)

    Ana Carla dos Santos Gomes

    Full Text Available Abstract The article reports the modeling of mortality due to respiratory diseases emanating from atmospheric conditions, capturing significant associations and verifying the ability of stochastic modeling to predict deaths arising from the relationship between weather conditions and air pollution. The statistical methods used in the analysis were cross-correlation and pre-whitening, in addition to dynamic regression modeling combining the dynamics of time series and the effect of explanatory variables. The results show there are significant associations between mortality and sulfur dioxide, air temperature, atmospheric pressure, relative humidity, and autoregressive structure. The cross-correlations captured significant lags between atmospheric variables and deaths, of two months for SO2 and relative humidity, eleven months for PM10, seven months for O3, and eight months for air temperature and the cross-correlation without lag with NO2. With CO variables, precipitation and atmospheric pressure, cross-correlations were not detected. Stochastic modeling showed that deaths due to respiratory diseases can be predicted from the combination of meteorological and air pollution variables, especially considering the existing trend and seasonality.

  4. Logistic Regression: Concept and Application

    Science.gov (United States)

    Cokluk, Omay

    2010-01-01

    The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…

  5. Factors associated with trait anger level of juvenile offenders in Hubei province: A binary logistic regression analysis.

    Science.gov (United States)

    Tang, Li-Na; Ye, Xiao-Zhou; Yan, Qiu-Ge; Chang, Hong-Juan; Ma, Yu-Qiao; Liu, De-Bin; Li, Zhi-Gen; Yu, Yi-Zhen

    2017-02-01

    The risk factors of high trait anger of juvenile offenders were explored through questionnaire study in a youth correctional facility of Hubei province, China. A total of 1090 juvenile offenders in Hubei province were investigated by self-compiled social-demographic questionnaire, Childhood Trauma Questionnaire (CTQ), and State-Trait Anger Expression Inventory-II (STAXI-II). The risk factors were analyzed by chi-square tests, correlation analysis, and binary logistic regression analysis with SPSS 19.0. A total of 1082 copies of valid questionnaires were collected. High trait anger group (n=316) was defined as those who scored in the upper 27th percentile of STAXI-II trait anger scale (TAS), and the rest were defined as low trait anger group (n=766). The risk factors associated with high level of trait anger included: childhood emotional abuse, childhood sexual abuse, step family, frequent drug abuse, and frequent internet using (P0.05). It was suggested that traumatic experience in childhood and unhealthy life style may significantly increase the level of trait anger in adulthood. The risk factors of high trait anger and their effects should be taken into consideration seriously.

  6. Sparse reduced-rank regression with covariance estimation

    KAUST Repository

    Chen, Lisha

    2014-12-08

    Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.

  7. Sparse reduced-rank regression with covariance estimation

    KAUST Repository

    Chen, Lisha; Huang, Jianhua Z.

    2014-01-01

    Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.

  8. Investigation of linear regression of EPR dosimetric signal of the man tooth enamel

    International Nuclear Information System (INIS)

    Pivovarov, S.P.; Rukhin, A.B.; Zhakparov, R.K.; Vasilevskaya, L.A.

    2001-01-01

    The experimental relations of the EPR radiation signal in samples of man tooth enamel of three donors of different age up to doses 1350 Gy are examined. To all of them the linear regression is applicable. The considerable errors leading to apparent non-linearity are eliminated most. (author)

  9. Spontaneous regression of intracranial malignant lymphoma. Case report

    Energy Technology Data Exchange (ETDEWEB)

    Kojo, Nobuto; Tokutomi, Takashi; Eguchi, Gihachirou; Takagi, Shigeyuki; Matsumoto, Tomie; Sasaguri, Yasuyuki; Shigemori, Minoru.

    1988-05-01

    In a 46-year-old female with a 1-month history of gait and speech disturbances, computed tomography (CT) demonstrated mass lesions of slightly high density in the left basal ganglia and left frontal lobe. The lesions were markedly enhanced by contrast medium. The patient received no specific treatment, but her clinical manifestations gradually abated and the lesions decreased in size. Five months after her initial examination, the lesions were absent on CT scans; only a small area of low density remained. Residual clinical symptoms included mild right hemiparesis and aphasia. After 14 months the patient again deteriorated, and a CT scan revealed mass lesions in the right frontal lobe and the pons. However, no enhancement was observed in the previously affected regions. A biopsy revealed malignant lymphoma. Despite treatment with steroids and radiation, the patient's clinical status progressively worsened and she died 27 months after initial presentation. Seven other cases of spontaneous regression of primary malignant lymphoma have been reported. In this case, the mechanism of the spontaneous regression was not clear, but changes in immunologic status may have been involved.

  10. Evidence for genetic factors explaining the association between birth weight and low-density lipoprotein cholesterol and possible intrauterine factors influencing the association between birth weight and high-density lipoprotein cholesterol: Analysis in twins

    NARCIS (Netherlands)

    IJzerman, R.G.; Stehouwer, C.D.A.; van Weissenbruch, M.M.; de Geus, E.J.C.; Boomsma, D.I.

    2001-01-01

    Recent studies have demonstrated an association between low weight at birth and an atherogenic lipid profile in later life. To examine the influences of intrauterine and genetic factors, we investigated 53 dizygotic and 61 monozygotic adolescent twin pairs. Regression analysis demonstrated that low

  11. High-throughput quantitative biochemical characterization of algal biomass by NIR spectroscopy; multiple linear regression and multivariate linear regression analysis.

    Science.gov (United States)

    Laurens, L M L; Wolfrum, E J

    2013-12-18

    One of the challenges associated with microalgal biomass characterization and the comparison of microalgal strains and conversion processes is the rapid determination of the composition of algae. We have developed and applied a high-throughput screening technology based on near-infrared (NIR) spectroscopy for the rapid and accurate determination of algal biomass composition. We show that NIR spectroscopy can accurately predict the full composition using multivariate linear regression analysis of varying lipid, protein, and carbohydrate content of algal biomass samples from three strains. We also demonstrate a high quality of predictions of an independent validation set. A high-throughput 96-well configuration for spectroscopy gives equally good prediction relative to a ring-cup configuration, and thus, spectra can be obtained from as little as 10-20 mg of material. We found that lipids exhibit a dominant, distinct, and unique fingerprint in the NIR spectrum that allows for the use of single and multiple linear regression of respective wavelengths for the prediction of the biomass lipid content. This is not the case for carbohydrate and protein content, and thus, the use of multivariate statistical modeling approaches remains necessary.

  12. Association between long working hours and serum gamma-glutamyltransferase levels in female workers: data from the fifth Korean National Health and Nutrition Examination Survey (2010-2011).

    Science.gov (United States)

    Park, Seung-Gwon; Lee, Yong-Jin; Ham, Jung-Oh; Jang, Eun-Chul; Kim, Seong-Woo; Park, Hyun

    2014-01-01

    The present study investigated the association between long working hours and serum gamma-glutamyltransferase (GGT) levels, a factor influencing the incidence of cardiovascular disease. Data from the fifth Korean National Health and Nutrition Examination Survey (2010-2011) were used to analyze 1,809 women. Subjects were divided into three groups based on the number of weekly working hours: ≤29, 30-51, and ≥52 hours per week. Complex samples logistic regression was performed after adjusting for general and occupational factors to determine the association between long working hours and high serum GGT levels. The prevalence of high serum GGT levels in groups with ≤29, 30-51, and ≥52 working hours per week was 22.0%, 16.9%, and 26.6%, respectively. Even after adjusting for general and occupational factors, those working 30-51 hours per week had the lowest prevalence of high serum GGT levels. Compared to those working 30-51 hours per week, the odds ratios (OR) of having high serum GGT levels in the groups with ≥52 and ≤29 working hours per week were 1.56 (95% confidence interval [CI], 1.10-2.23) and 1.53 (95% CI, 1.05-2.24), respectively. Long working hours were significantly associated with high serum GGT levels in Korean women.

  13. Approximate median regression for complex survey data with skewed response.

    Science.gov (United States)

    Fraser, Raphael André; Lipsitz, Stuart R; Sinha, Debajyoti; Fitzmaurice, Garrett M; Pan, Yi

    2016-12-01

    The ready availability of public-use data from various large national complex surveys has immense potential for the assessment of population characteristics using regression models. Complex surveys can be used to identify risk factors for important diseases such as cancer. Existing statistical methods based on estimating equations and/or utilizing resampling methods are often not valid with survey data due to complex survey design features. That is, stratification, multistage sampling, and weighting. In this article, we accommodate these design features in the analysis of highly skewed response variables arising from large complex surveys. Specifically, we propose a double-transform-both-sides (DTBS)'based estimating equations approach to estimate the median regression parameters of the highly skewed response; the DTBS approach applies the same Box-Cox type transformation twice to both the outcome and regression function. The usual sandwich variance estimate can be used in our approach, whereas a resampling approach would be needed for a pseudo-likelihood based on minimizing absolute deviations (MAD). Furthermore, the approach is relatively robust to the true underlying distribution, and has much smaller mean square error than a MAD approach. The method is motivated by an analysis of laboratory data on urinary iodine (UI) concentration from the National Health and Nutrition Examination Survey. © 2016, The International Biometric Society.

  14. Factors Associated With Caregivers' Resilience in a Terminal Cancer Care Setting.

    Science.gov (United States)

    Hwang, In Cheol; Kim, Young Sung; Lee, Yong Joo; Choi, Youn Seon; Hwang, Sun Wook; Kim, Hyo Min; Koh, Su-Jin

    2018-04-01

    Resilience implies characteristics such as self-efficacy, adaptability to change, optimism, and the ability to recover from traumatic stress. Studies on resilience in family caregivers (FCs) of patients with terminal cancer are rare. This study aims to examine the factors associated with FCs' resilience in a terminal cancer care setting. This is a cross-sectional study of 273 FCs from 7 hospice and palliative care units in Korea. Resilience was categorized as high and low, and factors associated with resilience were grouped or categorized into subscales. A multivariate logistic regression analysis was used to examine relevant factors. High FCs' resilience was significantly associated with FCs' health status, depression, and social support. In a multivariate regression model, FCs' perception of good health (adjusted odds ratio [aOR] = 2.26, 95% confidence interval [CI] = 1.16-4.40), positive social support (aOR = 3.70, 95% CI = 1.07-12.87), and absence of depression (aOR = 3.12, 95% CI = 1.59-6.13) remained significantly associated with high FCs' resilience. Lack of family support is associated with and may be a cause of diminished resilience. And more concern should be paid to FCs to improve FCs' health and emotional status. Education programs might be effective for improving caregivers' resilience. Further research with supportive interventions is indicated.

  15. Regression models of reactor diagnostic signals

    International Nuclear Information System (INIS)

    Vavrin, J.

    1989-01-01

    The application is described of an autoregression model as the simplest regression model of diagnostic signals in experimental analysis of diagnostic systems, in in-service monitoring of normal and anomalous conditions and their diagnostics. The method of diagnostics is described using a regression type diagnostic data base and regression spectral diagnostics. The diagnostics is described of neutron noise signals from anomalous modes in the experimental fuel assembly of a reactor. (author)

  16. Metabolomics study on primary dysmenorrhea patients during the luteal regression stage based on ultra performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry

    Science.gov (United States)

    Fang, Ling; Gu, Caiyun; Liu, Xinyu; Xie, Jiabin; Hou, Zhiguo; Tian, Meng; Yin, Jia; Li, Aizhu; Li, Yubo

    2017-01-01

    Primary dysmenorrhea (PD) is a common gynecological disorder which, while not life-threatening, severely affects the quality of life of women. Most patients with PD suffer ovarian hormone imbalances caused by uterine contraction, which results in dysmenorrhea. PD patients may also suffer from increases in estrogen levels caused by increased levels of prostaglandin synthesis and release during luteal regression and early menstruation. Although PD pathogenesis has been previously reported on, these studies only examined the menstrual period and neglected the importance of the luteal regression stage. Therefore, the present study used urine metabolomics to examine changes in endogenous substances and detect urine biomarkers for PD during luteal regression. Ultra performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry was used to create metabolomic profiles for 36 patients with PD and 27 healthy controls. Principal component analysis and partial least squares discriminate analysis were used to investigate the metabolic alterations associated with PD. Ten biomarkers for PD were identified, including ornithine, dihydrocortisol, histidine, citrulline, sphinganine, phytosphingosine, progesterone, 17-hydroxyprogesterone, androstenedione, and 15-keto-prostaglandin F2α. The specificity and sensitivity of these biomarkers was assessed based on the area under the curve of receiver operator characteristic curves, which can be used to distinguish patients with PD from healthy controls. These results provide novel targets for the treatment of PD. PMID:28098892

  17. Examination of a recommended algorithm for eliminating nonsystematic delay discounting response sets.

    Science.gov (United States)

    White, Thomas J; Redner, Ryan; Skelly, Joan M; Higgins, Stephen T

    2015-09-01

    To examine (1) whether use of a recommended algorithm (Johnson and Bickel, 2008) improves upon conventional statistical model fit (R(2)) for identifying nonsystematic response sets in delay discounting (DD) data, (2) whether removing such data meaningfully effects research outcomes, and (3) to identify participant characteristics associated with nonsystematic response sets. Discounting of hypothetical monetary rewards was assessed among 349 pregnant women (231 smokers and 118 recent quitters) via a computerized task comparing $1000 at seven future time points with smaller values available immediately. Nonsystematic response sets were identified using the algorithm and conventional statistical model fit (R(2)). The association between DD and quitting was analyzed with and without nonsystematic response sets to examine whether the inclusion or exclusion impacts this relationship. Logistic regression was used to examine whether participant sociodemographics were associated with nonsystematic response sets. The algorithm excluded fewer cases than the R(2) method (14% vs. 16%), and was not correlated with logk as is R(2). The relationship between logk and the clinical outcome (spontaneous quitting) was unaffected by exclusion methods; however, other variables in the model were affected. Lower educational attainment and younger age were associated with nonsystematic response sets. The algorithm eliminated data that were inconsistent with the nature of discounting and retained data that were orderly. Neither method impacted the smoking/DD relationship in this data set. Nonsystematic response sets are more likely among younger and less educated participants, who may need extra training or support in DD studies. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  18. Affect and subsequent physical activity: An ambulatory assessment study examining the affect-activity association in a real-life context

    Directory of Open Access Journals (Sweden)

    Christina eNiermann

    2016-05-01

    Full Text Available Traditionally, cognitive, motivational and volitional determinants have been used to explain and predict health behaviors such as physical activity. Recently, the role of affect in influencing and regulating health behaviors received more attention. Affects as internal cues may automatically activate unconscious processes of behavior regulation. The aim of our study was to examine the association between affect and physical activity in daily life. In addition, we studied the influence of the habit of being physically active on this relationship.An ambulatory assessment study in 89 persons (33.7% male, 25 to 65 years, M=45.2, SD=8.1 was conducted. Affect was assessed in the afternoon on 5 weekdays using smartphones. Physical activity was measured continuously objectively using accelerometers and subjectively using smartphones in the evening. Habit strength was assessed at the beginning of the diary period. The outcomes were objectively and subjectively measured moderate-to-vigorous physical activity (MVPA performed after work. Multilevel regression models were used to analyze the association between affect and after work MVPA. In addition, the cross-level interaction of habit strength and affect on after work MVPA was tested.Positive affect was positively related to objectively measured and self-reported after work MVPA: the greater the positive affect the more time persons subsequently spent on MVPA. An inverse relationship was found for negative affect: the greater the negative affect the less time persons spent on MVPA. The cross-level interaction effect was significant only for objectively measured MVPA. A strong habit seems to strengthen both the positive influence of positive affect and the negative influence of negative affect.The results of this study confirm previous results and indicate that affect plays an important role for the regulation of physical activity behavior in daily life. The results for positive affect were consistent

  19. Affect and Subsequent Physical Activity: An Ambulatory Assessment Study Examining the Affect-Activity Association in a Real-Life Context.

    Science.gov (United States)

    Niermann, Christina Y N; Herrmann, Christian; von Haaren, Birte; van Kann, Dave; Woll, Alexander

    2016-01-01

    Traditionally, cognitive, motivational, and volitional determinants have been used to explain and predict health behaviors such as physical activity. Recently, the role of affect in influencing and regulating health behaviors received more attention. Affects as internal cues may automatically activate unconscious processes of behavior regulation. The aim of our study was to examine the association between affect and physical activity in daily life. In addition, we studied the influence of the habit of being physically active on this relationship. An ambulatory assessment study in 89 persons (33.7% male, 25 to 65 years, M = 45.2, SD = 8.1) was conducted. Affect was assessed in the afternoon on 5 weekdays using smartphones. Physical activity was measured continuously objectively using accelerometers and subjectively using smartphones in the evening. Habit strength was assessed at the beginning of the diary period. The outcomes were objectively and subjectively measured moderate-to-vigorous physical activity (MVPA) performed after work. Multilevel regression models were used to analyze the association between affect and after work MVPA. In addition, the cross-level interaction of habit strength and affect on after work MVPA was tested. Positive affect was positively related to objectively measured and self-reported after work MVPA: the greater the positive affect the more time persons subsequently spent on MVPA. An inverse relationship was found for negative affect: the greater the negative affect the less time persons spent on MVPA. The cross-level interaction effect was significant only for objectively measured MVPA. A strong habit seems to strengthen both the positive influence of positive affect and the negative influence of negative affect. The results of this study confirm previous results and indicate that affect plays an important role for the regulation of physical activity behavior in daily life. The results for positive affect were consistent. However, in

  20. Management of Industrial Performance Indicators: Regression Analysis and Simulation

    Directory of Open Access Journals (Sweden)

    Walter Roberto Hernandez Vergara

    2017-11-01

    Full Text Available Stochastic methods can be used in problem solving and explanation of natural phenomena through the application of statistical procedures. The article aims to associate the regression analysis and systems simulation, in order to facilitate the practical understanding of data analysis. The algorithms were developed in Microsoft Office Excel software, using statistical techniques such as regression theory, ANOVA and Cholesky Factorization, which made it possible to create models of single and multiple systems with up to five independent variables. For the analysis of these models, the Monte Carlo simulation and analysis of industrial performance indicators were used, resulting in numerical indices that aim to improve the goals’ management for compliance indicators, by identifying systems’ instability, correlation and anomalies. The analytical models presented in the survey indicated satisfactory results with numerous possibilities for industrial and academic applications, as well as the potential for deployment in new analytical techniques.

  1. Participant characteristics and intervention processes associated with reductions in television viewing in the High Five for Kids study.

    Science.gov (United States)

    Cespedes, Elizabeth M; Horan, Christine M; Gillman, Matthew W; Gortmaker, Steven L; Price, Sarah; Rifas-Shiman, Sheryl L; Mitchell, Kathleen; Taveras, Elsie M

    2014-05-01

    To evaluate the High Five for Kids intervention effect on television within subgroups, examine participant characteristics associated with process measures and assess perceived helpfulness of television intervention components. High Five (randomized controlled trial of 445 overweight/obese 2-7 year-olds in Massachusetts [2006-2008]) reduced television by 0.36 h/day. 1-year effects on television viewing, stratified by subgroup, were assessed using linear regression. Among intervention participants (n=253), associations of intervention component helpfulness with television reduction were examined using linear regression and associations of participant characteristics with processes linked to television reduction (choosing television and completing intervention visits) were examined using logistic regression. High Five reduced television across subgroups. Parents of Latino (versus white) children had lower odds of completing ≥2 study visits (Odds Ratio: 0.39 [95% Confidence Interval: 0.18, 0.84]). Parents of black (versus white) children had higher odds of choosing television (Odds Ratio: 2.23 [95% Confidence Interval: 1.08, 4.59]), as did parents of obese (versus overweight) children and children watching ≥2 h/day (versus television reduction. Clinic-based motivational interviewing reduces television viewing in children. Low cost education approaches (e.g., printed materials) may be well-received. Parents of children at higher obesity risk could be more motivated to reduce television. Copyright © 2014 Elsevier Inc. All rights reserved.

  2. Association between resting-state brain network topological organization and creative ability: Evidence from a multiple linear regression model.

    Science.gov (United States)

    Jiao, Bingqing; Zhang, Delong; Liang, Aiying; Liang, Bishan; Wang, Zengjian; Li, Junchao; Cai, Yuxuan; Gao, Mengxia; Gao, Zhenni; Chang, Song; Huang, Ruiwang; Liu, Ming

    2017-10-01

    Previous studies have indicated a tight linkage between resting-state functional connectivity of the human brain and creative ability. This study aimed to further investigate the association between the topological organization of resting-state brain networks and creativity. Therefore, we acquired resting-state fMRI data from 22 high-creativity participants and 22 low-creativity participants (as determined by their Torrance Tests of Creative Thinking scores). We then constructed functional brain networks for each participant and assessed group differences in network topological properties before exploring the relationships between respective network topological properties and creative ability. We identified an optimized organization of intrinsic brain networks in both groups. However, compared with low-creativity participants, high-creativity participants exhibited increased global efficiency and substantially decreased path length, suggesting increased efficiency of information transmission across brain networks in creative individuals. Using a multiple linear regression model, we further demonstrated that regional functional integration properties (i.e., the betweenness centrality and global efficiency) of brain networks, particularly the default mode network (DMN) and sensorimotor network (SMN), significantly predicted the individual differences in creative ability. Furthermore, the associations between network regional properties and creative performance were creativity-level dependent, where the difference in the resource control component may be important in explaining individual difference in creative performance. These findings provide novel insights into the neural substrate of creativity and may facilitate objective identification of creative ability. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Neighborhood Disorder and the Sense of Personal Control: Which Factors Moderate the Association?

    Science.gov (United States)

    Kim, Joongbaeck; Conley, Meghan E.

    2011-01-01

    This study examines whether and how select individual characteristics moderate the relationship between neighborhood disorder and a sense of personal control. Our findings show that neighborhood disorder is associated with a decreased sense of control. However, regression analyses including interaction terms of neighborhood disorder and some…

  4. Regression and Sparse Regression Methods for Viscosity Estimation of Acid Milk From it’s Sls Features

    DEFF Research Database (Denmark)

    Sharifzadeh, Sara; Skytte, Jacob Lercke; Nielsen, Otto Højager Attermann

    2012-01-01

    Statistical solutions find wide spread use in food and medicine quality control. We investigate the effect of different regression and sparse regression methods for a viscosity estimation problem using the spectro-temporal features from new Sub-Surface Laser Scattering (SLS) vision system. From...... with sparse LAR, lasso and Elastic Net (EN) sparse regression methods. Due to the inconsistent measurement condition, Locally Weighted Scatter plot Smoothing (Loess) has been employed to alleviate the undesired variation in the estimated viscosity. The experimental results of applying different methods show...

  5. Testing discontinuities in nonparametric regression

    KAUST Repository

    Dai, Wenlin

    2017-01-19

    In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

  6. Testing discontinuities in nonparametric regression

    KAUST Repository

    Dai, Wenlin; Zhou, Yuejin; Tong, Tiejun

    2017-01-01

    In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

  7. The role of impulsivity in the association between childhood trauma and dissociative psychopathology: mediation versus moderation.

    Science.gov (United States)

    Somer, Eli; Ginzburg, Karni; Kramer, Lilach

    2012-03-30

    Previous studies on survivors of childhood trauma documented associations between psychological dysregulation, impulsivity, and both behavioral and emotional manifestations of distress. Yet, the mechanism that links these variables remains unclear. The current study aims to examine the pattern of relations between a history of child abuse, impulsivity and dissociation. More specifically, it examines whether impulsivity serves as a moderator or mediator in the association between childhood trauma and dissociation. Eighty-one inpatients from the acute wards of two psychiatric hospitals participated in this study. Data were collected by clinician-administered questionnaires. A highly significant linear hierarchical regression analysis revealed that both psychiatric comorbidity and childhood trauma made unique contributions to the variance of dissociation. Yet, the significant association between childhood trauma and dissociation decreased when impulsivity was entered into the regression model. Our findings suggest that impulsivity mediates the association between childhood trauma and dissociative psychopathology and imply that the identification and treatment of impulsivity could be a potentially valuable clinical target in individuals with dissociative disorders. Copyright © 2012 Elsevier Ltd. All rights reserved.

  8. Examining the Risk Factors Associated With Hypertension Among the Elderly in Ghana.

    Science.gov (United States)

    Boateng, Godfred Odei; Luginaah, Isaac N; Taabazuing, Mary-Margaret

    2015-10-01

    This study sought to examine the risk factors associated with hypertension among the elderly in Ghana. We focused on the association between chronic diseases, socioeconomic factors, and being hypertensive. Data for the study were drawn from Wave 1 of the 2007/2008 Ghana Study on Global Ageing and Adult Health (SAGE). A binary logit model was used to estimate the effect of other noncommunicable diseases, psychosocial factors, lifestyle factors, and sociocultural and biosocial factors on the elderly being hypertensive. Elderly Ghanaians who had been diagnosed with arthritis, angina, diabetes, and asthma were significantly more likely to be hypertensive. Additionally, those depressed were found to be 1.22 times more likely to be hypertensive. Prevention and control of hypertension are complex and demand multistakeholder collaboration including governments, educational institutions, media, food and beverage industry, and a conscious focus on personal lifestyle factors. © The Author(s) 2015.

  9. On Solving Lq-Penalized Regressions

    Directory of Open Access Journals (Sweden)

    Tracy Zhou Wu

    2007-01-01

    Full Text Available Lq-penalized regression arises in multidimensional statistical modelling where all or part of the regression coefficients are penalized to achieve both accuracy and parsimony of statistical models. There is often substantial computational difficulty except for the quadratic penalty case. The difficulty is partly due to the nonsmoothness of the objective function inherited from the use of the absolute value. We propose a new solution method for the general Lq-penalized regression problem based on space transformation and thus efficient optimization algorithms. The new method has immediate applications in statistics, notably in penalized spline smoothing problems. In particular, the LASSO problem is shown to be polynomial time solvable. Numerical studies show promise of our approach.

  10. Factors and common conditions associated with adolescent dietary supplement use: an analysis of the National Health and Nutrition Examination Survey (NHANES

    Directory of Open Access Journals (Sweden)

    Davis Roger B

    2008-03-01

    Full Text Available Abstract Background Little is known about the prevalence of dietary supplement (DS use in American adolescents. We conducted this study to analyze the prevalence of DS use and factors associated with this use in a national population-based sample. Methods We used data from the 1999 – 2002 National Health and Nutrition Examination Surveys (NHANES for adolescents age 11 to 19. Using weighted logistic regression, we identified demographic and clinical factors associated with the use of any DS, vitamins or minerals, herbs and other DS. Results Among the 5,306 responses representing approximately 36 million Americans 11–19 years old, 27% reported use of one or more DS in the prior month. The most commonly used DS were: multivitamins (16% and vitamin C (6%. In the multivariable analysis, African American [adjusted odds ratio 0.40 (0.31–0.50 95% CI] and Mexican American [0.55 (0.44–0.69] adolescents were less likely to use DS compared with non-Hispanic whites. DS use was more common in those who used prescription medications [1.37 (1.10–1.72] and among those who had a diagnosis of chronic headaches [1.25 (1.04–1.50]. DS use was less common among those reporting fair or poor health status [0.59 (0.40–0.88]. Conclusion Twenty seven percent of American adolescents use DS. DS use is higher among teens that use prescription medications; physicians and pharmacists should be aware of this, ask patients, and check for potential interactions.

  11. Caudal Regression and Encephalocele: Rare Manifestations of Expanded Goldenhar Complex

    Directory of Open Access Journals (Sweden)

    Gabriella D’Angelo

    2017-01-01

    Full Text Available Oculoauriculovertebral spectrum, or Goldenhar Syndrome, is a condition characterized by variable degrees of uni- or bilateral involvement of craniofacial structures, ocular anomalies, and vertebral defects. Its expressivity is variable; therefore, the term “expanded Goldenhar complex” has been coined. The Goldenhar Syndrome usually involves anomalies in craniofacial structures, but it is known that nervous system anomalies, including encephalocele or caudal regression, may, rarely, occur in this condition. We report two rare cases of infants affected by Goldenhar Syndrome, associated with neural tube defects, specifically caudal regression syndrome and nasal encephaloceles, to underline the extremely complex and heterogeneous clinical features of this oculoauriculovertebral spectrum. These additional particular cases could increase the number of new variable spectrums to be included in the “expanded Goldenhar complex.”

  12. Relationship between prosthodontic status and nutritional intake in the elderly in Korea: National Health and Nutrition Examination Survey (NHANES IV).

    Science.gov (United States)

    Choi, Y K; Park, D Y; Kim, Y

    2014-11-01

    Many health issues have been reported to be associated with poor nutritional status. We sought to examine the association between nutritional intake and oral health status in elderly people. The association between perceived disability in mastication and prosthodontic status was analysed using multiple logistic regression. Multiple linear regression was used to analyse the association between prosthodontic status and nutritional intake. The elderly subjects with partial or full dentures reported chewing difficulties 1.62-fold more frequently (95% CI: 1.06-2.49) than those with natural teeth or a fixed prosthesis after adjusting for gender, TMD (temporomandibular disorder), household income and education level. Additionally, daily nutritional intakes of energy, protein, fat, ash, calcium, phosphorus and thiamine were decreased significantly in elderly with partial or full dentures compared with those with no prosthesis or with a fixed prosthesis (P oral health status and perceived disability in mastication are associated with dietary imbalances in the elderly. We suggest that the evaluation of patients' nutritional status should be considered as a part of an overall plan for dental hygiene care. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  13. Testing of a Fiber Optic Wear, Erosion and Regression Sensor

    Science.gov (United States)

    Korman, Valentin; Polzin, Kurt A.

    2011-01-01

    The nature of the physical processes and harsh environments associated with erosion and wear in propulsion environments makes their measurement and real-time rate quantification difficult. A fiber optic sensor capable of determining the wear (regression, erosion, ablation) associated with these environments has been developed and tested in a number of different applications to validate the technique. The sensor consists of two fiber optics that have differing attenuation coefficients and transmit light to detectors. The ratio of the two measured intensities can be correlated to the lengths of the fiber optic lines, and if the fibers and the host parent material in which they are embedded wear at the same rate the remaining length of fiber provides a real-time measure of the wear process. Testing in several disparate situations has been performed, with the data exhibiting excellent qualitative agreement with the theoretical description of the process and when a separate calibrated regression measurement is available good quantitative agreement is obtained as well. The light collected by the fibers can also be used to optically obtain the spectra and measure the internal temperature of the wear layer.

  14. Boosted regression trees, multivariate adaptive regression splines and their two-step combinations with multiple linear regression or partial least squares to predict blood-brain barrier passage: a case study.

    Science.gov (United States)

    Deconinck, E; Zhang, M H; Petitet, F; Dubus, E; Ijjaali, I; Coomans, D; Vander Heyden, Y

    2008-02-18

    The use of some unconventional non-linear modeling techniques, i.e. classification and regression trees and multivariate adaptive regression splines-based methods, was explored to model the blood-brain barrier (BBB) passage of drugs and drug-like molecules. The data set contains BBB passage values for 299 structural and pharmacological diverse drugs, originating from a structured knowledge-based database. Models were built using boosted regression trees (BRT) and multivariate adaptive regression splines (MARS), as well as their respective combinations with stepwise multiple linear regression (MLR) and partial least squares (PLS) regression in two-step approaches. The best models were obtained using combinations of MARS with either stepwise MLR or PLS. It could be concluded that the use of combinations of a linear with a non-linear modeling technique results in some improved properties compared to the individual linear and non-linear models and that, when the use of such a combination is appropriate, combinations using MARS as non-linear technique should be preferred over those with BRT, due to some serious drawbacks of the BRT approaches.

  15. Testing Heteroscedasticity in Robust Regression

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2011-01-01

    Roč. 1, č. 4 (2011), s. 25-28 ISSN 2045-3345 Grant - others:GA ČR(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust regression * heteroscedasticity * regression quantiles * diagnostics Subject RIV: BB - Applied Statistics , Operational Research http://www.researchjournals.co.uk/documents/Vol4/06%20Kalina.pdf

  16. Diabetic Prevalence in Bangladesh: The Role of Some Associated Demographic and Socioeconomic Characteristics

    Science.gov (United States)

    Imam, Tasneem

    2012-12-01

    The study attempts at examining the association of a few selected socio-economic and demographic characteristics on diabetic prevalence. Nationally representative data from BIRDEM 2000 have been used to meet the objectives of the study. Cross tabulation, Chi-square and logistic regression analysis have been used to portray the necessary associations. Chi- square reveals significant relationship between diabetic prevalence and all the selected demographic and socio-economic variables except ìeducationî while logistic regression analysis shows no significant contribution of ìageî and ìeducationî in diabetic prevalence. It has to be noted that, this paper dealt with all the three types of diabetes- Type 1, Type 2 and Gestational.

  17. Examining neighborhood and interpersonal norms and social support on fruit and vegetable intake in low-income communities.

    Science.gov (United States)

    Dulin, Akilah; Risica, Patricia M; Mello, Jennifer; Ahmed, Rashid; Carey, Kate B; Cardel, Michelle; Howe, Chanelle J; Nadimpalli, Sarah; Gans, Kim M

    2018-04-05

    We examined whether neighborhood-, friend-, and family- norms and social support for consumption and purchase of fruits and vegetables (F&V) were associated with F&V intake among low-income residents in subsidized housing communities. We examined baseline data from a study ancillary to the Live Well/Viva Bien intervention. Participants included 290 residents in four low-income subsidized housing sites who were ≥ 18 years of age, English and/or Spanish speaking, and without medical conditions that prevented consumption of F&V. Linear regression models examined associations of norms and social support with F&V intake after adjustments for sociodemographic characteristics. In the analysis, neighborhood social support for F&V was associated with a 0.31 cup increase in F&V intake (95% CI = 0.05, 0.57). The family norm for eating F&V and family social support for eating F&V were associated with a 0.32 cup (95% CI = 0.13, 0.52) and 0.42 cup (95% CI = 0.19, 0.64) increase in F&V intake, respectively. To our knowledge, no other studies have examined neighborhood, family, and peer norms and social support simultaneously and in relation to F&V intake. These findings may inform neighborhood interventions and community-level policies to reduce neighborhood disparities in F&V consumption.

  18. Robust logistic regression to narrow down the winner's curse for rare and recessive susceptibility variants.

    Science.gov (United States)

    Kesselmeier, Miriam; Lorenzo Bermejo, Justo

    2017-11-01

    Logistic regression is the most common technique used for genetic case-control association studies. A disadvantage of standard maximum likelihood estimators of the genotype relative risk (GRR) is their strong dependence on outlier subjects, for example, patients diagnosed at unusually young age. Robust methods are available to constrain outlier influence, but they are scarcely used in genetic studies. This article provides a non-intimidating introduction to robust logistic regression, and investigates its benefits and limitations in genetic association studies. We applied the bounded Huber and extended the R package 'robustbase' with the re-descending Hampel functions to down-weight outlier influence. Computer simulations were carried out to assess the type I error rate, mean squared error (MSE) and statistical power according to major characteristics of the genetic study and investigated markers. Simulations were complemented with the analysis of real data. Both standard and robust estimation controlled type I error rates. Standard logistic regression showed the highest power but standard GRR estimates also showed the largest bias and MSE, in particular for associated rare and recessive variants. For illustration, a recessive variant with a true GRR=6.32 and a minor allele frequency=0.05 investigated in a 1000 case/1000 control study by standard logistic regression resulted in power=0.60 and MSE=16.5. The corresponding figures for Huber-based estimation were power=0.51 and MSE=0.53. Overall, Hampel- and Huber-based GRR estimates did not differ much. Robust logistic regression may represent a valuable alternative to standard maximum likelihood estimation when the focus lies on risk prediction rather than identification of susceptibility variants. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  19. The limiting behavior of the estimated parameters in a misspecified random field regression model

    DEFF Research Database (Denmark)

    Dahl, Christian Møller; Qin, Yu

    This paper examines the limiting properties of the estimated parameters in the random field regression model recently proposed by Hamilton (Econometrica, 2001). Though the model is parametric, it enjoys the flexibility of the nonparametric approach since it can approximate a large collection of n...

  20. Regression Analysis by Example. 5th Edition

    Science.gov (United States)

    Chatterjee, Samprit; Hadi, Ali S.

    2012-01-01

    Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. "Regression Analysis by Example, Fifth Edition" has been expanded and thoroughly…