Supine position and nonmodifiable risk factors for ventilator-associated pneumonia in trauma patients.

Science.gov (United States)

Michetti, Christopher P; Prentice, Heather A; Rodriguez, Jennifer; Newcomb, Anna

2017-02-01

We studied trauma-specific conditions precluding semiupright positioning and other nonmodifiable risk factors for their influence on ventilator-associated pneumonia (VAP). We performed a retrospective study at a Level I trauma center from 2008 to 2012 on ICU patients aged ≥15, who were intubated for more than 2 days. Using backward logistic regression, a composite of 4 factors (open abdomen, acute spinal cord injury, spine fracture, spine surgery) that preclude semiupright positioning (supine composite) and other variables were analyzed. In total, 77 of 374 (21%) patients had VAP. Abbreviated Injury Score head/neck greater than 2 (odds ratio [OR] 2.79, P = .006), esophageal obturator airway (OR 4.25, P = .015), red cell/plasma transfusion in the first 2 intensive care unit days (OR 2.59, P = .003), and 11 or more ventilator days (OR 17.38, P VAP risk factors, whereas supine composite, scene vs emergency department airway intervention, brain injury, and coma were not. Factors that may temporarily preclude semiupright positioning in intubated trauma patients were not associated with a higher risk for VAP. Copyright © 2016 Elsevier Inc. All rights reserved.

Extrinsic Factors as Component Positions to Bone and Intrinsic Factors Affecting Postoperative Rotational Limb Alignment in Total Knee Arthroplasty.

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Mochizuki, Tomoharu; Sato, Takashi; Tanifuji, Osamu; Watanabe, Satoshi; Kobayashi, Koichi; Endo, Naoto

2018-02-13

This study aimed to identify the factors affecting postoperative rotational limb alignment of the tibia relative to the femur. We hypothesized that not only component positions but also several intrinsic factors were associated with postoperative rotational limb alignment. This study included 99 knees (90 women and 9 men) with a mean age of 77 ± 6 years. A three-dimensional (3D) assessment system was applied under weight-bearing conditions to biplanar long-leg radiographs using 3D-to-2D image registration technique. The evaluation parameters were (1) component position; (2) preoperative and postoperative coronal, sagittal, and rotational limb alignment; (3) preoperative bony deformity, including femoral torsion, condylar twist angle, and tibial torsion; and (4) preoperative and postoperative range of motion (ROM). In multiple linear regression analysis using a stepwise procedure, postoperative rotational limb alignment was associated with the following: (1) rotation of the component position (tibia: β = 0.371, P intrinsic factors, such as preoperative rotational limb alignment, ROM, and tibial torsion, affected postoperative rotational limb alignment. On a premise of correct component positions, the intrinsic factors that can be controlled by surgeons should be taken care. In particular, ROM is necessary to be improved within the possible range to acquire better postoperative rotational limb alignment. Copyright © 2018 Elsevier Inc. All rights reserved.

Risk factors for HIV positivity among more than 3,400 Tanzanian women

DEFF Research Database (Denmark)

Faber, Mette Tuxen; Munk, Christian; Mwaiselage, Julius

2017-01-01

In a cross-sectional study of 3,424 women from urban (Dar es Salaam) and rural (Pwani, Mwanza, and Mtwara) Tanzania, conducted in 2008–2009, we investigated risk factors for human immunodeficiency virus (HIV) and the association between different measures of human papillomavirus (HPV) and HIV...... positivity. Study participants were interviewed about socio-demographic and reproductive factors and sexual behavior. Blood samples were tested for HIV, and the women underwent a gynecological examination. HPV status was determined by Hybrid Capture 2, and HPV genotyping was performed using the LiPA Extra...... test. Multivariable logistic regression models estimating odds ratios (OR) and 95% confidence intervals (CI) were used. The overall HIV prevalence was 10.2%. HIV-positive women were more likely to have high-risk (HR) HPV detected (OR = 4.11; 95% CI: 3.23–5.24) and clinically visible genital warts (OR...

Estimation of a Reactor Core Power Peaking Factor Using Support Vector Regression and Uncertainty Analysis

International Nuclear Information System (INIS)

Bae, In Ho; Naa, Man Gyun; Lee, Yoon Joon; Park, Goon Cherl

2009-01-01

The monitoring of detailed 3-dimensional (3D) reactor core power distribution is a prerequisite in the operation of nuclear power reactors to ensure that various safety limits imposed on the LPD and DNBR, are not violated during nuclear power reactor operation. The LPD and DNBR should be calculated in order to perform the two major functions of the core protection calculator system (CPCS) and the core operation limit supervisory system (COLSS). The LPD at the hottest part of a hot fuel rod, which is related to the power peaking factor (PPF, F q ), is more important than the LPD at any other position in a reactor core. The LPD needs to be estimated accurately to prevent nuclear fuel rods from melting. In this study, support vector regression (SVR) and uncertainty analysis have been applied to estimation of reactor core power peaking factor

Logistic Regression and Path Analysis Method to Analyze Factors influencing Students’ Achievement

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Noeryanti, N.; Suryowati, K.; Setyawan, Y.; Aulia, R. R.

2018-04-01

Students' academic achievement cannot be separated from the influence of two factors namely internal and external factors. The first factors of the student (internal factors) consist of intelligence (X1), health (X2), interest (X3), and motivation of students (X4). The external factors consist of family environment (X5), school environment (X6), and society environment (X7). The objects of this research are eighth grade students of the school year 2016/2017 at SMPN 1 Jiwan Madiun sampled by using simple random sampling. Primary data are obtained by distributing questionnaires. The method used in this study is binary logistic regression analysis that aims to identify internal and external factors that affect student’s achievement and how the trends of them. Path Analysis was used to determine the factors that influence directly, indirectly or totally on student’s achievement. Based on the results of binary logistic regression, variables that affect student’s achievement are interest and motivation. And based on the results obtained by path analysis, factors that have a direct impact on student’s achievement are students’ interest (59%) and students’ motivation (27%). While the factors that have indirect influences on students’ achievement, are family environment (97%) and school environment (37).

DETERMINATION OF FACTORS AFFECTING LENGTH OF STAY WITH MULTINOMIAL LOGISTIC REGRESSION IN TURKEY

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Öğr. Gör. Rukiye NUMAN TEKİN

2016-08-01

Full Text Available Length of stay (LOS has important implications in various aspects of health services, can vary according to a wide range of factors. It is noticed that LOS has been neglected mostly in both theoratical studies and practice of health care management in Turkey. The main purpose of this study is to identify factors related to LOS in Turkey. A retrospective analysis of 2.255.836 patients hospitalized to private, university, foundation university and other (municipality, association and foreigners/minority hospitals hospitals which have an agreement with Social Security Institution (SSI in Turkey, from January 1, 2010, until the December 31, 2010, was examined. Patient’s data were taken from MEDULA (National Electronic Invoice System and SPSS 18.0 was used to perform statistical analysis. In this study t-test, one way anova and multinomial logistic regression are used to determine variables that may affect to LOS. The average LOS of patients was 3,93 days (SD = 5,882. LOS showed a statistically significant difference according to all independent variables used in the study (age, gender, disease class, type of hospitalization, presence of comorbidity, type and number of surgery, season of hospitalization, hospital ownership/bed capacity/ geographical region/residential area/type of service. According to the results of the multinomial lojistic regression analysis, LOS was negatively affected in terms of gender, presence of comorbidity, geographical region of hospital and was positively affected in terms of age, season of hospitalization, hospital bed capacity/ ownership/type of service/residential area.

On the null distribution of Bayes factors in linear regression

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We show that under the null, the 2 log (Bayes factor) is asymptotically distributed as a weighted sum of chi-squared random variables with a shifted mean. This claim holds for Bayesian multi-linear regression with a family of conjugate priors, namely, the normal-inverse-gamma prior, the g-prior, and...

Retrieving relevant factors with exploratory SEM and principal-covariate regression: A comparison.

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Vervloet, Marlies; Van den Noortgate, Wim; Ceulemans, Eva

2018-02-12

Behavioral researchers often linearly regress a criterion on multiple predictors, aiming to gain insight into the relations between the criterion and predictors. Obtaining this insight from the ordinary least squares (OLS) regression solution may be troublesome, because OLS regression weights show only the effect of a predictor on top of the effects of other predictors. Moreover, when the number of predictors grows larger, it becomes likely that the predictors will be highly collinear, which makes the regression weights' estimates unstable (i.e., the "bouncing beta" problem). Among other procedures, dimension-reduction-based methods have been proposed for dealing with these problems. These methods yield insight into the data by reducing the predictors to a smaller number of summarizing variables and regressing the criterion on these summarizing variables. Two promising methods are principal-covariate regression (PCovR) and exploratory structural equation modeling (ESEM). Both simultaneously optimize reduction and prediction, but they are based on different frameworks. The resulting solutions have not yet been compared; it is thus unclear what the strengths and weaknesses are of both methods. In this article, we focus on the extents to which PCovR and ESEM are able to extract the factors that truly underlie the predictor scores and can predict a single criterion. The results of two simulation studies showed that for a typical behavioral dataset, ESEM (using the BIC for model selection) in this regard is successful more often than PCovR. Yet, in 93% of the datasets PCovR performed equally well, and in the case of 48 predictors, 100 observations, and large differences in the strengths of the factors, PCovR even outperformed ESEM.

Identifying the Safety Factors over Traffic Signs in State Roads using a Panel Quantile Regression Approach.

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Šarić, Željko; Xu, Xuecai; Duan, Li; Babić, Darko

2018-06-20

This study intended to investigate the interactions between accident rate and traffic signs in state roads located in Croatia, and accommodate the heterogeneity attributed to unobserved factors. The data from 130 state roads between 2012 and 2016 were collected from Traffic Accident Database System maintained by the Republic of Croatia Ministry of the Interior. To address the heterogeneity, a panel quantile regression model was proposed, in which quantile regression model offers a more complete view and a highly comprehensive analysis of the relationship between accident rate and traffic signs, while the panel data model accommodates the heterogeneity attributed to unobserved factors. Results revealed that (1) low visibility of material damage (MD) and death or injured (DI) increased the accident rate; (2) the number of mandatory signs and the number of warning signs were more likely to reduce the accident rate; (3)average speed limit and the number of invalid traffic signs per km exhibited a high accident rate. To our knowledge, it's the first attempt to analyze the interactions between accident consequences and traffic signs by employing a panel quantile regression model; by involving the visibility, the present study demonstrates that the low visibility causes a relatively higher risk of MD and DI; It is noteworthy that average speed limit corresponds with accident rate positively; The number of mandatory signs and the number of warning signs are more likely to reduce the accident rate; The number of invalid traffic signs per km are significant for accident rate, thus regular maintenance should be kept for a safer roadway environment.

Factors associated with conception among a sample of HIV-positive ...

African Journals Online (AJOL)

positive status, the variables were compared for women in two groups: those who conceived while knowing their HIV-positive status and those who discovered their HIV status during pregnancy. Bivariate and logistic regression analyses were ...

Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change.

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Feng, Yongjiu; Tong, Xiaohua

2017-09-22

Defining transition rules is an important issue in cellular automaton (CA)-based land use modeling because these models incorporate highly correlated driving factors. Multicollinearity among correlated driving factors may produce negative effects that must be eliminated from the modeling. Using exploratory regression under pre-defined criteria, we identified all possible combinations of factors from the candidate factors affecting land use change. Three combinations that incorporate five driving factors meeting pre-defined criteria were assessed. With the selected combinations of factors, three logistic regression-based CA models were built to simulate dynamic land use change in Shanghai, China, from 2000 to 2015. For comparative purposes, a CA model with all candidate factors was also applied to simulate the land use change. Simulations using three CA models with multicollinearity eliminated performed better (with accuracy improvements about 3.6%) than the model incorporating all candidate factors. Our results showed that not all candidate factors are necessary for accurate CA modeling and the simulations were not sensitive to changes in statistically non-significant driving factors. We conclude that exploratory regression is an effective method to search for the optimal combinations of driving factors, leading to better land use change models that are devoid of multicollinearity. We suggest identification of dominant factors and elimination of multicollinearity before building land change models, making it possible to simulate more realistic outcomes.

Differentiating regressed melanoma from regressed lichenoid keratosis.

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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.

Fuzzy Regression Prediction and Application Based on Multi-Dimensional Factors of Freight Volume

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Xiao, Mengting; Li, Cheng

2018-01-01

Based on the reality of the development of air cargo, the multi-dimensional fuzzy regression method is used to determine the influencing factors, and the three most important influencing factors of GDP, total fixed assets investment and regular flight route mileage are determined. The system’s viewpoints and analogy methods, the use of fuzzy numbers and multiple regression methods to predict the civil aviation cargo volume. In comparison with the 13th Five-Year Plan for China’s Civil Aviation Development (2016-2020), it is proved that this method can effectively improve the accuracy of forecasting and reduce the risk of forecasting. It is proved that this model predicts civil aviation freight volume of the feasibility, has a high practical significance and practical operation.

Risk Factors of Falls in Community-Dwelling Older Adults: Logistic Regression Tree Analysis

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Yamashita, Takashi; Noe, Douglas A.; Bailer, A. John

2012-01-01

Purpose of the Study: A novel logistic regression tree-based method was applied to identify fall risk factors and possible interaction effects of those risk factors. Design and Methods: A nationally representative sample of American older adults aged 65 years and older (N = 9,592) in the Health and Retirement Study 2004 and 2006 modules was used.…

Regression-Based Norms for a Bi-factor Model for Scoring the Brief Test of Adult Cognition by Telephone (BTACT).

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Gurnani, Ashita S; John, Samantha E; Gavett, Brandon E

2015-05-01

The current study developed regression-based normative adjustments for a bi-factor model of the The Brief Test of Adult Cognition by Telephone (BTACT). Archival data from the Midlife Development in the United States-II Cognitive Project were used to develop eight separate linear regression models that predicted bi-factor BTACT scores, accounting for age, education, gender, and occupation-alone and in various combinations. All regression models provided statistically significant fit to the data. A three-predictor regression model fit best and accounted for 32.8% of the variance in the global bi-factor BTACT score. The fit of the regression models was not improved by gender. Eight different regression models are presented to allow the user flexibility in applying demographic corrections to the bi-factor BTACT scores. Occupation corrections, while not widely used, may provide useful demographic adjustments for adult populations or for those individuals who have attained an occupational status not commensurate with expected educational attainment. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Factors affecting CO_2 emissions in China’s agriculture sector: Evidence from geographically weighted regression model

International Nuclear Information System (INIS)

Xu, Bin; Lin, Boqiang

2017-01-01

China is currently the world's largest emitter of carbon dioxide. Considered as a large agricultural country, carbon emission in China’s agriculture sector keeps on growing rapidly. It is, therefore, of great importance to investigate the driving forces of carbon dioxide emissions in this sector. The traditional regression estimation can only get “average” and “global” parameter estimates; it excludes the “local” parameter estimates which vary across space in some spatial systems. Geographically weighted regression embeds the latitude and longitude of the sample data into the regression parameters, and uses the local weighted least squares method to estimate the parameters point–by–point. To reveal the nonstationary spatial effects of driving forces, geographically weighted regression model is employed in this paper. The results show that economic growth is positively correlated with emissions, with the impact in the western region being less than that in the central and eastern regions. Urbanization is positively related to emissions but produces opposite effects pattern. Energy intensity is also correlated with emissions, with a decreasing trend from the eastern region to the central and western regions. Therefore, policymakers should take full account of the spatial nonstationarity of driving forces in designing emission reduction policies. - Highlights: • We explore the driving forces of CO_2 emissions in the agriculture sector. • Urbanization is positively related to emissions but produces opposite effect pattern. • The effect of energy intensity declines from the eastern region to western region.

Factors associated with false-positive self-reported adherence to antihypertensive drugs.

Science.gov (United States)

Tedla, Y G; Bautista, L E

2017-05-01

Self-reported medication adherence is known to overestimate true adherence. However, little is known about patient factors that may contribute to the upward bias in self-reported medication adherence. The objective of this study is to examine whether demographic, behavioral, medication and mood factors are associated with being a false-positive self-reported adherer (FPA) to antihypertensive drug treatment. We studied 175 patients (mean age: 50 years; 57% men) from primary-care clinics starting antihypertensive drug treatment. Self-reported adherence (SRA) was measured with the Medication Adherence Report Scale (MARS) and by the number of drug doses missed in the previous week/month, and compared with pill count adherence ratio (PCAR) as gold standard. Data on adherence, demographic, behavioral, medication and mood factors were collected at baseline and every 3 months up to 1 year. FPA was defined as being a non-adherer by PCAR and an adherer by self-report. Mixed effect logistic regression was used for the analysis. Twenty percent of participants were FPA. Anxiety increased (odds ratio (OR): 3.00; P=0.01), whereas smoking (OR: 0.40; P=0.03) and drug side effects (OR: 0.46, P=0.03) decreased the probability for FPA by MARS. Education below high-school completion increased the probability of being an FPA as measured by missing doses in the last month (OR: 1.66; P=0.04) and last week (OR: 1.88; P=0.02). The validity of SRA varies significantly according to drug side effects, behavioral factors and patient's mood. Careful consideration should be given to the use of self-reported measures of adherence among patients likely to be false-positive adherers.

Quality of life and related factors among HIV-positive spouses from serodiscordant couples under antiretroviral therapy in Henan Province, China.

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Duo Shan

Full Text Available OBJECTIVE: To describe the quality of life and related factors in HIV-positive spouses undergoing ART from discordant couples. METHODS: A cross-sectional study was conducted among 1,009 HIV-positive spouses from serodiscordant couples in Zhumadian, Henan Province, between October 1, 2008 and March 31, 2009. HIV-positive spouses were interviewed by local health professionals. Quality of life was evaluated by WHOQOL (Chinese Version. A multiple linear regression model was used to analyze the related factors. RESULTS: The majority of subjects were female (56.39%, had received a high school education (44%, were of Han ethnicity (98.41%, and were farmers (90.09%; the median time period of receiving ART was 3.92 years. The physical, psychological, social, and environmental QOL scores of the subjects were 12.91±1.95, 12.35±1.80, 13.96±2.43, and 12.45±1.91 respectively. The multiple linear regression model identified the physical domain related factors to be CD4 count, educational level, and occupation; psychological domain related factors include age, educational level, and reported STD symptom; social domain related factors included education level; and environmental domain related factors included education level, reported STD symptoms, and occupation. CONCLUSION: Being younger, a farmer, having a lower level of education, a reported STD symptom, or lower CD4 count, could decrease one's quality of life, suggesting that the use of blanket ART programs alone may not necessarily improve quality of life. Subjects received lower scores in the psychological domain, suggesting that psychological intervention may also need to be strengthened.

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

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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.

Prenatal diagnosis of Caudal Regression Syndrome : a case report

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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.

Effective factors contraceptive use by logistic regression model in Tehran, 1996

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Ramezani F

1999-07-01

Full Text Available Despite unwillingness to fertility, about 30% of couples do not use any kind of contraception and this will lead to unwanted pregnancy. In this clinical trial study, 4177 subjects who had at least one alive child, and delivered in one of the 12 university hospitals in Tehran were recruited. This study was conducted in 1996. The questionnaire included some questions about contraceptive use, their attitudes about unwantedness or wantedness of their current pregnancies. Data were analysed using a Logistic Regrassion Model. Results showed that 20.3% of those who had no fertility intention, did not use any kind of contraception methods, 41.1% of the subjects who were using a contraception method before pregnancy, had got pregnant unwantedly. Based on Logistic Regression Model; age, education, previous familiarity of women with contraception methods and husband's education were the most significant factors in contraceptive use. Subjects who were 20 years old and less or 35 years old and more and illeterate subjects were at higher risk for unuse of contraception methods. This risk was not related to the gender of their children that suggests a positive change in their perspectives towards sex and the number of children. It is suggested that health politicians choose an appropriate model to enhance the literacy, education and counseling for the correct usage of contraceptives and prevention of unwanted pregnancy.

Risk factors for subclinical intramammary infection in dairy goats in two longitudinal field studies evaluated by Bayesian logistic regression

DEFF Research Database (Denmark)

Koop, Gerrit; Collar, Carol A.; Toft, Nils

2013-01-01

Identification of risk factors for subclinical intramammary infections (IMI) in dairy goats should contribute to improved udder health. Intramammary infection may be diagnosed by bacteriological culture or by somatic cell count (SCC) of a milk sample. Both bacteriological culture and SCC are impe......Identification of risk factors for subclinical intramammary infections (IMI) in dairy goats should contribute to improved udder health. Intramammary infection may be diagnosed by bacteriological culture or by somatic cell count (SCC) of a milk sample. Both bacteriological culture and SCC...... are imperfect tests, particularly lacking sensitivity, which leads to misclassification and thus to biased estimates of odds ratios in risk factor studies. The objective of this study was to evaluate risk factors for the true (latent) IMI status of major pathogens in dairy goats. We used Bayesian logistic...... regression models that accounted for imperfect measurement of IMI by both culture and SCC. Udder half milk samples were collected from 530 Dutch and 438 California dairy goats in 10 herds on 3 occasions during lactation. Udder halves were classified as positive or negative for isolation of a major pathogen...

Factors Influencing Pregnancy Desires among HIV Positive Women ...

African Journals Online (AJOL)

Factors Influencing Pregnancy Desires among HIV Positive Women in Sibande District in Mpumalanga, South Africa. ... Gender and Behaviour ... The objective of the study is to present findings on factors influencing pregnancy desires amongst HIV positive women that have participated in Prevention of Mother to child ...

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.)

Support vector regression model for the estimation of γ-ray buildup factors for multi-layer shields

International Nuclear Information System (INIS)

Trontl, Kresimir; Smuc, Tomislav; Pevec, Dubravko

2007-01-01

The accuracy of the point-kernel method, which is a widely used practical tool for γ-ray shielding calculations, strongly depends on the quality and accuracy of buildup factors used in the calculations. Although, buildup factors for single-layer shields comprised of a single material are well known, calculation of buildup factors for stratified shields, each layer comprised of different material or a combination of materials, represent a complex physical problem. Recently, a new compact mathematical model for multi-layer shield buildup factor representation has been suggested for embedding into point-kernel codes thus replacing traditionally generated complex mathematical expressions. The new regression model is based on support vector machines learning technique, which is an extension of Statistical Learning Theory. The paper gives complete description of the novel methodology with results pertaining to realistic engineering multi-layer shielding geometries. The results based on support vector regression machine learning confirm that this approach provides a framework for general, accurate and computationally acceptable multi-layer buildup factor model

Reducing false-positive incidental findings with ensemble genotyping and logistic regression based variant filtering methods.

Science.gov (United States)

Hwang, Kyu-Baek; Lee, In-Hee; Park, Jin-Ho; Hambuch, Tina; Choe, Yongjoon; Kim, MinHyeok; Lee, Kyungjoon; Song, Taemin; Neu, Matthew B; Gupta, Neha; Kohane, Isaac S; Green, Robert C; Kong, Sek Won

2014-08-01

As whole genome sequencing (WGS) uncovers variants associated with rare and common diseases, an immediate challenge is to minimize false-positive findings due to sequencing and variant calling errors. False positives can be reduced by combining results from orthogonal sequencing methods, but costly. Here, we present variant filtering approaches using logistic regression (LR) and ensemble genotyping to minimize false positives without sacrificing sensitivity. We evaluated the methods using paired WGS datasets of an extended family prepared using two sequencing platforms and a validated set of variants in NA12878. Using LR or ensemble genotyping based filtering, false-negative rates were significantly reduced by 1.1- to 17.8-fold at the same levels of false discovery rates (5.4% for heterozygous and 4.5% for homozygous single nucleotide variants (SNVs); 30.0% for heterozygous and 18.7% for homozygous insertions; 25.2% for heterozygous and 16.6% for homozygous deletions) compared to the filtering based on genotype quality scores. Moreover, ensemble genotyping excluded > 98% (105,080 of 107,167) of false positives while retaining > 95% (897 of 937) of true positives in de novo mutation (DNM) discovery in NA12878, and performed better than a consensus method using two sequencing platforms. Our proposed methods were effective in prioritizing phenotype-associated variants, and an ensemble genotyping would be essential to minimize false-positive DNM candidates. © 2014 WILEY PERIODICALS, INC.

Negative and positive urgency may both be risk factors for compulsive buying.

Science.gov (United States)

Rose, Paul; Segrist, Daniel J

2014-06-01

Descriptions of compulsive buying often emphasize the roles of negative moods and trait impulsivity in the development of problematic buying habits. Trait impulsivity is sometimes treated as a unidimensional trait in compulsive buying research, but recent factor analyses suggest that impulsivity consists of multiple components that are probably best treated as independent predictors of problem behavior. In order to draw greater attention to the role of positive moods in compulsive buying, in this study we tested whether negative urgency (the tendency to act rashly while in negative moods) and positive urgency (the tendency to act rashly while in positive moods) account for similar amounts of variance in compulsive buying. North American adults (N = 514) completed an online survey containing the Richmond Compulsive Buying Scale (Ridgway, Kukar-Kinney & Monroe, 2008), established measures of positive and negative urgency (Cyders et al., 2007), ad hoc measures of buying-specific positive and negative urgency, measures of extraversion and neuroticism obtained from the International Personality Item Pool (http://ipip.ori.org/), and demographic questions. In several multiple regression analyses, when demographic variables, neuroticism, and extraversion were controlled, positive urgency and negative urgency both emerged as significant predictors of compulsive buying. Whether the two urgency variables were domain-general or buying-specific, they accounted for similar amounts of variance in compulsive buying. Preventing and reducing compulsive buying may require attention not only to the purchasing decisions people make while in negative states, but also to the purchasing decisions they make while in positive states.

Modelling long-term fire occurrence factors in Spain by accounting for local variations with geographically weighted regression

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Martínez-Fernández, J.; Chuvieco, E.; Koutsias, N.

2013-02-01

Humans are responsible for most forest fires in Europe, but anthropogenic factors behind these events are still poorly understood. We tried to identify the driving factors of human-caused fire occurrence in Spain by applying two different statistical approaches. Firstly, assuming stationary processes for the whole country, we created models based on multiple linear regression and binary logistic regression to find factors associated with fire density and fire presence, respectively. Secondly, we used geographically weighted regression (GWR) to better understand and explore the local and regional variations of those factors behind human-caused fire occurrence. The number of human-caused fires occurring within a 25-yr period (1983-2007) was computed for each of the 7638 Spanish mainland municipalities, creating a binary variable (fire/no fire) to develop logistic models, and a continuous variable (fire density) to build standard linear regression models. A total of 383 657 fires were registered in the study dataset. The binary logistic model, which estimates the probability of having/not having a fire, successfully classified 76.4% of the total observations, while the ordinary least squares (OLS) regression model explained 53% of the variation of the fire density patterns (adjusted R2 = 0.53). Both approaches confirmed, in addition to forest and climatic variables, the importance of variables related with agrarian activities, land abandonment, rural population exodus and developmental processes as underlying factors of fire occurrence. For the GWR approach, the explanatory power of the GW linear model for fire density using an adaptive bandwidth increased from 53% to 67%, while for the GW logistic model the correctly classified observations improved only slightly, from 76.4% to 78.4%, but significantly according to the corrected Akaike Information Criterion (AICc), from 3451.19 to 3321.19. The results from GWR indicated a significant spatial variation in the local

Logistic regression models of factors influencing the location of bioenergy and biofuels plants

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T.M. Young; R.L. Zaretzki; J.H. Perdue; F.M. Guess; X. Liu

2011-01-01

Logistic regression models were developed to identify significant factors that influence the location of existing wood-using bioenergy/biofuels plants and traditional wood-using facilities. Logistic models provided quantitative insight for variables influencing the location of woody biomass-using facilities. Availability of "thinnings to a basal area of 31.7m2/ha...

Risk factors for pedicled flap necrosis in hand soft tissue reconstruction: a multivariate logistic regression analysis.

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Gong, Xu; Cui, Jianli; Jiang, Ziping; Lu, Laijin; Li, Xiucun

2018-03-01

Few clinical retrospective studies have reported the risk factors of pedicled flap necrosis in hand soft tissue reconstruction. The aim of this study was to identify non-technical risk factors associated with pedicled flap perioperative necrosis in hand soft tissue reconstruction via a multivariate logistic regression analysis. For patients with hand soft tissue reconstruction, we carefully reviewed hospital records and identified 163 patients who met the inclusion criteria. The characteristics of these patients, flap transfer procedures and postoperative complications were recorded. Eleven predictors were identified. The correlations between pedicled flap necrosis and risk factors were analysed using a logistic regression model. Of 163 skin flaps, 125 flaps survived completely without any complications. The pedicled flap necrosis rate in hands was 11.04%, which included partial flap necrosis (7.36%) and total flap necrosis (3.68%). Soft tissue defects in fingers were noted in 68.10% of all cases. The logistic regression analysis indicated that the soft tissue defect site (P = 0.046, odds ratio (OR) = 0.079, confidence interval (CI) (0.006, 0.959)), flap size (P = 0.020, OR = 1.024, CI (1.004, 1.045)) and postoperative wound infection (P < 0.001, OR = 17.407, CI (3.821, 79.303)) were statistically significant risk factors for pedicled flap necrosis of the hand. Soft tissue defect site, flap size and postoperative wound infection were risk factors associated with pedicled flap necrosis in hand soft tissue defect reconstruction. © 2017 Royal Australasian College of Surgeons.

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

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Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

2017-01-01

The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

Positive Orientation and the Five-Factor Model

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Miciuk Łukasz Roland

2016-04-01

Full Text Available The aim of the present study was to investigate the relationship between positive orientation (PO defined as a basic predisposition to perceive and evaluate positive aspects of life, the future and oneself and the Five-Factor Model of personality (FFM. Hypotheses postulated positive correlations between PO and extraversion, conscientiousness, agreeableness and openness; a negative correlation was predicted between PO and neuroticism. Two hundred Polish students completed the following measures: SES (Self-Esteem Scale, Rosenberg, SWLS (The Satisfaction with Life Scale; Diener, Emmons, Larson & Griffin, LOT-R (The Life Orientation Test - Revised; Scheier, Carver & Bridges and NEOFFI (NEO Five Factor Inventory, Costa & McCrae. The results confirmed correlations between PO and extraversion, conscientiousness, and neuroticism; correlations with openness and agreeableness were not supported. According to canonical correlations, PO shows a clear affinity to the FFM.

Logistic regression analysis of risk factors for postoperative recurrence of spinal tumors and analysis of prognostic factors.

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Zhang, Shanyong; Yang, Lili; Peng, Chuangang; Wu, Minfei

2018-02-01

The aim of the present study was to investigate the risk factors for postoperative recurrence of spinal tumors by logistic regression analysis and analysis of prognostic factors. In total, 77 male and 48 female patients with spinal tumor were selected in our hospital from January, 2010 to December, 2015 and divided into the benign (n=76) and malignant groups (n=49). All the patients underwent microsurgical resection of spinal tumors and were reviewed regularly 3 months after operation. The McCormick grading system was used to evaluate the postoperative spinal cord function. Data were subjected to statistical analysis. Of the 125 cases, 63 cases showed improvement after operation, 50 cases were stable, and deterioration was found in 12 cases. The improvement rate of patients with cervical spine tumor, which reached 56.3%, was the highest. Fifty-two cases of sensory disturbance, 34 cases of pain, 30 cases of inability to exercise, 26 cases of ataxia, and 12 cases of sphincter disorders were found after operation. Seventy-two cases (57.6%) underwent total resection, 18 cases (14.4%) received subtotal resection, 23 cases (18.4%) received partial resection, and 12 cases (9.6%) were only treated with biopsy/decompression. Postoperative recurrence was found in 57 cases (45.6%). The mean recurrence time of patients in the malignant group was 27.49±6.09 months, and the mean recurrence time of patients in the benign group was 40.62±4.34. The results were significantly different (Pregression analysis of total resection-related factors showed that total resection should be the preferred treatment for patients with benign tumors, thoracic and lumbosacral tumors, and lower McCormick grade, as well as patients without syringomyelia and intramedullary tumors. Logistic regression analysis of recurrence-related factors revealed that the recurrence rate was relatively higher in patients with malignant, cervical, thoracic and lumbosacral, intramedullary tumors, and higher Mc

Logistic regression applied to natural hazards: rare event logistic regression with replications

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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.

Application of geographically-weighted regression analysis to assess risk factors for malaria hotspots in Keur Soce health and demographic surveillance site.

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Ndiath, Mansour M; Cisse, Badara; Ndiaye, Jean Louis; Gomis, Jules F; Bathiery, Ousmane; Dia, Anta Tal; Gaye, Oumar; Faye, Babacar

2015-11-18

In Senegal, considerable efforts have been made to reduce malaria morbidity and mortality during the last decade. This resulted in a marked decrease of malaria cases. With the decline of malaria cases, transmission has become sparse in most Senegalese health districts. This study investigated malaria hotspots in Keur Soce sites by using geographically-weighted regression. Because of the occurrence of hotspots, spatial modelling of malaria cases could have a considerable effect in disease surveillance. This study explored and analysed the spatial relationships between malaria occurrence and socio-economic and environmental factors in small communities in Keur Soce, Senegal, using 6 months passive surveillance. Geographically-weighted regression was used to explore the spatial variability of relationships between malaria incidence or persistence and the selected socio-economic, and human predictors. A model comparison of between ordinary least square and geographically-weighted regression was also explored. Vector dataset (spatial) of the study area by village levels and statistical data (non-spatial) on malaria confirmed cases, socio-economic status (bed net use), population data (size of the household) and environmental factors (temperature, rain fall) were used in this exploratory analysis. ArcMap 10.2 and Stata 11 were used to perform malaria hotspots analysis. From Jun to December, a total of 408 confirmed malaria cases were notified. The explanatory variables-household size, housing materials, sleeping rooms, sheep and distance to breeding site returned significant t values of -0.25, 2.3, 4.39, 1.25 and 2.36, respectively. The OLS global model revealed that it explained about 70 % (adjusted R(2) = 0.70) of the variation in malaria occurrence with AIC = 756.23. The geographically-weighted regression of malaria hotspots resulted in coefficient intercept ranging from 1.89 to 6.22 with a median of 3.5. Large positive values are distributed mainly in the southeast

Risk factors associated with default among new smear positive TB patients treated under DOTS in India.

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Vijay, Sophia; Kumar, Prahlad; Chauhan, Lakbir Singh; Vollepore, Balasangameshwara Hanumanthappa; Kizhakkethil, Unnikrishnan Pallikkara; Rao, Sumathi Govinda

2010-04-06

Poor treatment adherence leading to risk of drug resistance, treatment failure, relapse, death and persistent infectiousness remains an impediment to the tuberculosis control programmes. The objective of the study was to identify predictors of default among new smear positive TB patients registered for treatment to suggest possible interventions to set right the problems to sustain and enhance the programme performance. Twenty districts selected from six states were assigned to six strata formed, considering the geographic, socio-cultural and demographic setup of the area. New smear positive patients registered for treatment in two consecutive quarters during III quarter 2004 to III quarter 2005 formed the retrospective study cohort. Case control analysis was done including defaulted patients as "cases" and equal number of age and sex matched patients completing treatment as "controls". The presence and degree of association between default and determinant factors was computed through univariate and multivariate logistic regression analysis. Data collection was through patient interviews using pre-tested semi structured questionnaire and review of treatment related records. Information on a wide range of socio demographic and patient related factors was obtained. Among the 687 defaulted and equal numbers of patients in completed group, 389 and 540 patients respectively were satisfactorily interviewed. In the logistic regression analysis, factors independently associated with default were alcoholism [AOR-1.72 (1.23-2.44)], illiteracy [AOR-1.40 (1.03-1.92)], having other commitments during treatment [AOR-3.22 (1.1-9.09)], inadequate knowledge of TB [AOR-1.88(1.35-2.63)], poor patient provider interaction [AOR-1.72(1.23-2.44)], lack of support from health staff [AOR-1.93(1.41-2.64)], having instances of missed doses [AOR-2.56(1.82-3.57)], side effects to anti TB drugs [AOR-2.55 (1.87-3.47)] and dissatisfaction with services provided [AOR-1.73 (1.14-2.6)]. Majority of

Risk factors associated with default among new smear positive TB patients treated under DOTS in India.

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Sophia Vijay

2010-04-01

Full Text Available Poor treatment adherence leading to risk of drug resistance, treatment failure, relapse, death and persistent infectiousness remains an impediment to the tuberculosis control programmes. The objective of the study was to identify predictors of default among new smear positive TB patients registered for treatment to suggest possible interventions to set right the problems to sustain and enhance the programme performance.Twenty districts selected from six states were assigned to six strata formed, considering the geographic, socio-cultural and demographic setup of the area. New smear positive patients registered for treatment in two consecutive quarters during III quarter 2004 to III quarter 2005 formed the retrospective study cohort. Case control analysis was done including defaulted patients as "cases" and equal number of age and sex matched patients completing treatment as "controls". The presence and degree of association between default and determinant factors was computed through univariate and multivariate logistic regression analysis. Data collection was through patient interviews using pre-tested semi structured questionnaire and review of treatment related records. Information on a wide range of socio demographic and patient related factors was obtained. Among the 687 defaulted and equal numbers of patients in completed group, 389 and 540 patients respectively were satisfactorily interviewed. In the logistic regression analysis, factors independently associated with default were alcoholism [AOR-1.72 (1.23-2.44], illiteracy [AOR-1.40 (1.03-1.92], having other commitments during treatment [AOR-3.22 (1.1-9.09], inadequate knowledge of TB [AOR-1.88(1.35-2.63], poor patient provider interaction [AOR-1.72(1.23-2.44], lack of support from health staff [AOR-1.93(1.41-2.64], having instances of missed doses [AOR-2.56(1.82-3.57], side effects to anti TB drugs [AOR-2.55 (1.87-3.47] and dissatisfaction with services provided [AOR-1.73 (1

Related factors to semi-recumbent position compliance and pressure ulcers in patients with invasive mechanical ventilation: An observational study (CAPCRI study).

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Llaurado-Serra, Mireia; Ulldemolins, Marta; Fernandez-Ballart, Joan; Guell-Baro, Rosa; Valentí-Trulls, Teresa; Calpe-Damians, Neus; Piñol-Tena, Angels; Pi-Guerrero, Mercedes; Paños-Espinosa, Cristina; Sandiumenge, Alberto; Jimenez-Herrera, María F

2016-09-01

Semi-recumbent position is recommended to prevent ventilator-associated pneumonia. Its implementation, however, is below optimal. We aimed to assess real semi-recumbent position compliance and the degree of head-of-bed elevation in Spanish intensive care units, along with factors determining compliance and head-of-bed elevation and their relationship with the development of pressure ulcers. Finally, we investigated the impact that might have the diagnosis of pressure ulcers in the attitude toward head-of-bed elevation. We performed a prospective, multicenter, observational study in 6 intensive care units. Inclusion criteria were patients ≥18 years old and expected to remain under mechanical ventilator for ≥48h. Exclusion criteria were patients with contraindications for semi-recumbent position from admission, mechanical ventilation during the previous 7 days and prehospital intubation. Head-of-bed elevation was measured 3 times/day for a maximum of 28 days using the BOSCH GLM80(®) device. The variables collected related to patient admission, risk of pressure ulcers and the measurements themselves. Bivariate and multivariate analyses were carried out using multiple binary logistic regression and linear regression as appropriate. Statistical significance was set at preplacement therapy, nursing shift, open abdomen, abdominal vacuum therapy and agitation. Twenty-five patients (9.1%) developed a total of 34 pressure ulcers. The diagnosis of pressure ulcers did not affect the head-of-bed elevation. In the multivariate analysis, head-of-bed elevation was not identified as an independent risk factor for pressure ulcers. Semi-recumbent position compliance is below optimal despite the fact that it seems achievable most of the time. Factors that affect semi-recumbent position include the particular intensive care unit, abdominal conditions, renal replacement therapy, agitation and bed type. Head-of-bed elevation was not related to the risk of pressure ulcers. Efforts

Psychological and Social Work Factors as Predictors of Mental Distress and Positive Affect: A Prospective, Multilevel Study.

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Live Bakke Finne

Full Text Available Occupational health research has mainly addressed determinants of negative health effects, typically employing individual-level self-report data. The present study investigated individual- and department-level (means of each work unit effects of psychological/social work factors on mental distress and positive affect. Employees were recruited from 63 Norwegian organizations, representing a wide variety of job types. A total of 4158 employees, in 918 departments, responded at baseline and at follow-up two years later. Multilevel linear regressions estimated individual- and department-level effects simultaneously, and accounted for clustering of data. Baseline exposures and average exposures over time ([T1+T2]/2 were tested. All work factors; decision control, role conflict, positive challenge, support from immediate superior, fair leadership, predictability during the next month, commitment to organization, rumors of change, human resource primacy, and social climate, were related to mental distress and positive affect at the individual and department level. However, analyses of baseline exposures adjusted for baseline outcome, demonstrated significant associations at the individual level only. Baseline "rumors of change" was related to mental distress only and baseline "predictability during the next month" was not a statistical significant predictor of either outcome when adjusted for outcome at baseline. Psychological and social work factors were generally related to mental distress and positive affect in a mirrored way. Impact of exposures seemed most pervasive at the individual level. However, department-level relations were also discovered. Supplementing individual-level measures with aggregated measures may increase understanding of working conditions influence on employees`health and well-being. Organizational improvements focusing on the work factors in the current study should be able to reduce distress and enhance positive affect

Psychological and Social Work Factors as Predictors of Mental Distress and Positive Affect: A Prospective, Multilevel Study.

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Finne, Live Bakke; Christensen, Jan Olav; Knardahl, Stein

2016-01-01

Occupational health research has mainly addressed determinants of negative health effects, typically employing individual-level self-report data. The present study investigated individual- and department-level (means of each work unit) effects of psychological/social work factors on mental distress and positive affect. Employees were recruited from 63 Norwegian organizations, representing a wide variety of job types. A total of 4158 employees, in 918 departments, responded at baseline and at follow-up two years later. Multilevel linear regressions estimated individual- and department-level effects simultaneously, and accounted for clustering of data. Baseline exposures and average exposures over time ([T1+T2]/2) were tested. All work factors; decision control, role conflict, positive challenge, support from immediate superior, fair leadership, predictability during the next month, commitment to organization, rumors of change, human resource primacy, and social climate, were related to mental distress and positive affect at the individual and department level. However, analyses of baseline exposures adjusted for baseline outcome, demonstrated significant associations at the individual level only. Baseline "rumors of change" was related to mental distress only and baseline "predictability during the next month" was not a statistical significant predictor of either outcome when adjusted for outcome at baseline. Psychological and social work factors were generally related to mental distress and positive affect in a mirrored way. Impact of exposures seemed most pervasive at the individual level. However, department-level relations were also discovered. Supplementing individual-level measures with aggregated measures may increase understanding of working conditions influence on employees`health and well-being. Organizational improvements focusing on the work factors in the current study should be able to reduce distress and enhance positive affect. Furthermore, both

An examination of retention factors among registered nurses in Northeastern Ontario, Canada: Nurses intent to stay in their current position.

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Nowrouzi, Behdin; Rukholm, Ellen; Lariviere, Michel; Carter, Lorraine; Koren, Irene; Mian, Oxana; Giddens, Emilia

2016-03-10

The purpose of the study was to examine factors related to the retention of registered nurses in northeastern Ontario, Canada. A cross-sectional survey of registered nurses working in northeastern Ontario, Canada was conducted. Logistic regression analyses were used to consider intent to stay in current employment in relation to the following: 1) demographic factors, and 2) occupation and career satisfaction factors. A total of 459 (29.8% response rate) questionnaires were completed. The adjusted odds logistic regression analysis of RNs who intended to remain in their current position for the next five years, demonstrated that respondents in the 46 to 56 age group (OR: 2.65; 95% CI: 1.50 to 4.69), the importance of staff development in the organization (OR: 3.04; 95% CI: 1.13 to 8.13) northeastern Ontario lifestyle (OR: 2.61; 95% CI: 1.55 to 4.40), working in nursing for 14 to 22.5 years (OR: 2.55; 95% CI: 1.10 to 5.93), and working between 0 to 1 hour of overtime per week (OR: 1.20; 95% CI: 1.20 to 4.64) were significant factors in staying in their current position for the next five years. This study shows that a further understanding of the work environment could assist with developing retention for rural nurses. Furthermore, employers may use such information to ameliorate the working conditions of nurses, while researchers may use such evidence to develop interventions that are applicable to improving the working conditions of nurses.

Logistic regression applied to natural hazards: rare event logistic regression with replications

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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.

Determinants of LSIL Regression in Women from a Colombian Cohort

International Nuclear Information System (INIS)

Molano, Monica; Gonzalez, Mauricio; Gamboa, Oscar; Ortiz, Natasha; Luna, Joaquin; Hernandez, Gustavo; Posso, Hector; Murillo, Raul; Munoz, Nubia

2010-01-01

Objective: To analyze the role of Human Papillomavirus (HPV) and other risk factors in the regression of cervical lesions in women from the Bogota Cohort. Methods: 200 HPV positive women with abnormal cytology were included for regression analysis. The time of lesion regression was modeled using methods for interval censored survival time data. Median duration of total follow-up was 9 years. Results: 80 (40%) women were diagnosed with Atypical Squamous Cells of Undetermined Significance (ASCUS) or Atypical Glandular Cells of Undetermined Significance (AGUS) while 120 (60%) were diagnosed with Low Grade Squamous Intra-epithelial Lesions (LSIL). Globally, 40% of the lesions were still present at first year of follow up, while 1.5% was still present at 5 year check-up. The multivariate model showed similar regression rates for lesions in women with ASCUS/AGUS and women with LSIL (HR= 0.82, 95% CI 0.59-1.12). Women infected with HR HPV types and those with mixed infections had lower regression rates for lesions than did women infected with LR types (HR=0.526, 95% CI 0.33-0.84, for HR types and HR=0.378, 95% CI 0.20-0.69, for mixed infections). Furthermore, women over 30 years had a higher lesion regression rate than did women under 30 years (HR1.53, 95% CI 1.03-2.27). The study showed that the median time for lesion regression was 9 months while the median time for HPV clearance was 12 months. Conclusions: In the studied population, the type of infection and the age of the women are critical factors for the regression of cervical lesions.

Risk factors for positive margins in conservative surgery for breast cancer after neoadjuvant chemotherapy.

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Bouzón, Alberto; Acea, Benigno; García, Alejandra; Iglesias, Ángela; Mosquera, Joaquín; Santiago, Paz; Seoane, Teresa

2016-01-01

Breast conservative surgery after neoadjuvant chemotherapy intends to remove any residual tumor with negative margins. The purpose of this study was to analyze the preoperative clinical-pathological factors influencing the margin status after conservative surgery in breast cancer patients receiving neoadjuvant chemotherapy. A retrospective study of 91 breast cancer patients undergoing neoadjuvant chemotherapy (92 breast lesions) during the period 2006 to 2013. A Cox regression analysis to identify baseline tumor characteristics associated with positive margins after breast conservative surgery was performed. Of all cases, 71 tumors were initially treated with conservative surgery after neoadjuvant chemotherapy. Pathologic exam revealed positive margins in 16 of the 71 cases (22.5%). The incidence of positive margins was significantly higher in cancers with initial size >5cm (P=.021), in cancers with low tumor grade (P=.031), and in patients with hormone receptor-positive cancer (P=.006). After a median follow-up of 45.2 months, 7 patients of the 71 treated with conservative surgery had disease recurrence (9.8%). There was no significant difference in terms of disease-free survival according to the margin status (P=.596). A baseline tumor size >5cm, low tumor grade and hormone receptor-positive status increase the risk for surgical margin involvement in breast conservative surgery after neoadjuvant chemotherapy. Copyright © 2016 AEC. Publicado por Elsevier España, S.L.U. All rights reserved.

This research is to study the factors which influence the business success of small business ‘processed rotan’. The data employed in the study are primary data within the period of July to August 2013, 30 research observations through census method. Method of analysis used in the study is multiple linear regressions. The results of analysis showed that the factors of labor, innovation and promotion have positive and significant influence on the business success of small business ‘processed rotan’ simultaneously. The analysis also showed that partially labor has positive and significant influence on the business success, yet innovation and promotion have insignificant and positive influence on the business success.

OpenAIRE

Nasution, Inggrita Gusti Sari; Muchtar, Yasmin Chairunnisa

2013-01-01

This research is to study the factors which influence the business success of small business ‘processed rotan’. The data employed in the study are primary data within the period of July to August 2013, 30 research observations through census method. Method of analysis used in the study is multiple linear regressions. The results of analysis showed that the factors of labor, innovation and promotion have positive and significant influence on the business success of small busine...

Risk Factors Associated With Circumferential Resection Margin Positivity in Rectal Cancer: A Binational Registry Study.

Science.gov (United States)

Warrier, Satish K; Kong, Joseph Cherng; Guerra, Glen R; Chittleborough, Timothy J; Naik, Arun; Ramsay, Robert G; Lynch, A Craig; Heriot, Alexander G

2018-04-01

Rectal cancer outcomes have improved with the adoption of a multidisciplinary model of care. However, there is a spectrum of quality when viewed from a national perspective, as highlighted by the Consortium for Optimizing the Treatment of Rectal Cancer data on rectal cancer care in the United States. The aim of this study was to assess and identify predictors of circumferential resection margin involvement for rectal cancer across Australasia. A retrospective study from a prospectively maintained binational colorectal cancer database was interrogated. This study is based on a binational colorectal cancer audit database. Clinical information on all consecutive resected rectal cancer cases recorded in the registry from 2007 to 2016 was retrieved, collated, and analyzed. The primary outcome measure was positive circumferential resection margin, measured as a resection margin ≤1 mm. A total of 3367 patients were included, with 261 (7.5%) having a positive circumferential resection margin. After adjusting for hospital and surgeon volume, hierarchical logistic regression analysis identified a 6-variable model encompassing the independent predictors, including urgent operation, abdominoperineal resection, open technique, low rectal cancer, T3 to T4, and N1 to N2. The accuracy of the model was 92.3%, with an receiver operating characteristic of 0.783 (p risk associated with circumferential resection margin positivity ranged from risk factors) to 43% (6 risk factors). This study was limited by the lack of recorded long-term outcomes associated with circumferential resection margin positivity. The rate of circumferential resection margin involvement in patients undergoing rectal cancer resection in Australasia is low and is influenced by a number of factors. Risk stratification of outcome is important with the increasing demand for publicly accessible quality data. See Video Abstract at http://links.lww.com/DCR/A512.

Regression and kriging analysis for grid power factor estimation

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Rajesh Guntaka

2014-12-01

Full Text Available The measurement of power factor (PF in electrical utility grids is a mainstay of load balancing and is also a critical element of transmission and distribution efficiency. The measurement of PF dates back to the earliest periods of electrical power distribution to public grids. In the wide-area distribution grid, measurement of current waveforms is trivial and may be accomplished at any point in the grid using a current tap transformer. However, voltage measurement requires reference to ground and so is more problematic and measurements are normally constrained to points that have ready and easy access to a ground source. We present two mathematical analysis methods based on kriging and linear least square estimation (LLSE (regression to derive PF at nodes with unknown voltages that are within a perimeter of sample nodes with ground reference across a selected power grid. Our results indicate an error average of 1.884% that is within acceptable tolerances for PF measurements that are used in load balancing tasks.

Driven Factors Analysis of China’s Irrigation Water Use Efficiency by Stepwise Regression and Principal Component Analysis

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Renfu Jia

2016-01-01

Full Text Available This paper introduces an integrated approach to find out the major factors influencing efficiency of irrigation water use in China. It combines multiple stepwise regression (MSR and principal component analysis (PCA to obtain more realistic results. In real world case studies, classical linear regression model often involves too many explanatory variables and the linear correlation issue among variables cannot be eliminated. Linearly correlated variables will cause the invalidity of the factor analysis results. To overcome this issue and reduce the number of the variables, PCA technique has been used combining with MSR. As such, the irrigation water use status in China was analyzed to find out the five major factors that have significant impacts on irrigation water use efficiency. To illustrate the performance of the proposed approach, the calculation based on real data was conducted and the results were shown in this paper.

Risk factors of regression and undercorrection in photorefractive keratectomy:a case-control study

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Seyed-Farzad Mohammadi

2015-10-01

Full Text Available AIM:To determine risk factors of regression and undercorrection following photorefractive keratectomy (PRK in myopia or myopic astigmatism.METHODS: A case-control study was designed in which eyes with an indication for re-treatment (RT were defined as cases; primary criteria for RT indication, as assessed at least 9mo postoperatively, included an uncorrected distance visual acuity (UDVA of 20/30 or worse and a stable refraction for more than 3mo. Additional considerations included optical quality symptoms and significant higher order aberrations (HOAs. Controls were chosen from the same cohort of operated eyes which had complete post-operative follow up data beyond 9mo and did not need RT. The cohort included patients who had undergone PRK by the Tissue-Saving (TS ablation profile of Technolas 217z100 excimer laser (Bausch & Lomb, Rochester, NY, USA. Mitomycin C had been used in all of the primary procedures.RESULTS:We had 70 case eyes and 158 control eyes, and they were comparable in terms of age, sex and follow-up time (P values:0.58, 1.00 and 0.89, respectively. Pre-operative spherical equivalent of more than -5.00 diopter (D, intended optical zone (OZ diameter of less than 6.00 mm and ocular fixation instability during laser ablation were associated with RT indications (all P values <0.001. These factors maintained their significance in the multiple logistic regression model with odd ratios of 6.12, 6.71 and 7.89, respectively.CONCLUSION:Higher refractive correction (>-5.00 D, smaller OZ (<6.00 mm and unstable fixation during laser ablation of PRK for myopia and myopic astigmatism were found to be strong predictors of undercorrection and regression.

Geographically Weighted Logistic Regression Applied to Credit Scoring Models

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Pedro Henrique Melo Albuquerque

Full Text Available Abstract This study used real data from a Brazilian financial institution on transactions involving Consumer Direct Credit (CDC, granted to clients residing in the Distrito Federal (DF, to construct credit scoring models via Logistic Regression and Geographically Weighted Logistic Regression (GWLR techniques. The aims were: to verify whether the factors that influence credit risk differ according to the borrower’s geographic location; to compare the set of models estimated via GWLR with the global model estimated via Logistic Regression, in terms of predictive power and financial losses for the institution; and to verify the viability of using the GWLR technique to develop credit scoring models. The metrics used to compare the models developed via the two techniques were the AICc informational criterion, the accuracy of the models, the percentage of false positives, the sum of the value of false positive debt, and the expected monetary value of portfolio default compared with the monetary value of defaults observed. The models estimated for each region in the DF were distinct in their variables and coefficients (parameters, with it being concluded that credit risk was influenced differently in each region in the study. The Logistic Regression and GWLR methodologies presented very close results, in terms of predictive power and financial losses for the institution, and the study demonstrated viability in using the GWLR technique to develop credit scoring models for the target population in the study.

Análise de fatores e regressão bissegmentada em estudos de estratificação ambiental e adaptabilidade em milho Factor analysis and bissegmented regression for studies about environmental stratification and maize adaptability

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Deoclécio Domingos Garbuglio

2007-02-01

Full Text Available O objetivo deste trabalho foi verificar possíveis divergências entre os resultados obtidos nas avaliações da adaptabilidade de 27 genótipos de milho (Zea mays L., e na estratificação de 22 ambientes no Estado do Paraná, por meio de técnicas baseadas na análise de fatores e regressão bissegmentada. As estratificações ambientais foram feitas por meio do método tradicional e por análise de fatores, aliada ao porcentual da porção simples da interação GxA (PS%. As análises de adaptabilidade foram realizadas por meio de regressão bissegmentada e análise de fatores. Pela análise de regressão bissegmentada, os genótipos estudados apresentaram alta performance produtiva; no entanto, não foi constatado o genótipo considerado como ideal. A adaptabilidade dos genótipos, analisada por meio de plotagens gráficas, apresentou respostas diferenciadas quando comparada à regressão bissegmentada. A análise de fatores mostrou-se eficiente nos processos de estratificação ambiental e adaptabilidade dos genótipos de milho.The objective of this work was to verify possible divergences among results obtained on adaptability evaluations of 27 maize genotypes (Zea mays L., and on stratification of 22 environments on Paraná State, Brazil, through techniques of factor analysis and bissegmented regression. The environmental stratifications were made through the traditional methodology and by factor analysis, allied to the percentage of the simple portion of GxE interaction (PS%. Adaptability analyses were carried out through bissegmented regression and factor analysis. By the analysis of bissegmented regression, studied genotypes had presented high productive performance; however, it was not evidenced the genotype considered as ideal. The adaptability of the genotypes, analyzed through graphs, presented different answers when compared to bissegmented regression. Factor analysis was efficient in the processes of environment stratification and

Positive factors associated with quality of life among Chinese patients with renal carcinoma: a cross-sectional study.

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Liu, Jiao; Gong, Da-Xin; Zeng, Yu; Li, Zhen-Hua; Kong, Chui-Ze

2018-01-01

Quality of life and positive psychological variables has become a focus of concern in patients with renal carcinoma. However, the integrative effects of positive psychological variables on the illness have seldom been reported. The aims of this study were to evaluate the quality of life and the integrative effects of hope, resilience and optimism on the quality of life among Chinese renal carcinoma patients. A cross-sectional study was conducted at the First Hospital of China Medical University. 284 participants completed questionnaires consisting of demographic and clinical characteristics, EORTC QLQ-C30, Adult Hope Scale, Resilience Scale-14 and Life Orientation Scale-Revised from July 2013 to July 2014. Pearson's correlation and hierarchical regression analyses were performed to explore the effects of related factors. Hope, resilience and optimism were significantly associated with quality of life. Hierarchical regression analyses indicated that hope, resilience and optimism as a whole accounted for 9.8, 24.4 and 21.9% of the variance in the global health status, functioning status and symptom status, respectively. The low level of quality of life for Chinese renal carcinoma patients should receive more attention from Chinese medical institutions. Psychological interventions to increase hope, resilience and optimism may be essential to enhancing the quality of life of Chinese cancer patients.

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

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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.

Least Squares Adjustment: Linear and Nonlinear Weighted Regression Analysis

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2007-01-01

This note primarily describes the mathematics of least squares regression analysis as it is often used in geodesy including land surveying and satellite positioning applications. In these fields regression is often termed adjustment. The note also contains a couple of typical land surveying...... and satellite positioning application examples. In these application areas we are typically interested in the parameters in the model typically 2- or 3-D positions and not in predictive modelling which is often the main concern in other regression analysis applications. Adjustment is often used to obtain...... the clock error) and to obtain estimates of the uncertainty with which the position is determined. Regression analysis is used in many other fields of application both in the natural, the technical and the social sciences. Examples may be curve fitting, calibration, establishing relationships between...

Risk factors associated with low CD4+ lymphocyte count among HIV-positive pregnant women in Nigeria.

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Abimiku, Alash'le; Villalba-Diebold, Pacha; Dadik, Jelpe; Okolo, Felicia; Mang, Edwina; Charurat, Man

2009-09-01

To determine the risk factors for CD4+ lymphocyte counts of 200 cells/mm(3) or lower in HIV-positive pregnant women in Nigeria. A cross-sectional data analysis from a prospective cohort of 515 HIV-positive women attending a prenatal clinic. Risk of a low CD4+ count was estimated using logistic regression analysis. CD4+ lymphocyte counts of 200 cells/mm(3) or lower (280+/-182 cells/mm(3)) were recorded in 187 (36.3%) out of 515 HIV-positive pregnant women included in the study. Low CD4+ count was associated with older age (adjusted odds ratio [aOR] 10.71; 95% confidence interval [CI], 1.20-95.53), lack of condom use (aOR, 5.16; 95% CI, 1.12-23.8), history of genital ulcers (aOR, 1.78; 95% CI, 1.12-2.82), and history of vaginal discharge (aOR; 1.62; 1.06-2.48). Over 35% of the HIV-positive pregnant women had low CD4+ counts, indicating the need for treatment. The findings underscore the need to integrate prevention of mother-to-child transmission with HIV treatment and care, particularly services for sexually transmitted infections.

The Research of Regression Method for Forecasting Monthly Electricity Sales Considering Coupled Multi-factor

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Wang, Jiangbo; Liu, Junhui; Li, Tiantian; Yin, Shuo; He, Xinhui

2018-01-01

The monthly electricity sales forecasting is a basic work to ensure the safety of the power system. This paper presented a monthly electricity sales forecasting method which comprehensively considers the coupled multi-factors of temperature, economic growth, electric power replacement and business expansion. The mathematical model is constructed by using regression method. The simulation results show that the proposed method is accurate and effective.

An empirical study on open position risk assessment using VAR and regression analysis: A case study of Iranian banking industry

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Elmira Mahmoudzadeh

2012-10-01

Full Text Available During the past few years, there have been tremendous fluctuations on different currencies. For instance, European common currency, Euro, has be fluctuated between 0.60 to 0.9 against US dollar. Therefore, it is important to study the behavior of currency valuations using different techniques. In this paper, we present an empirical study to measure the impact of different items on risk of foreign currency using value at risk (VaR and regression methods. The proposed model of this paper investigates whether the risk of open positions of six foreign currencies including US dollar, Euro, British Pound, Switzerland Frank, Norwegian Kroner and United Emirate Dirham increase during the time horizon. The proposed study of this paper uses historical daily prices of these currencies for a fiscal year of 2011 in one of private banks located in Iran and measures the relative risk. The results of the implementation of two methods of VaR and linear regression indicate that the risk of open positions increases during the time horizon.

Effective factors on adoption ofinnovation in organizational IT ...

African Journals Online (AJOL)

... organizational factors and human factors have a positive and significant effect on adoption of new technologies. The results of analysis of regression and simple linear regression revealed that organizational and innovation variables have highest coefficients with most effectiveness in adoption of new technologies in IT.

Factors associated with the use of irreversible contraception and continuous use of reversible contraception in a cohort of HIV-positive women.

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Kancheva Landolt, Nadia; Ramautarsing, Reshmie Ashmanie; Phanuphak, Nittaya; Teeratakulpisarn, Nipat; Pinyakorn, Suteeraporn; Rodbamrung, Piyanee; Chaithongwongwatthana, Surasith; Ananworanich, Jintanat

2013-07-01

Effective contraception can be lifesaving by reducing maternal mortality linked to childbirth and unsafe abortion and by reducing vertical and horizontal transmission of HIV, in the case of an HIV-positive woman. This study is a secondary analysis of a prospective cohort study. We assessed factors associated with the use of irreversible contraception and the continuous use of reversible contraception in HIV-positive Thai women. We used descriptive statistics to present baseline characteristics and logistic regression to assess the association between contraceptive use and factors in the study. Of 196 women included in the analysis, 87% self-reported always using male condoms and 56% continuously using another effective contraceptive method during the period of the study (12-18 months). The choice of effective contraceptive methods was suboptimal--42% were sterilized, 14% used hormonal contraception and no participant reported the use of an intrauterine device. Sexual activity and past contraceptive use were factors associated positively with current continuous contraceptive use. Live births and lower levels of education were additional factors associated positively with sterilization. Despite high contraceptive use, there are still uncovered contraceptive needs among HIV-positive women in Thailand. HIV-positive women need established specialized family planning services, offering an optimal variety of contraceptive choices and tailored to their individual needs. As sterilization is an irreversible choice, it cannot be a viable alternative for every woman. Due to the positive trend between current and past contraceptive use, we consider that it may be possible to improve family planning programs if they start as early as possible in a woman's life and are continued throughout her sexually active and reproductive years. Copyright © 2013 Elsevier Inc. All rights reserved.

Factorization of cp-rank-3 completely positive matrices

Czech Academy of Sciences Publication Activity Database

Brandts, J.; Křížek, Michal

2016-01-01

Roč. 66, č. 3 (2016), s. 955-970 ISSN 0011-4642 R&D Projects: GA ČR GA14-02067S Institutional support: RVO:67985840 Keywords : completely positive matrix * cp-rank * factorization Subject RIV: BA - General Mathematics Impact factor: 0.364, year: 2016 http://hdl.handle.net/10338.dmlcz/145882

Positive and negative associations of individual social capital factors with health among community-dwelling older people.

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Kabayama, Mai; Watanabe, Chie; Ryuno, Hirochika; Kamide, Kei

2017-12-01

Previous literature has found positive correlations between social capital and health in older adults, fewer studies have investigated the subdimension's effects of social capital on health. We aimed to determine the individual social capital subfactors in community-dwelling older adults in Japan, and to analyze the associations of these factors with physical and mental health. We sent a self-administered questionnaire assessing their perception of social group activity as the individual social capital, and mental and physical health (measured by the Medical Outcomes Study Short Form-36) to 4320 randomly selected older people. There were 1836 valid responses. We clarified that people who participated in any social activity group were in significantly better physical and mental health compared with the people who did not. By the factor analysis of the perception for the social group activity, we identified three components of the individual social capital aspect that we termed harmonious, hierarchic and diversity. Using multiple linear regression, we found the hierarchic aspect was significantly negatively associated with mental health, whereas the harmonious aspect was significantly positively associated with mental and physical health, and diversity was significantly positively associated with mental health. As the previous research literature on social capital has mainly emphasized its positive health consequences, the present findings provide a novel demonstration that some aspects of individual social capital can have negative associations with health outcomes in community-dwelling older people. For the practical application of promoting a healthier society, it is important to consider both the positive and negative sides of social capital. Geriatr Gerontol Int 2017; 17: 2427-2434. © 2017 Japan Geriatrics Society.

Clinicopathologic Risk Factor Distributions for MLH1 Promoter Region Methylation in CIMP-Positive Tumors.

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Levine, A Joan; Phipps, Amanda I; Baron, John A; Buchanan, Daniel D; Ahnen, Dennis J; Cohen, Stacey A; Lindor, Noralane M; Newcomb, Polly A; Rosty, Christophe; Haile, Robert W; Laird, Peter W; Weisenberger, Daniel J

2016-01-01

The CpG island methylator phenotype (CIMP) is a major molecular pathway in colorectal cancer. Approximately 25% to 60% of CIMP tumors are microsatellite unstable (MSI-H) due to DNA hypermethylation of the MLH1 gene promoter. Our aim was to determine if the distributions of clinicopathologic factors in CIMP-positive tumors with MLH1 DNA methylation differed from those in CIMP-positive tumors without DNA methylation of MLH1. We assessed the associations between age, sex, tumor-site, MSI status BRAF and KRAS mutations, and family colorectal cancer history with MLH1 methylation status in a large population-based sample of CIMP-positive colorectal cancers defined by a 5-marker panel using unconditional logistic regression to assess the odds of MLH1 methylation by study variables. Subjects with CIMP-positive tumors without MLH1 methylation were significantly younger, more likely to be male, and more likely to have distal colon or rectal primaries and the MSI-L phenotype. CIMP-positive MLH1-unmethylated tumors were significantly less likely than CIMP-positive MLH1-methylated tumors to harbor a BRAF V600E mutation and significantly more likely to harbor a KRAS mutation. MLH1 methylation was associated with significantly better overall survival (HR, 0.50; 95% confidence interval, 0.31-0.82). These data suggest that MLH1 methylation in CIMP-positive tumors is not a completely random event and implies that there are environmental or genetic determinants that modify the probability that MLH1 will become methylated during CIMP pathogenesis. MLH1 DNA methylation status should be taken into account in etiologic studies. ©2015 American Association for Cancer Research.

Clinicopathological risk factor distributions for MLH1 promoter region methylation in CIMP positive tumors

Science.gov (United States)

Levine, A. Joan; Phipps, Amanda I.; Baron, John A.; Buchanan, Daniel D.; Ahnen, Dennis J.; Cohen, Stacey A.; Lindor, Noralane M.; Newcomb, Polly A.; Rosty, Christophe; Haile, Robert W.; Laird, Peter W.; Weisenberger, Daniel J.

2015-01-01

Background The CpG Island Methylator Phenotype (CIMP) is a major molecular pathway in colorectal cancer (CRC). Approximately 25% to 60% of CIMP tumors are microsatellite unstable (MSI-H) due to DNA hypermethylation of the MLH1 gene promoter. Our aim was to determine if the distributions of clinicopathologic factors in CIMP-positive tumors with MLH1 DNA methylation differed from those in CIMP-positive tumors without DNA methylation of MLH1. Methods We assessed the associations between age, sex, tumor-site, MSI status BRAF and KRAS mutations and family CRC history with MLH1 methylation status in a large population-based sample of CIMP-positive CRCs defined by a 5-marker panel using unconditional logistic regression to assess the odds of MLH1 methylation by study variables. Results Subjects with CIMP-positive tumors without MLH1 methylation were significantly younger, more likely to be male, more likely to have distal colon or rectal primaries and the MSI-L phenotype. CIMP-positive MLH1-unmethylated tumors were significantly less likely than CIMP-positive MLH1-methylated tumors to harbor a BRAF V600E mutation and significantly more likely to harbor a KRAS mutation. MLH1 methylation was associated with significantly better overall survival (HR=0.50; 95% Confidence Interval (0.31, 0.82)). Conclusions These data suggest that MLH1 methylation in CIMP-positive tumors is not a completely random event and implies that there are environmental or genetic determinants that modify the probability that MLH1 will become methylated during CIMP pathogenesis. Impact MLH1 DNA methylation status should be taken into account in etiologic studies. PMID:26512054

Trait Mindfulness as a Limiting Factor for Residual Depressive Symptoms: An Explorative Study Using Quantile Regression

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Radford, Sholto; Eames, Catrin; Brennan, Kate; Lambert, Gwladys; Crane, Catherine; Williams, J. Mark G.; Duggan, Danielle S.; Barnhofer, Thorsten

2014-01-01

Mindfulness has been suggested to be an important protective factor for emotional health. However, this effect might vary with regard to context. This study applied a novel statistical approach, quantile regression, in order to investigate the relation between trait mindfulness and residual depressive symptoms in individuals with a history of recurrent depression, while taking into account symptom severity and number of episodes as contextual factors. Rather than fitting to a single indicator of central tendency, quantile regression allows exploration of relations across the entire range of the response variable. Analysis of self-report data from 274 participants with a history of three or more previous episodes of depression showed that relatively higher levels of mindfulness were associated with relatively lower levels of residual depressive symptoms. This relationship was most pronounced near the upper end of the response distribution and moderated by the number of previous episodes of depression at the higher quantiles. The findings suggest that with lower levels of mindfulness, residual symptoms are less constrained and more likely to be influenced by other factors. Further, the limiting effect of mindfulness on residual symptoms is most salient in those with higher numbers of episodes. PMID:24988072

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.

Regression in autistic spectrum disorders.

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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.

Recreational drug use and related social factors among HIV-positive men in Japan.

Science.gov (United States)

Togari, Taisuke; Inoue, Yoji; Takaku, Yosuke; Abe, Sakurako; Hosokawa, Rikuya; Itagaki, Takashi; Yoshizawa, Shigeyuki; Oki, Sachiko; Katakura, Naoko; Yamauchi, Asae; Wakabayashi, Chihiro; Yajima, Takashi

2016-07-01

This study aims to determine the relationship between recreational drug use in HIV-positive males in the past year and socio-economic factors and/or social support networks in Japan. A national online survey in a cross-sectional study was conducted by HIV Futures Japan project from July 2013 to February 2014. Of the 1095 HIV-positive individuals who responded, 913 responses were determined to be valid; responses from the 875 males were analysed. A total of 282 participants used addictive drugs (32.2%) in past year. New psychoactive substances were used by 121 participants (13.8%), methamphetamine or amphetamine by 47 (5.4%), air dusters/sprays/gas by 31 (3.5%), 5-methoxy-N,N-diisopropyltryptamine (5MeO-DIPT) by 16 (1.8%) and cannabis (1.0%) by 9. Multiple logistic regression analysis was performed with the use of alkyl nitrites, addictive drugs, air dusters and thinners, which are low illegality, as dependent variables. We found that the odds ratio (95% confidence interval) for use among participants with full-time and temp/contracted/part-time employees compared to management/administration professions were 2.59 (0.99-6.77) and 2.61 (0.91-7.51). Also, a correlation was observed between alkyl nitrites and new psychoactive substances and usage rates in people engaged in few HIV-positive networks. It is necessary to develop targeted policies for drug use prevention and user support among HIV-positive men and to support and provide care for drug users who are isolated or have a narrow HIV/AIDS support network.

Using Structured Additive Regression Models to Estimate Risk Factors of Malaria: Analysis of 2010 Malawi Malaria Indicator Survey Data

Science.gov (United States)

Chirombo, James; Lowe, Rachel; Kazembe, Lawrence

2014-01-01

Background After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions. Methods We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi. Results Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk. Conclusions The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities. PMID:24991915

Total-Factor Energy Efficiency (TFEE Evaluation on Thermal Power Industry with DEA, Malmquist and Multiple Regression Techniques

Directory of Open Access Journals (Sweden)

Jin-Peng Liu

2017-07-01

Full Text Available Under the background of a new round of power market reform, realizing the goals of energy saving and emission reduction, reducing the coal consumption and ensuring the sustainable development are the key issues for thermal power industry. With the biggest economy and energy consumption scales in the world, China should promote the energy efficiency of thermal power industry to solve these problems. Therefore, from multiple perspectives, the factors influential to the energy efficiency of thermal power industry were identified. Based on the economic, social and environmental factors, a combination model with Data Envelopment Analysis (DEA and Malmquist index was constructed to evaluate the total-factor energy efficiency (TFEE in thermal power industry. With the empirical studies from national and provincial levels, the TFEE index can be factorized into the technical efficiency index (TECH, the technical progress index (TPCH, the pure efficiency index (PECH and the scale efficiency index (SECH. The analysis showed that the TFEE was mainly determined by TECH and PECH. Meanwhile, by panel data regression model, unit coal consumption, talents and government supervision were selected as important indexes to have positive effects on TFEE in thermal power industry. In addition, the negative indexes, such as energy price and installed capacity, were also analyzed to control their undesired effects. Finally, considering the analysis results, measures for improving energy efficiency of thermal power industry were discussed widely, such as strengthening technology research and design (R&D, enforcing pollutant and emission reduction, distributing capital and labor rationally and improving the government supervision. Relative study results and suggestions can provide references for Chinese government and enterprises to enhance the energy efficiency level.

Evaluating risk factors for endemic human Salmonella Enteritidis infections with different phage types in Ontario, Canada using multinomial logistic regression and a case-case study approach

Directory of Open Access Journals (Sweden)

Varga Csaba

2012-10-01

Full Text Available Abstract Background Identifying risk factors for Salmonella Enteritidis (SE infections in Ontario will assist public health authorities to design effective control and prevention programs to reduce the burden of SE infections. Our research objective was to identify risk factors for acquiring SE infections with various phage types (PT in Ontario, Canada. We hypothesized that certain PTs (e.g., PT8 and PT13a have specific risk factors for infection. Methods Our study included endemic SE cases with various PTs whose isolates were submitted to the Public Health Laboratory-Toronto from January 20th to August 12th, 2011. Cases were interviewed using a standardized questionnaire that included questions pertaining to demographics, travel history, clinical symptoms, contact with animals, and food exposures. A multinomial logistic regression method using the Generalized Linear Latent and Mixed Model procedure and a case-case study design were used to identify risk factors for acquiring SE infections with various PTs in Ontario, Canada. In the multinomial logistic regression model, the outcome variable had three categories representing human infections caused by SE PT8, PT13a, and all other SE PTs (i.e., non-PT8/non-PT13a as a referent category to which the other two categories were compared. Results In the multivariable model, SE PT8 was positively associated with contact with dogs (OR=2.17, 95% CI 1.01-4.68 and negatively associated with pepper consumption (OR=0.35, 95% CI 0.13-0.94, after adjusting for age categories and gender, and using exposure periods and health regions as random effects to account for clustering. Conclusions Our study findings offer interesting hypotheses about the role of phage type-specific risk factors. Multinomial logistic regression analysis and the case-case study approach are novel methodologies to evaluate associations among SE infections with different PTs and various risk factors.

Neutron Buildup Factors Calculation for Support Vector Regression Application in Shielding Analysis

International Nuclear Information System (INIS)

Duckic, P.; Matijevic, M.; Grgic, D.

2016-01-01

In this paper initial set of data for neutron buildup factors determination using Support Vector Regression (SVR) method is prepared. The performance of SVR technique strongly depends on the quality of information used for model training. Thus it is very important to provide representable data to the SVR. SVR is a supervised type of learning so it demands data in the input/output form. In the case of neutron buildup factors estimation, the input parameters are the incident neutron energy, shielding thickness and shielding material and the output parameter is the neutron buildup factor value. So far the initial sets of data for different shielding configurations have been obtained using SCALE4.4 sequence SAS3. However, this results were obtained using group constants, thus the incident neutron energy was determined as the average value for each energy group. Obtained this way, the data provided to the SVR are fewer and therefore insufficient. More valuable information is obtained using SCALE6.2beta5 sequence MAVRIC which can perform calculations for the explicit incident neutron energy, which leads to greater maneuvering possibilities when active learning measures are employed, and consequently improves the quality of the developed SVR model.(author).

The risk factor of false-negative and false-positive for T-SPOT.TB in active tuberculosis.

Science.gov (United States)

Di, Li; Li, Yan

2018-02-01

T-SPOT.TB is a promising diagnosis tool to identify both pulmonary tuberculosis and extrapulmonary tuberculosis, as well as latent tuberculosis; however, the factors that affect the results of T-SPOT.TB remains unclear. In this study, we aim to figure out the risk factor of T-SPOT.TB for active TB. A total of 349 patients were recruited between January 1st, 2016 and January 22st, 2017 at Renmin Hospital of Wuhan University, including 98 subjects with TB and 251 subjects with non-TB disease, and received T-SPOT.TB (Oxford Immunotec Ltd). Statistics were analyzed by SPSS 19.0 using logistic regression. The overall specificity and sensitivity of the T-SPOT.TB was 92.83% (233/251; 95%CI 0.8872-0.9557) and 83.67% (82/98; 95%CI 0.7454-0.9010), respectively. Patients with tuberculous meningitis were more likely to have false-negative results (OR 17.4, 95%CI 3.068-98.671; P.05). Tuberculous meningitis was a risk factor of false-negative for T-SPOT.TB, while cured TB was a risk factor of false-positive. © 2017 Wiley Periodicals, Inc.

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.

Applying spatial regression to evaluate risk factors for microbiological contamination of urban groundwater sources in Juba, South Sudan

Science.gov (United States)

Engström, Emma; Mörtberg, Ulla; Karlström, Anders; Mangold, Mikael

2017-06-01

This study developed methodology for statistically assessing groundwater contamination mechanisms. It focused on microbial water pollution in low-income regions. Risk factors for faecal contamination of groundwater-fed drinking-water sources were evaluated in a case study in Juba, South Sudan. The study was based on counts of thermotolerant coliforms in water samples from 129 sources, collected by the humanitarian aid organisation Médecins Sans Frontières in 2010. The factors included hydrogeological settings, land use and socio-economic characteristics. The results showed that the residuals of a conventional probit regression model had a significant positive spatial autocorrelation (Moran's I = 3.05, I-stat = 9.28); therefore, a spatial model was developed that had better goodness-of-fit to the observations. The most significant factor in this model ( p-value 0.005) was the distance from a water source to the nearest Tukul area, an area with informal settlements that lack sanitation services. It is thus recommended that future remediation and monitoring efforts in the city be concentrated in such low-income regions. The spatial model differed from the conventional approach: in contrast with the latter case, lowland topography was not significant at the 5% level, as the p-value was 0.074 in the spatial model and 0.040 in the traditional model. This study showed that statistical risk-factor assessments of groundwater contamination need to consider spatial interactions when the water sources are located close to each other. Future studies might further investigate the cut-off distance that reflects spatial autocorrelation. Particularly, these results advise research on urban groundwater quality.

Influential factors of red-light running at signalized intersection and prediction using a rare events logistic regression model.

Science.gov (United States)

Ren, Yilong; Wang, Yunpeng; Wu, Xinkai; Yu, Guizhen; Ding, Chuan

2016-10-01

Red light running (RLR) has become a major safety concern at signalized intersection. To prevent RLR related crashes, it is critical to identify the factors that significantly impact the drivers' behaviors of RLR, and to predict potential RLR in real time. In this research, 9-month's RLR events extracted from high-resolution traffic data collected by loop detectors from three signalized intersections were applied to identify the factors that significantly affect RLR behaviors. The data analysis indicated that occupancy time, time gap, used yellow time, time left to yellow start, whether the preceding vehicle runs through the intersection during yellow, and whether there is a vehicle passing through the intersection on the adjacent lane were significantly factors for RLR behaviors. Furthermore, due to the rare events nature of RLR, a modified rare events logistic regression model was developed for RLR prediction. The rare events logistic regression method has been applied in many fields for rare events studies and shows impressive performance, but so far none of previous research has applied this method to study RLR. The results showed that the rare events logistic regression model performed significantly better than the standard logistic regression model. More importantly, the proposed RLR prediction method is purely based on loop detector data collected from a single advance loop detector located 400 feet away from stop-bar. This brings great potential for future field applications of the proposed method since loops have been widely implemented in many intersections and can collect data in real time. This research is expected to contribute to the improvement of intersection safety significantly. Copyright © 2016 Elsevier Ltd. All rights reserved.

Factors influencing HIV-risk behaviors among HIV-positive urban African Americans.

Science.gov (United States)

Plowden, Keith O; Fletcher, Audwin; Miller, J Lawrence

2005-01-01

Urban African Americans are disproportionately affected by HIV, the virus associated with AIDS. Although incidence and mortality appear to be decreasing in some populations, they continue to remain steady among inner-city African Americans. A major concern is the number of HIV-positive individuals who continue to practice high-risk behaviors. Understanding factors that increase risks is essential for the development and implementation of effective prevention initiatives. Following a constructionist epistemology, this study used ethnography to explore social and cultural factors that influence high-risk behaviors among inner-city HIV-positive African Americans. Leininger's culture care diversity and universality theory guided the study. Individual qualitative interviews were conducted with HIV-positive African Americans in the community to explore social and cultural factors that increase HIV-risky behaviors. For this study, family/kinship, economic, and education factors played a significant role in risky behaviors. Reducing HIV disparity among African Americans is dependent on designing appropriate interventions that enhance protective factors. Clinicians providing care to HIV-positive individuals can play a key role in reducing transmission by recognizing and incorporating these factors when designing effective prevention interventions.

A study of the dengue epidemic and meteorological factors in Guangzhou, China, by using a zero-inflated Poisson regression model.

Science.gov (United States)

Wang, Chenggang; Jiang, Baofa; Fan, Jingchun; Wang, Furong; Liu, Qiyong

2014-01-01

The aim of this study is to develop a model that correctly identifies and quantifies the relationship between dengue and meteorological factors in Guangzhou, China. By cross-correlation analysis, meteorological variables and their lag effects were determined. According to the epidemic characteristics of dengue in Guangzhou, those statistically significant variables were modeled by a zero-inflated Poisson regression model. The number of dengue cases and minimum temperature at 1-month lag, along with average relative humidity at 0- to 1-month lag were all positively correlated with the prevalence of dengue fever, whereas wind velocity and temperature in the same month along with rainfall at 2 months' lag showed negative association with dengue incidence. Minimum temperature at 1-month lag and wind velocity in the same month had a greater impact on the dengue epidemic than other variables in Guangzhou.

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...

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.

Determination of osteoporosis risk factors using a multiple logistic regression model in postmenopausal Turkish women.

Science.gov (United States)

Akkus, Zeki; Camdeviren, Handan; Celik, Fatma; Gur, Ali; Nas, Kemal

2005-09-01

To determine the risk factors of osteoporosis using a multiple binary logistic regression method and to assess the risk variables for osteoporosis, which is a major and growing health problem in many countries. We presented a case-control study, consisting of 126 postmenopausal healthy women as control group and 225 postmenopausal osteoporotic women as the case group. The study was carried out in the Department of Physical Medicine and Rehabilitation, Dicle University, Diyarbakir, Turkey between 1999-2002. The data from the 351 participants were collected using a standard questionnaire that contains 43 variables. A multiple logistic regression model was then used to evaluate the data and to find the best regression model. We classified 80.1% (281/351) of the participants using the regression model. Furthermore, the specificity value of the model was 67% (84/126) of the control group while the sensitivity value was 88% (197/225) of the case group. We found the distribution of residual values standardized for final model to be exponential using the Kolmogorow-Smirnow test (p=0.193). The receiver operating characteristic curve was found successful to predict patients with risk for osteoporosis. This study suggests that low levels of dietary calcium intake, physical activity, education, and longer duration of menopause are independent predictors of the risk of low bone density in our population. Adequate dietary calcium intake in combination with maintaining a daily physical activity, increasing educational level, decreasing birth rate, and duration of breast-feeding may contribute to healthy bones and play a role in practical prevention of osteoporosis in Southeast Anatolia. In addition, the findings of the present study indicate that the use of multivariate statistical method as a multiple logistic regression in osteoporosis, which maybe influenced by many variables, is better than univariate statistical evaluation.

Hematological findings and factors associated with feline leukemia virus (FeLV and feline immunodeficiency virus (FIV positivity in cats from southern Brazil

Directory of Open Access Journals (Sweden)

Fernanda V.A. da Costa

Full Text Available ABSTRACT: Using a retrospective study, 493 cats tested for FeLV and FIV were selected for analysis of the association between hematologic findings and positivity at immunoassay test. Individual and hematologic variables were assessed considering the influence of results using univariate and multivariate logistic regression analysis. Out 153 of the 493 cats were positive for FeLV (31%, 50 were positive for FIV (10.1% and 22 were positive for both FIV and FeLV (4.4%. Multivariate analysis detected significant associations between FeLV infection and age below 1 year (p=0.01, age from 1 to 10 years (p=0.03, and crossbreed (p=0.04. Male cats were more likely to be FIV-positive (p=0.002. Regarding hematological changes, FeLV-positive cats have higher odds to anemia, leukopenia and lymphopenia than FeLV-negative cats. FIV-positive cats are more likely to have anemia than negative. Identification of associated factors related to animal status and correlation of hematological disorders with infection by retroviruses in cats could be useful for detecting these retroviral diseases in cats.

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

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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.

Bias in logistic regression due to imperfect diagnostic test results and practical correction approaches.

Science.gov (United States)

Valle, Denis; Lima, Joanna M Tucker; Millar, Justin; Amratia, Punam; Haque, Ubydul

2015-11-04

Logistic regression is a statistical model widely used in cross-sectional and cohort studies to identify and quantify the effects of potential disease risk factors. However, the impact of imperfect tests on adjusted odds ratios (and thus on the identification of risk factors) is under-appreciated. The purpose of this article is to draw attention to the problem associated with modelling imperfect diagnostic tests, and propose simple Bayesian models to adequately address this issue. A systematic literature review was conducted to determine the proportion of malaria studies that appropriately accounted for false-negatives/false-positives in a logistic regression setting. Inference from the standard logistic regression was also compared with that from three proposed Bayesian models using simulations and malaria data from the western Brazilian Amazon. A systematic literature review suggests that malaria epidemiologists are largely unaware of the problem of using logistic regression to model imperfect diagnostic test results. Simulation results reveal that statistical inference can be substantially improved when using the proposed Bayesian models versus the standard logistic regression. Finally, analysis of original malaria data with one of the proposed Bayesian models reveals that microscopy sensitivity is strongly influenced by how long people have lived in the study region, and an important risk factor (i.e., participation in forest extractivism) is identified that would have been missed by standard logistic regression. Given the numerous diagnostic methods employed by malaria researchers and the ubiquitous use of logistic regression to model the results of these diagnostic tests, this paper provides critical guidelines to improve data analysis practice in the presence of misclassification error. Easy-to-use code that can be readily adapted to WinBUGS is provided, enabling straightforward implementation of the proposed Bayesian models.

The epidemiology of smear positive pulmonary tuberculosis at ...

African Journals Online (AJOL)

Currently, data regarding the magnitude of TB and associated factors have been released at different health facilities as part of service auditing. However ... Logistic regression model was used to analyze the association between TB positivity and potential associated variables; p < 0.05 was considered to be significant.

On Positive Semidefinite Modification Schemes for Incomplete Cholesky Factorization

Czech Academy of Sciences Publication Activity Database

Scott, J.; Tůma, Miroslav

2014-01-01

Roč. 36, č. 2 (2014), A609-A633 ISSN 1064-8275 R&D Projects: GA ČR GA13-06684S Institutional support: RVO:67985807 Keywords : sparse matrices * sparse linear systems * positive-definite symmetric systems * iterative solvers * preconditioning * incomplete Cholesky factorization Subject RIV: BA - General Mathematics Impact factor: 1.854, year: 2014

Factors Associated with Delayed Enrollment in HIV Medical Care among HIV-Positive Individuals in Odessa Region, Ukraine.

Science.gov (United States)

Neduzhko, Oleksandr; Postnov, Oleksandr; Perehinets, Ihor; DeHovitz, Jack; Joseph, Michael; Odegaard, David; Kaplan, Robert; Kiriazova, Tetiana

In Ukraine, about one-third of identified HIV-positive individuals are not connected to care. We conducted a cross-sectional survey (n = 200) among patients registered at Odessa AIDS centers in October to December 2011. Factors associated with delayed enrollment in HIV care (>3 months since positive HIV test) were evaluated using logistic regression. Among study participants (mean age 35 ± 8.2 years, 47.5% female, 42.5% reported history of injecting drugs), 55% delayed HIV care enrollment. Odds of delayed enrollment were higher for those with lower educational attainment (adjusted odds ratio [aOR]: 2.65, 95% confidence interval [CI]: 1.04-6.76), not feeling ill (aOR: 2.98, 95% CI: 1.50-5.93), or not having time to go to the AIDS center (aOR: 3.89, 95% CI: 1.39-10.89); injection drug use was not associated with delayed enrollment. Programs linking HIV-positive individuals to specialized care should address enrollment barriers and include education on HIV care benefits and case management for direct linkage to care. HIV testing and treatment should be coupled to ensure a continuum of care.

A Robust Incomplete Factorization Preconditioner for Positive Definite Matrices

Czech Academy of Sciences Publication Activity Database

Benzi, M.; Tůma, Miroslav

2003-01-01

Roč. 10, - (2003), s. 385-400 ISSN 1070-5325 R&D Projects: GA AV ČR IAA2030801; GA AV ČR IAA1030103 Institutional research plan: AV0Z1030915 Keywords : sparse linear systems * positive definite matrices * preconditioned conjugate gradient s * incomplete factorization * A-orthogonalization * SAINV Subject RIV: BA - General Mathematics Impact factor: 1.042, year: 2003

[Predictive factors for failure of non-invasive positive pressure ventilation in immunosuppressed patients with acute respiratory failure].

Science.gov (United States)

Jia, Xiangli; Yan, Ci; Xu, Sicheng; Gu, Xingli; Wan, Qiufeng; Hu, Xinying; Li, Jingwen; Liu, Guangming; Caikai, Shareli; Guo, Zhijin

2018-02-01

To evaluate the predictive factors for failure of non-invasive positive pressure ventilation (NIPPV) in immunosuppressed patients with acute respiratory failure (ARF). The clinical data of 118 immuno-deficient patients treated with NIPPV in the respiratory and intensive care unit (RICU) of the First Affiliated Hospital of Xinjiang Medical University from January 2012 to August 2017 were retrospectively analyzed. The patients were divided into a non-endotracheal intubation (ETI) group (n = 62) and ETI group (n = 56) according to whether ETI was performed during the hospitalization period or not. Each observed indicator was analyzed by univariate analysis, and factors leading to failure of NIPPV were further analyzed by Logistic regression. Receiver operating characteristic (ROC) curve was plotted to evaluate the predictive value of risk factors for failure of NIPPV in immunosuppressed patients with ARF. The non-intubation rate for NIPPV in immunosuppressed patients was 50.8% (60/118). Compared with the non-ETI group, the body temperature, pH value in the ETI group were significantly increased, the partial pressure of arterial carbon dioxide (PaCO 2 ) was significantly decreased, the ratio of oxygenation index (PaO 2 /FiO 2 ) failure of NIPPV. ROC curve analysis showed that the APACHE II score ≥ 20 and PaO 2 /FiO 2 failure of NIPPV, the area under ROC curve (AUC) of the APACHE II score ≥ 20 was 0.787, the sensitivity was 83.93%, the specificity was 69.35%, the positive predict value (PPV) was 71.21%, the negative predict value (NPV) was 82.69%, the positive likelihood ratio (PLR) was 2.74, the negative likelihood ratio (NLR) was 0.23, and Youden index was 0.53; the AUC of PaO 2 /FiO 2 failure of NIPPV in immunocompromised patients.

Regression Levels of Selected Affective Factors on Science Achievement: A Structural Equation Model with TIMSS 2011 Data

Science.gov (United States)

Akilli, Mustafa

2015-01-01

The aim of this study is to demonstrate the science success regression levels of chosen emotional features of 8th grade students using Structural Equation Model. The study was conducted by the analysis of students' questionnaires and science success in TIMSS 2011 data using SEM. Initially, the factors that are thought to have an effect on science…

Incomplete factorization technique for positive definite linear systems

International Nuclear Information System (INIS)

Manteuffel, T.A.

1980-01-01

This paper describes a technique for solving the large sparse symmetric linear systems that arise from the application of finite element methods. The technique combines an incomplete factorization method called the shifted incomplete Cholesky factorization with the method of generalized conjugate gradients. The shifted incomplete Cholesky factorization produces a splitting of the matrix A that is dependent upon a parameter α. It is shown that if A is positive definite, then there is some α for which this splitting is possible and that this splitting is at least as good as the Jacobi splitting. The method is shown to be more efficient on a set of test problems than either direct methods or explicit iteration schemes

Perceived positive teacher-student relationship as a protective factor for Chinese left-behind children's emotional and behavioural adjustment.

Science.gov (United States)

Liu, Yan; Li, Xiaowei; Chen, Li; Qu, Zhiyong

2015-10-01

Using cross-sectional data collected in rural communities of two provinces of China, this study examined the protective role of perceived positive teacher-student relationship for Chinese left-behind children. The participants included 1442 children with a mean age of 14.13 classified into two groups: a left-behind group (104 boys and 110 girls) and a comparison group (588 boys and 640 girls). Self-reported questionnaires concerning self-esteem, depression, problem behaviours and the teacher-student relationship were administered. Relative to the comparison group, after controlling for age, gender and family socioeconomic status, the left-behind group was disadvantaged in terms of self-esteem and depression but not in problem behaviours. As hypothesised, the results of regression analyses indicated that teacher-student relationship positively predicted self-esteem and negatively predicted depression and problem behaviours for both groups. Moreover, the association between teacher-student relationship and depression was stronger among the left-behind group, suggesting that left-behind children were more responsive to the positive effect of a desired teacher-student relationship. Taken together, the results of our study support the idea that perceived positive teacher-student relationship may serve as a protective factor for left-behind children. Practical implications and limitations of the present study are discussed. © 2014 International Union of Psychological Science.

Local bilinear multiple-output quantile/depth regression

Czech Academy of Sciences Publication Activity Database

Hallin, M.; Lu, Z.; Paindaveine, D.; Šiman, Miroslav

2015-01-01

Roč. 21, č. 3 (2015), s. 1435-1466 ISSN 1350-7265 R&D Projects: GA MŠk(CZ) 1M06047 Institutional support: RVO:67985556 Keywords : conditional depth * growth chart * halfspace depth * local bilinear regression * multivariate quantile * quantile regression * regression depth Subject RIV: BA - General Mathematics Impact factor: 1.372, year: 2015 http://library.utia.cas.cz/separaty/2015/SI/siman-0446857.pdf

Relationship between positive self-recognition of maternal role and psychosocial factors in Japanese mothers with severe mental illness.

Science.gov (United States)

Ueno, Rie; Kamibeppu, Kiyoko

2011-10-01

Mothers with mental illness have positive self-recognition of maternal role (PM), and it is important for parenting. The purpose of this study was to determine the psychosocial factors related to the PM. We recruited a total of 74 women diagnosed as having schizophrenia or mood disorders according to the DSM-IV-TR and who had minor children. Participant completed devaluation-discrimination measure, The social support questionnaire, self-efficacy for community life scale (SECL), parenting stress-short form scale (PS-SF), and Acceptance of maternal role scale. To identify factors predicting the PM, we utilized hierarchical regression analysis. The variables in all blocks explained 53% of the variance in the PM. In the final model, 'hard' living conditions (β = -0.31, P < 0.05), SECL (β = 0.34, P < 0.01) and PS-SF (β = -0.45, P < 0.01) were significant predictors of the PM. Our result indicates that psychosocial approach could enhance the PM.

Increased Age-Dependent Risk of Death Associated With lukF-PV-Positive Staphylococcus aureus Bacteremia

DEFF Research Database (Denmark)

Knudsen, Trine A; Skov, Robert; Petersen, Andreas

2016-01-01

BACKGROUND: Panton-Valentine leucocidin is a Staphylococcus aureus virulence factor encoded by lukF-PV and lukS-PV that is infrequent in S aureus bacteremia (SAB), and, therefore, little is known about risk factors and outcome of lukF-PV/lukS-PV-positive SAB. METHODS: This report is a register......-based nationwide observational cohort study. lukF-PV was detected by polymerase chain reaction. Factors associated with the presence of lukF-PV were assessed by logistic regression analysis. Adjusted 30-day hazard ratios of mortality associated with lukF-PV status were computed by Cox proportional hazards...... regression analysis. RESULTS: Of 9490 SAB cases, 129 were lukF-PV-positive (1.4%), representing 14 different clonal complexes. lukF-PV was associated with younger age, absence of comorbidity, and methicillin-resistant S aureus. In unadjusted analysis, mortality associated with lukF-PV-positive SAB...

Sensitivity of Microstructural Factors Influencing the Impact Toughness of Hypoeutectoid Steels with Ferrite-Pearlite Structure using Multiple Regression Analysis

International Nuclear Information System (INIS)

Lee, Seung-Yong; Lee, Sang-In; Hwang, Byoung-chul

2016-01-01

In this study, the effect of microstructural factors on the impact toughness of hypoeutectoid steels with ferrite-pearlite structure was quantitatively investigated using multiple regression analysis. Microstructural analysis results showed that the pearlite fraction increased with increasing austenitizing temperature and decreasing transformation temperature which substantially decreased the pearlite interlamellar spacing and cementite thickness depending on carbon content. The impact toughness of hypoeutectoid steels usually increased as interlamellar spacing or cementite thickness decreased, although the impact toughness was largely associated with pearlite fraction. Based on these results, multiple regression analysis was performed to understand the individual effect of pearlite fraction, interlamellar spacing, and cementite thickness on the impact toughness. The regression analysis results revealed that pearlite fraction significantly affected impact toughness at room temperature, while cementite thickness did at low temperature.

Impacts on CO2 Emission Allowance Prices in China: A Quantile Regression Analysis of the Shanghai Emission Trading Scheme

Directory of Open Access Journals (Sweden)

Jie Zhang

2016-11-01

Full Text Available A pilot regional carbon emission trading scheme (ETS has been implemented in China for more than two years. An investigation into the impacts of different factors on carbon dioxide (CO2 emission allowance prices provides guidance for price-making in 2017 when the nation-wide ETS of China will be established. This paper adopts a quantile regression approach to estimate the impacts of different factors in Shanghai emission trading scheme (SH-ETS, namely, economic growth, energy prices and temperature. The empirical analysis shows that: (i the economic growth in Shanghai leads to a drop in the carbon allowance prices; (ii the oil price has a slightly positive effect on the allowance prices regardless of the ordinary least squares (OLS or quantile regression method; (iii a long-run negative relationship exists between the coal price and the Shanghai emission allowances (SHEA prices, but a positive interaction under different quantiles, especially the 25%–50% quantiles; (iv temperature has a significantly positive effect at the 20%–30% quantiles and a conspicuous negative impact at the right tail of the allowances prices.

Logistic Regression Analysis on Factors Affecting Adoption of Rice-Fish Farming in North Iran

Directory of Open Access Journals (Sweden)

Seyyed Ali NOORHOSSEINI-NIYAKI

2012-06-01

Full Text Available We evaluated the factors influencing the adoption of rice-fish farming in the Tavalesh region near the Caspian Sea in northern Iran. We conducted a survey with open-ended questions. Data were collected from 184 respondents (61 adopters and 123 non-adopters randomly sampled from selected villages and analyzed using logistic regression and multi-response analysis. Family size, number of contacts with an extension agent, participation in extension-education activities, membership in social institutions and the presence of farm workers were the most important socio-economic factors for the adoption of rice-fish farming system. In addition, economic problems were the most common issue reported by adopters. Other issues such as lack of access to appropriate fish food, losses of fish, lack of access to high quality fish fingerlings and dehydration and poor water quality were also important to a number of farmers.

Quasi-Poisson versus negative binomial regression models in identifying factors affecting initial CD4 cell count change due to antiretroviral therapy administered to HIV-positive adults in North-West Ethiopia (Amhara region).

Science.gov (United States)

Seyoum, Awoke; Ndlovu, Principal; Zewotir, Temesgen

2016-01-01

CD4 cells are a type of white blood cells that plays a significant role in protecting humans from infectious diseases. Lack of information on associated factors on CD4 cell count reduction is an obstacle for improvement of cells in HIV positive adults. Therefore, the main objective of this study was to investigate baseline factors that could affect initial CD4 cell count change after highly active antiretroviral therapy had been given to adult patients in North West Ethiopia. A retrospective cross-sectional study was conducted among 792 HIV positive adult patients who already started antiretroviral therapy for 1 month of therapy. A Chi square test of association was used to assess of predictor covariates on the variable of interest. Data was secondary source and modeled using generalized linear models, especially Quasi-Poisson regression. The patients' CD4 cell count changed within a month ranged from 0 to 109 cells/mm 3 with a mean of 15.9 cells/mm 3 and standard deviation 18.44 cells/mm 3 . The first month CD4 cell count change was significantly affected by poor adherence to highly active antiretroviral therapy (aRR = 0.506, P value = 2e -16 ), fair adherence (aRR = 0.592, P value = 0.0120), initial CD4 cell count (aRR = 1.0212, P value = 1.54e -15 ), low household income (aRR = 0.63, P value = 0.671e -14 ), middle income (aRR = 0.74, P value = 0.629e -12 ), patients without cell phone (aRR = 0.67, P value = 0.615e -16 ), WHO stage 2 (aRR = 0.91, P value = 0.0078), WHO stage 3 (aRR = 0.91, P value = 0.0058), WHO stage 4 (0876, P value = 0.0214), age (aRR = 0.987, P value = 0.000) and weight (aRR = 1.0216, P value = 3.98e -14 ). Adherence to antiretroviral therapy, initial CD4 cell count, household income, WHO stages, age, weight and owner of cell phone played a major role for the variation of CD4 cell count in our data. Hence, we recommend a close follow-up of patients to adhere the prescribed medication for

Logistic regression analysis of the risk factors of anastomotic fistula after radical resection of esophageal‐cardiac cancer

Science.gov (United States)

Huang, Jinxi; Wang, Chenghu; Yuan, Weiwei; Zhang, Zhandong; Chen, Beibei; Zhang, Xiefu

2017-01-01

Background This study was conducted to investigate the risk factors of anastomotic fistula after the radical resection of esophageal‐cardiac cancer. Methods Five hundred and forty‐four esophageal‐cardiac cancer patients who underwent surgery and had complete clinical data were included in the study. Fifty patients diagnosed with postoperative anastomotic fistula were considered the case group and the remaining 494 subjects who did not develop postoperative anastomotic fistula were considered the control. The potential risk factors for anastomotic fistula, such as age, gender, diabetes history, smoking history, were collected and compared between the groups. Statistically significant variables were substituted into logistic regression to further evaluate the independent risk factors for postoperative anastomotic fistulas in esophageal‐cardiac cancer. Results The incidence of anastomotic fistulas was 9.2% (50/544). Logistic regression analysis revealed that female gender (P < 0.05), laparoscopic surgery (P < 0.05), decreased postoperative albumin (P < 0.05), and postoperative renal dysfunction (P < 0.05) were independent risk factors for anastomotic fistulas in patients who received surgery for esophageal‐cardiac cancer. Of the 50 anastomotic fistulas, 16 cases were small fistulas, which were only discovered by conventional imaging examination and not presenting clinical symptoms. All of the anastomotic fistulas occurred within seven days after surgery. Five of the patients with anastomotic fistulas underwent a second surgery and three died. Conclusion Female patients with esophageal‐cardiac cancer treated with endoscopic surgery and suffering from postoperative hypoproteinemia and renal dysfunction were susceptible to postoperative anastomotic fistula. PMID:28940985

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.

The mechanical properties of high speed GTAW weld and factors of nonlinear multiple regression model under external transverse magnetic field

Science.gov (United States)

Lu, Lin; Chang, Yunlong; Li, Yingmin; He, Youyou

2013-05-01

A transverse magnetic field was introduced to the arc plasma in the process of welding stainless steel tubes by high-speed Tungsten Inert Gas Arc Welding (TIG for short) without filler wire. The influence of external magnetic field on welding quality was investigated. 9 sets of parameters were designed by the means of orthogonal experiment. The welding joint tensile strength and form factor of weld were regarded as the main standards of welding quality. A binary quadratic nonlinear regression equation was established with the conditions of magnetic induction and flow rate of Ar gas. The residual standard deviation was calculated to adjust the accuracy of regression model. The results showed that, the regression model was correct and effective in calculating the tensile strength and aspect ratio of weld. Two 3D regression models were designed respectively, and then the impact law of magnetic induction on welding quality was researched.

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.

Computing multiple-output regression quantile regions

Czech Academy of Sciences Publication Activity Database

Paindaveine, D.; Šiman, Miroslav

2012-01-01

Roč. 56, č. 4 (2012), s. 840-853 ISSN 0167-9473 R&D Projects: GA MŠk(CZ) 1M06047 Institutional research plan: CEZ:AV0Z10750506 Keywords : halfspace depth * multiple-output regression * parametric linear programming * quantile regression Subject RIV: BA - General Mathematics Impact factor: 1.304, year: 2012 http://library.utia.cas.cz/separaty/2012/SI/siman-0376413.pdf

Repeated Results Analysis for Middleware Regression Benchmarking

Czech Academy of Sciences Publication Activity Database

Bulej, Lubomír; Kalibera, T.; Tůma, P.

2005-01-01

Roč. 60, - (2005), s. 345-358 ISSN 0166-5316 R&D Projects: GA ČR GA102/03/0672 Institutional research plan: CEZ:AV0Z10300504 Keywords : middleware benchmarking * regression benchmarking * regression testing Subject RIV: JD - Computer Applications, Robotics Impact factor: 0.756, year: 2005

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.

Association between cardiovascular risk factors and carotid intima-media thickness in prepubertal Brazilian children.

Science.gov (United States)

Gazolla, Fernanda Mussi; Neves Bordallo, Maria Alice; Madeira, Isabel Rey; de Miranda Carvalho, Cecilia Noronha; Vieira Monteiro, Alexandra Maria; Pinheiro Rodrigues, Nádia Cristina; Borges, Marcos Antonio; Collett-Solberg, Paulo Ferrez; Muniz, Bruna Moreira; de Oliveira, Cecilia Lacroix; Pinheiro, Suellen Martins; de Queiroz Ribeiro, Rebeca Mathias

2015-05-01

Early exposure to cardiovascular risk factors creates a chronic inflammatory state that could damage the endothelium followed by thickening of the carotid intima-media. To investigate the association of cardiovascular risk factors and thickening of the carotid intima. Media in prepubertal children. In this cross-sectional study, carotid intima-media thickness (cIMT) and cardiovascular risk factors were assessed in 129 prepubertal children aged from 5 to 10 year. Association was assessed by simple and multivariate logistic regression analyses. In simple logistic regression analyses, body mass index (BMI) z-score, waist circumference, and systolic blood pressure (SBP) were positively associated with increased left, right, and average cIMT, whereas diastolic blood pressure was positively associated only with increased left and average cIMT (p<0.05). In multivariate logistic regression analyses increased left cIMT was positively associated to BMI z-score and SBP, and increased average cIMT was only positively associated to SBP (p<0.05). BMI z-score and SBP were the strongest risk factors for increased cIMT.

Prediction of nucleosome positioning based on transcription factor binding sites.

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Xianfu Yi

Full Text Available BACKGROUND: The DNA of all eukaryotic organisms is packaged into nucleosomes, the basic repeating units of chromatin. The nucleosome consists of a histone octamer around which a DNA core is wrapped and the linker histone H1, which is associated with linker DNA. By altering the accessibility of DNA sequences, the nucleosome has profound effects on all DNA-dependent processes. Understanding the factors that influence nucleosome positioning is of great importance for the study of genomic control mechanisms. Transcription factors (TFs have been suggested to play a role in nucleosome positioning in vivo. PRINCIPAL FINDINGS: Here, the minimum redundancy maximum relevance (mRMR feature selection algorithm, the nearest neighbor algorithm (NNA, and the incremental feature selection (IFS method were used to identify the most important TFs that either favor or inhibit nucleosome positioning by analyzing the numbers of transcription factor binding sites (TFBSs in 53,021 nucleosomal DNA sequences and 50,299 linker DNA sequences. A total of nine important families of TFs were extracted from 35 families, and the overall prediction accuracy was 87.4% as evaluated by the jackknife cross-validation test. CONCLUSIONS: Our results are consistent with the notion that TFs are more likely to bind linker DNA sequences than the sequences in the nucleosomes. In addition, our results imply that there may be some TFs that are important for nucleosome positioning but that play an insignificant role in discriminating nucleosome-forming DNA sequences from nucleosome-inhibiting DNA sequences. The hypothesis that TFs play a role in nucleosome positioning is, thus, confirmed by the results of this study.

A logistic regression analysis of factors related to the treatment compliance of infertile patients with polycystic ovary syndrome.

Science.gov (United States)

Li, Saijiao; He, Aiyan; Yang, Jing; Yin, TaiLang; Xu, Wangming

2011-01-01

To investigate factors that can affect compliance with treatment of polycystic ovary syndrome (PCOS) in infertile patients and to provide a basis for clinical treatment, specialist consultation and health education. Patient compliance was assessed via a questionnaire based on the Morisky-Green test and the treatment principles of PCOS. Then interviews were conducted with 99 infertile patients diagnosed with PCOS at Renmin Hospital of Wuhan University in China, from March to September 2009. Finally, these data were analyzed using logistic regression analysis. Logistic regression analysis revealed that a total of 23 (25.6%) of the participants showed good compliance. Factors that significantly (p < 0.05) affected compliance with treatment were the patient's body mass index, convenience of medical treatment and concerns about adverse drug reactions. Patients who are obese, experience inconvenient medical treatment or are concerned about adverse drug reactions are more likely to exhibit noncompliance. Treatment education and intervention aimed at these patients should be strengthened in the clinic to improve treatment compliance. Further research is needed to better elucidate the compliance behavior of patients with PCOS.

Position specific variation in the rate of evolution intranscription factor binding sites

Energy Technology Data Exchange (ETDEWEB)

Moses, Alan M.; Chiang, Derek Y.; Kellis, Manolis; Lander, EricS.; Eisen, Michael B.

2003-08-28

The binding sites of sequence specific transcription factors are an important and relatively well-understood class of functional non-coding DNAs. Although a wide variety of experimental and computational methods have been developed to characterize transcription factor binding sites, they remain difficult to identify. Comparison of non-coding DNA from related species has shown considerable promise in identifying these functional non-coding sequences, even though relatively little is known about their evolution. Here we analyze the genome sequences of the budding yeasts Saccharomyces cerevisiae, S. bayanus, S. paradoxus and S. mikataeto study the evolution of transcription factor binding sites. As expected, we find that both experimentally characterized and computationally predicted binding sites evolve slower than surrounding sequence, consistent with the hypothesis that they are under purifying selection. We also observe position-specific variation in the rate of evolution within binding sites. We find that the position-specific rate of evolution is positively correlated with degeneracy among binding sites within S. cerevisiae. We test theoretical predictions for the rate of evolution at positions where the base frequencies deviate from background due to purifying selection and find reasonable agreement with the observed rates of evolution. Finally, we show how the evolutionary characteristics of real binding motifs can be used to distinguish them from artifacts of computational motif finding algorithms. As has been observed for protein sequences, the rate of evolution in transcription factor binding sites varies with position, suggesting that some regions are under stronger functional constraint than others. This variation likely reflects the varying importance of different positions in the formation of the protein-DNA complex. The characterization of the pattern of evolution in known binding sites will likely contribute to the effective use of comparative

Scale for positive aspects of caregiving experience: development, reliability, and factor structure.

Science.gov (United States)

Kate, N; Grover, S; Kulhara, P; Nehra, R

2012-06-01

OBJECTIVE. To develop an instrument (Scale for Positive Aspects of Caregiving Experience [SPACE]) that evaluates positive caregiving experience and assess its psychometric properties. METHODS. Available scales which assess some aspects of positive caregiving experience were reviewed and a 50-item questionnaire with a 5-point rating was constructed. In all, 203 primary caregivers of patients with severe mental disorders were asked to complete the questionnaire. Internal consistency, test-retest reliability, cross-language reliability, split-half reliability, and face validity were evaluated. Principal component factor analysis was run to assess the factorial validity of the scale. RESULTS. The scale developed as part of the study was found to have good internal consistency, test-retest reliability, cross-language reliability, split-half reliability, and face validity. Principal component factor analysis yielded a 4-factor structure, which also had good test-retest reliability and cross-language reliability. There was a strong correlation between the 4 factors obtained. CONCLUSION. The SPACE developed as part of this study has good psychometric properties.

Multiple regression analysis of anthropometric measurements influencing the cephalic index of male Japanese university students.

Science.gov (United States)

Hossain, Md Golam; Saw, Aik; Alam, Rashidul; Ohtsuki, Fumio; Kamarul, Tunku

2013-09-01

Cephalic index (CI), the ratio of head breadth to head length, is widely used to categorise human populations. The aim of this study was to access the impact of anthropometric measurements on the CI of male Japanese university students. This study included 1,215 male university students from Tokyo and Kyoto, selected using convenient sampling. Multiple regression analysis was used to determine the effect of anthropometric measurements on CI. The variance inflation factor (VIF) showed no evidence of a multicollinearity problem among independent variables. The coefficients of the regression line demonstrated a significant positive relationship between CI and minimum frontal breadth (p regression analysis showed a greater likelihood for minimum frontal breadth (p regression analysis revealed bizygomatic breadth, head circumference, minimum frontal breadth, head height and morphological facial height to be the best predictor craniofacial measurements with respect to CI. The results suggest that most of the variables considered in this study appear to influence the CI of adult male Japanese students.

Oral manifestations and related factors of HIV positive patients in south-east of Iran

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Shirin Saravani

2017-03-01

Full Text Available Introduction: Oral manifestations can be the first signs of human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS and a useful marker for the progression of this disease. The present study aimed to determine the prevalence of oral manifestations and examine their relationship with socio-demographic factors in HIV-positive patients in the health centers affiliated to Zahedan University of Medical Sciences (Southeast Iran. Methods: In this cross-sectional study in addition to determining oral manifestations based on the classification of EC-clearing house (European Commission clearing house, information such as age, gender, marital status, residence, education, occupation, habits, oral hygiene, loss of weight in the last six months. Body Mass Index (BMI, mode of HIV transmission, stage of disease, anti-retroviral therapy (ART, and duration of HIV were gathered through direct question from the patients or the information contained in their records. Then the relationship between various factors and oral manifestations was analyzed using Chi-square, Fisher’s Exact Test, Student T Test, Mann- Whitney tests and logistic regression. Results: Oral examination was performed on 119 HIV-positive patients who were 69.7% male and 30.3% female and had a mean age of 35.4±12.7 years. Oral manifestations were found in 57.1% of the patients. Pseudomembranous candidiasis (34.1% and linear gingival erythema (33% were the most common lesions in these patients. The probability of oral manifestations occurrence increased with age and duration of smoking in smokers with HIV (P=0.036 and P=0.012, respectively. Conclusion: Most oral manifestations were those strongly associated with HIV infection (91%. Timely diagnosis and treatment of oral manifestations in HIV patients should be considered in conjunction with other treatments.

Gender effects in gaming research: a case for regression residuals?

Science.gov (United States)

Pfister, Roland

2011-10-01

Numerous recent studies have examined the impact of video gaming on various dependent variables, including the players' affective reactions, positive as well as detrimental cognitive effects, and real-world aggression. These target variables are typically analyzed as a function of game characteristics and player attributes-especially gender. However, findings on the uneven distribution of gaming experience between males and females, on the one hand, and the effect of gaming experience on several target variables, on the other hand, point at a possible confound when gaming experiments are analyzed with a standard analysis of variance. This study uses simulated data to exemplify analysis of regression residuals as a potentially beneficial data analysis strategy for such datasets. As the actual impact of gaming experience on each of the various dependent variables differs, the ultimate benefits of analysis of regression residuals entirely depend on the research question, but it offers a powerful statistical approach to video game research whenever gaming experience is a confounding factor.

Logistic regression analysis of prognostic factors in 106 acute-on-chronic liver failure patients with hepatic encephalopathy

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CUI Yanping

2014-10-01

Full Text Available ObjectiveTo analyze the prognostic factors in acute-on-chronic liver failure (ACLF patients with hepatic encephalopathy (HE and to explore the risk factors for prognosis. MethodsA retrospective analysis was performed on 106 ACLF patients with HE who were hospitalized in our hospital from January 2010 to July 2013. The patients were divided into improved group and deteriorated group. The univariate indicators including age, sex, laboratory indicators ［total bilirubin (TBil, albumin (Alb, alanine aminotransferase (ALT, aspartate amino-transferase (AST, and prothrombin time activity (PTA］, the stage of HE, complications ［persistent hyponatremia, digestive tract bleeding, hepatorenal syndrome (HRS, ascites, infection, and spontaneous bacterial peritonitis (SBP］, and plasma exchange were analyzed by chi-square test or t-test. Indicators with statistical significance were subsequently analyzed by binary logistic regression. ResultsUnivariate analysis showed that ALT (P=0.009, PTA (P=0.043, the stage of HE (P=0.000, and HRS (P=0.003 were significantly different between the two groups, whereas differences in age, sex, TBil, Alb, AST, persistent hyponatremia, digestive tract bleeding, ascites, infection, SBP, and plasma exchange were not statistically significant (P＞0.05. Binary logistic regression demonstrated that PTA (b=-0097, P=0.025, OR=0.908, HRS (b=2.279, P=0.007, OR=9.764, and the stage of HE (b=1873, P=0.000, OR=6.510 were prognostic factors in ACLF patients with HE. ConclusionThe stage of HE, HRS, and PTA are independent influential factors for the prognosis in ACLF patients with HE. Reduced PTA, advanced HE stage, and the presence of HRS indicate worse prognosis.

Multiple Linear Regression Analysis of Factors Affecting Real Property Price Index From Case Study Research In Istanbul/Turkey

Science.gov (United States)

Denli, H. H.; Koc, Z.

2015-12-01

Estimation of real properties depending on standards is difficult to apply in time and location. Regression analysis construct mathematical models which describe or explain relationships that may exist between variables. The problem of identifying price differences of properties to obtain a price index can be converted into a regression problem, and standard techniques of regression analysis can be used to estimate the index. Considering regression analysis for real estate valuation, which are presented in real marketing process with its current characteristics and quantifiers, the method will help us to find the effective factors or variables in the formation of the value. In this study, prices of housing for sale in Zeytinburnu, a district in Istanbul, are associated with its characteristics to find a price index, based on information received from a real estate web page. The associated variables used for the analysis are age, size in m2, number of floors having the house, floor number of the estate and number of rooms. The price of the estate represents the dependent variable, whereas the rest are independent variables. Prices from 60 real estates have been used for the analysis. Same price valued locations have been found and plotted on the map and equivalence curves have been drawn identifying the same valued zones as lines.

Predictive Factors for Nonsentinel Lymph Node Metastasis in Patients With Positive Sentinel Lymph Nodes After Neoadjuvant Chemotherapy: Nomogram for Predicting Nonsentinel Lymph Node Metastasis.

Science.gov (United States)

Ryu, Jai Min; Lee, Se Kyung; Kim, Ji Young; Yu, Jonghan; Kim, Seok Won; Lee, Jeong Eon; Han, Se Hwan; Jung, Yong Sik; Nam, Seok Jin

2017-11-01

Axillary lymph node (ALN) status is an important prognostic factor for breast cancer patients. With increasing numbers of patients undergoing neoadjuvant chemotherapy (NAC), issues concerning sentinel lymph node biopsy (SLNB) after NAC have emerged. We analyzed the clinicopathologic features and developed a nomogram to predict the possibility of nonsentinel lymph node (NSLN) metastases in patients with positive SLNs after NAC. A retrospective medical record review was performed of 140 patients who had had clinically positive ALNs at presentation, had a positive SLN after NAC on subsequent SLNB, and undergone axillary lymph node dissection (ALND) from 2008 to 2014. On multivariate stepwise logistic regression analysis, pathologic T stage, lymphovascular invasion, SLN metastasis size, and number of positive SLN metastases were independent predictors for NSLN metastases (P Samsung Medical Center NAC nomogram was developed to predict the likelihood of additional positive NSLNs. The Samsung Medical Center NAC nomogram could provide information to surgeons regarding whether to perform additional ALND when the permanent biopsy revealed positive findings, although the intraoperative SLNB findings were negative. Copyright © 2017 Elsevier Inc. All rights reserved.

The burden of anaemia and associated factors in HIV positive Nigerian women.

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Ezechi, O C; Kalejaiye, O O; Gab-Okafor, C V; Oladele, D A; Oke, B; Ekama, S O; Odunukwe, N N; Ujah, I A O

2013-02-01

Anaemia is the most common complication of pregnancy and a predictor of poor maternal and foetal outcomes. HIV infection is now recognized as one of the major contributors to anaemia in pregnancy. It is therefore important to determine the burden and risk factors of anaemia in maternal HIV infection in others to plan effective prevention strategies as well as optimize management outcomes. To determine the prevalence and risk factors of anaemia in pregnant HIV positive Nigerians. The prevalence and possible risk factors of anaemia were investigated in HIV positive pregnant Nigerian women at a large HIV treatment clinic in southwestern Nigeria using a cross-sectional design between January 2006 and December 2011. Nine hundred and eighty-five (42.5 %) women of 2,318 HIV positive pregnant women seen during the period were anaemic by WHO standard defined by haemoglobin anaemia in HIV positive pregnant women after controlling for confounding variables. Anaemia was found to be high at 42.5 % among the HIV positive women studied and was found to be independently associated with short inter birth interval, presence of OIs, advanced HIV disease and use of zidovudine containing HAART regimen.

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.

Random regression models for detection of gene by environment interaction

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Meuwissen Theo HE

2007-02-01

Full Text Available Abstract Two random regression models, where the effect of a putative QTL was regressed on an environmental gradient, are described. The first model estimates the correlation between intercept and slope of the random regression, while the other model restricts this correlation to 1 or -1, which is expected under a bi-allelic QTL model. The random regression models were compared to a model assuming no gene by environment interactions. The comparison was done with regards to the models ability to detect QTL, to position them accurately and to detect possible QTL by environment interactions. A simulation study based on a granddaughter design was conducted, and QTL were assumed, either by assigning an effect independent of the environment or as a linear function of a simulated environmental gradient. It was concluded that the random regression models were suitable for detection of QTL effects, in the presence and absence of interactions with environmental gradients. Fixing the correlation between intercept and slope of the random regression had a positive effect on power when the QTL effects re-ranked between environments.

Alternative regression models to assess increase in childhood BMI

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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.

Succinate production positively correlates with the affinity of the global transcription factor Cra for its effector FBP in Escherichia coli.

Science.gov (United States)

Wei, Li-Na; Zhu, Li-Wen; Tang, Ya-Jie

2016-01-01

Effector binding is important for transcription factors, affecting both the pattern and function of transcriptional regulation to alter cell phenotype. Our previous work suggested that the affinity of the global transcription factor catabolite repressor/activator (Cra) for its effector fructose-1,6-bisphosphate (FBP) may contribute to succinate biosynthesis. To support this hypothesis, single-point and three-point mutations were proposed through the semi-rational design of Cra to improve its affinity for FBP. For the first time, a positive correlation between succinate production and the affinity of Cra for FBP was revealed in Escherichia coli . Using the best-fit regression function, a cubic equation was used to examine and describe the relationship between succinate production and the affinity of Cra for FBP, demonstrating a significant positive correlation between the two factors (coefficient of determination R 2  = 0.894, P  = 0.000 Cra and DNA showed that Cra bound to the promoter regions of pck and aceB to activate the corresponding genes. Normally, Cra-regulated operons under positive control are deactivated in the presence of FBP. Therefore, theoretically, the enhanced affinity of Cra for FBP will inhibit the activation of pck and aceB . However, the activation of genes involved in CO 2 fixation and the glyoxylate pathway was further improved by the Cra mutant, ultimately contributing to succinate biosynthesis. Enhanced binding of Cra to FBP or active site mutations may eliminate the repressive effect caused by FBP, thus leading to increased activation of genes associated with succinate biosynthesis in the Cra mutant. This work demonstrates an important transcriptional regulation strategy in the metabolic engineering of succinate production and provides useful information for better understanding of the regulatory mechanisms of transcription factors.

Driving factors of retention in care among HIV-positive MSM and transwomen in Indonesia: A cross-sectional study

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Erasmus, Vicki; Coulter, Robert W. S.; Koirala, Sushil; Nampaisan, Oranuch; Pamungkas, Wirastra; Richardus, Jan Hendrik

2018-01-01

Little is known about the prevalence of and factors that influence retention in HIV-related care among Indonesian men who have sex with men (MSM) and transgender women (transwomen, or waria in Indonesian term). Therefore, we explored the driving factors of retention in care among HIV-positive MSM and waria in Indonesia. This cross-sectional study involved 298 self-reported HIV-positive MSM (n = 165) and waria (n = 133). Participants were recruited using targeted sampling and interviewed using a structured questionnaire. We applied a four-step model building process using multivariable logistic regression to examine how sociodemographic, predisposing, enabling, and reinforcing factors were associated with retention in care. Overall, 78.5% of participants were linked to HIV care within 3 months after diagnosis or earlier, and 66.4% were adequately retained in care (at least one health care visit every three months once a person is diagnosed with HIV). Being on antiretroviral therapy (adjusted odds ratio [AOR] = 6.00; 95% confidence interval [CI]: 2.93–12.3), using the Internet to find HIV-related information (AOR = 2.15; 95% CI: 1.00–4.59), and having medical insurance (AOR = 2.84; 95% CI: 1.27–6.34) were associated with adequate retention in care. Involvement with an HIV-related organization was associated negatively with retention in care (AOR = 0.47; 95% CI: 0.24–0.95). Future interventions should increase health insurance coverage and utilize the Internet to help MSM and waria to remain in HIV-related care, thereby assisting them in achieving viral suppression. PMID:29342172

Factors influencing superimposition error of 3D cephalometric landmarks by plane orientation method using 4 reference points: 4 point superimposition error regression model.

Science.gov (United States)

Hwang, Jae Joon; Kim, Kee-Deog; Park, Hyok; Park, Chang Seo; Jeong, Ho-Gul

2014-01-01

Superimposition has been used as a method to evaluate the changes of orthodontic or orthopedic treatment in the dental field. With the introduction of cone beam CT (CBCT), evaluating 3 dimensional changes after treatment became possible by superimposition. 4 point plane orientation is one of the simplest ways to achieve superimposition of 3 dimensional images. To find factors influencing superimposition error of cephalometric landmarks by 4 point plane orientation method and to evaluate the reproducibility of cephalometric landmarks for analyzing superimposition error, 20 patients were analyzed who had normal skeletal and occlusal relationship and took CBCT for diagnosis of temporomandibular disorder. The nasion, sella turcica, basion and midpoint between the left and the right most posterior point of the lesser wing of sphenoidal bone were used to define a three-dimensional (3D) anatomical reference co-ordinate system. Another 15 reference cephalometric points were also determined three times in the same image. Reorientation error of each landmark could be explained substantially (23%) by linear regression model, which consists of 3 factors describing position of each landmark towards reference axes and locating error. 4 point plane orientation system may produce an amount of reorientation error that may vary according to the perpendicular distance between the landmark and the x-axis; the reorientation error also increases as the locating error and shift of reference axes viewed from each landmark increases. Therefore, in order to reduce the reorientation error, accuracy of all landmarks including the reference points is important. Construction of the regression model using reference points of greater precision is required for the clinical application of this model.

Changes of platelet GMP-140 in diabetic nephropathy and its multi-factor regression analysis

International Nuclear Information System (INIS)

Wang Zizheng; Du Tongxin; Wang Shukui

2001-01-01

The relation of platelet GMP-140 and its related factors with diabetic nephropathy was studied. 144 patients of diabetic mellitus without nephropathy (group without DN, mean suffering duration of 25.5 +- 18.6 months); 80 with diabetic nephropathy (group DN, mean suffering duration of 58.7 +- 31.6 months) and 50 normal controls were chosen in the research. Platelet GMP-140, plasma α 1 -MG, β 2 -MG, and 24 hour urine albumin (ALB), IgG, α 1 -MG, β 2 -MG were detected by RIA, while HBA 1 C via chromatographic separation and FBG, PBG, Ch, TG, HDL, FG via biochemical methods. All the data had been processed with software on computer with t-test and linear regression, and multi-factor analysis were done also. The levels of platelet GMP-140, FG, DBP, TG, HBA 1 C and PBG in group DN were significantly higher than those of group without DN and normal control (P 0.05), while they were higher than those of normal controls. Multi-factor analysis of platelet GMP-140 with TG, DBP and HBA 1 C were performed in 80 patients with DN (P 1 C are the independent factors enhancing the activation of platelets. The disturbance of lipid metabolism in type II diabetic mellitus may also enhance the activation of platelets. Elevation of blood pressure may accelerate the initiation and deterioration of DN in which change of platelet GMP-140 is an independent factor. Elevation of HBA 1 C and blood glucose are related closely to the diabetic nephropathy

Positive outcomes influence the rate and time to publication, but not the impact factor of publications of clinical trial results.

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Pilar Suñé

Full Text Available OBJECTIVES: Publication bias may affect the validity of evidence based medical decisions. The aim of this study is to assess whether research outcomes affect the dissemination of clinical trial findings, in terms of rate, time to publication, and impact factor of journal publications. METHODS AND FINDINGS: All drug-evaluating clinical trials submitted to and approved by a general hospital ethics committee between 1997 and 2004 were prospectively followed to analyze their fate and publication. Published articles were identified by searching Pubmed and other electronic databases. Clinical study final reports submitted to the ethics committee, final reports synopses available online and meeting abstracts were also considered as sources of study results. Study outcomes were classified as positive (when statistical significance favoring experimental drug was achieved, negative (when no statistical significance was achieved or it favored control drug and descriptive (for non-controlled studies. Time to publication was defined as time from study closure to publication. A survival analysis was performed using a Cox regression model to analyze time to publication. Journal impact factors of identified publications were recorded. Publication rate was 48·4% (380/785. Study results were identified for 68·9% of all completed clinical trials (541/785. Publication rate was 84·9% (180/212 for studies with results classified as positive and 68·9% (128/186 for studies with results classified as negative (p<0·001. Median time to publication was 2·09 years (IC95 1·61-2·56 for studies with results classified as positive and 3·21 years (IC95 2·69-3·70 for studies with results classified as negative (hazard ratio 1·99 (IC95 1·55-2·55. No differences were found in publication impact factor between positive (median 6·308, interquartile range: 3·141-28·409 and negative result studies (median 8·266, interquartile range: 4·135-17·157. CONCLUSIONS

Are familial factors underlying the association between socioeconomic position and prescription medicine?

DEFF Research Database (Denmark)

Madsen, Mia; Andersen, Per Kragh; Gerster, Mette

2013-01-01

OBJECTIVES: Although well established, the association between socioeconomic position and health and health behaviour is not clearly understood, and it has been speculated that familial factors, for example, dispositional factors or exposures in the rearing environment, may be underlying the asso......OBJECTIVES: Although well established, the association between socioeconomic position and health and health behaviour is not clearly understood, and it has been speculated that familial factors, for example, dispositional factors or exposures in the rearing environment, may be underlying...... and the Danish Registry of Medicinal Product statistics. A total of 8582 monozygotic (MZ) and 15 788 dizygotic same sex (DZSS) twins were included. OUTCOME MEASURES: Number of prescription fillings during follow-up (1995-2005) was analysed according to education and income. Results of unpaired and intrapair...

Key factors contributing to accident severity rate in construction industry in Iran: a regression modelling approach.

Science.gov (United States)

Soltanzadeh, Ahmad; Mohammadfam, Iraj; Moghimbeigi, Abbas; Ghiasvand, Reza

2016-03-01

Construction industry involves the highest risk of occupational accidents and bodily injuries, which range from mild to very severe. The aim of this cross-sectional study was to identify the factors associated with accident severity rate (ASR) in the largest Iranian construction companies based on data about 500 occupational accidents recorded from 2009 to 2013. We also gathered data on safety and health risk management and training systems. Data were analysed using Pearson's chi-squared coefficient and multiple regression analysis. Median ASR (and the interquartile range) was 107.50 (57.24- 381.25). Fourteen of the 24 studied factors stood out as most affecting construction accident severity (p<0.05). These findings can be applied in the design and implementation of a comprehensive safety and health risk management system to reduce ASR.

Positive predictors of quality of life for postpartum mothers with a history of childhood maltreatment.

Science.gov (United States)

Irwin, Jessica L; Beeghly, Marjorie; Rosenblum, Katherine L; Muzik, Maria

2016-12-01

The postpartum period brings a host of biopsychosocial, familial, and economic changes, which may be challenging for new mothers, especially those with trauma histories. Trauma-exposed women are at heightened risk for psychiatric symptomatology and reduced quality of life. The current study sought to evaluate whether a set of hypothesized promotive factors assessed during the first 18 months postpartum (positive parenting, family cohesion, and maternal resilience) are associated with life satisfaction in this population, after controlling for income and postpartum psychiatric symptoms. Analyses were based on data collected for 266 mother-infant dyads from a longitudinal cohort study, Maternal Anxiety during the Childbearing Years (MACY), of women oversampled for childhood maltreatment history. Hierarchical linear regression was used to evaluate the study hypotheses. Consistent with prior work, greater postpartum psychiatric symptoms and less income predicted poor perceptions of life quality. In hierarchical regressions controlling for income and psychiatric symptoms, positive parenting and family cohesion predicted unique variance in mothers' positive perceptions of life quality, and resilience was predictive beyond all other factors. Factors from multiple levels of analysis (maternal, dyadic, and familial) may serve as promotive factors predicting positive perceptions of life quality among women with childhood trauma histories, even those struggling with high levels of psychiatric or economic distress.

Positioning patient-perceived medical services to develop a marketing strategy.

Science.gov (United States)

Jung, Minsoo; Hong, Myung-Sun

2012-01-01

In today's medical market, marketing philosophy is being rapidly transformed from customer searching to patient satisfaction and service improvement. The principal objective of this study was to contribute to the establishment of a desirable medical marketing strategy, through the factors of customer satisfaction and the positioning of patients' perceptions by marketing institutions. The data were collected from 282 students of the College of Public Health and Medicine in Seoul. The survey tools were developed using the SERVQUAL scale. Analysis in this study involved both statistical and network analysis. The former was used to verify the determinants of service satisfaction as perceived by respondents, via factor analysis and multiple regression analysis. The latter was obtained using a positioning map and 2-mode network analysis with the matrix data converted from raw data. The determining factors for patient satisfaction were identified as facilities, accessibility, process, physicians, and medical staff. The regression equation was significant (R = 0.606), and the most influential variable was the service quality of physicians (β = .569). According to multidimensional scaling, the positioning of medical institutions indicated that patients' perceptions were affected by hospital size and specialization. By recognizing and managing patient satisfaction, medical institutions are able to foster customer loyalty and, in turn, to enhance service quality. It is necessary to develop an adequate marketing mix to provide better medical services and to overcome medical competition among institutions.

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.

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).

The risk factors of acute attack of benign paroxysmal positional vertigo

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Rabiei Sohrab

2010-04-01

Full Text Available ntroduction: Many people suffer from vertigo. Its origin in 85% of cases is otological while in 15% is central etiology. Benign paroxysmal positional vertigo (BPPV is the most common cause of the true vertigo. In this research we evaluated the risk factors of acute attack of BPPV. Materials and Methods: This study was performed on 322 patients, presenting with BPPV. Diagnosis was confirmed by history and Dix-Hallpike manoeuvre. The underling risk factors documented carefully. Data analyzed by SPSS and K.square test. Results: Number of 321 patients (including 201 females and 120 males with BPPV included in our study. Their average age was 41. They showed symptoms for 1 month to 15 years (mean 8 months. Emotional stress was positive in 34% and trauma was the only risk factor in 8.12% patients. Ear surgery and prolonged journey were respectively the main risk factors in 7.2 and 12.8% of patients. Conclusion: The confirmed risk factors of acute attack of BPPV were as trauma, major surgery and ear surgery especially stapedotomy, vestibular  neuronitis and prolonged bedrestriction. Meniere was not considered as risk factor. In our study the psychological conflict was the major risk factor for BPPV. Other new risk factors which introduced for first time included; sleep disorder, fatigue, professional sport, starving and prolonged journey.

Response and binding elements for ligand-dependent positive transcription factors integrate positive and negative regulation of gene expression

International Nuclear Information System (INIS)

Rosenfeld, M.G.; Glass, C.K.; Adler, S.; Crenshaw, E.B. III; He, X.; Lira, S.A.; Elsholtz, H.P.; Mangalam, H.J.; Holloway, J.M.; Nelson, C.; Albert, V.R.; Ingraham, H.A.

1988-01-01

Accurate, regulated initiation of mRNA transcription by RNA polymerase II is dependent on the actions of a variety of positive and negative trans-acting factors that bind cis-acting promoter and enhancer elements. These transcription factors may exert their actions in a tissue-specific manner or function under control of plasma membrane or intracellular ligand-dependent receptors. A major goal in the authors' laboratory has been to identify the molecular mechanisms responsible for the serial activation of hormone-encoding genes in the pituitary during development and the positive and negative regulation of their transcription. The anterior pituitary gland contains phenotypically distinct cell types, each of which expresses unique trophic hormones: adrenocorticotropic hormone, thyroid-stimulating hormone, prolactin, growth hormone, and follicle-stimulating hormone/luteinizing hormone. The structurally related prolactin and growth hormone genes are expressed in lactotrophs and somatotrophs, respectively, with their expression virtually limited to the pituitary gland. The reported transient coexpression of these two structurally related neuroendocrine genes raises the possibility that the prolactin and growth hormone genes are developmentally controlled by a common factor(s)

The High Five: Associations of the Five Positive Factors with the Big Five and Well-being

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Alejandro C. Cosentino

2017-07-01

Full Text Available The study of individual differences in positive characteristics has mainly focused on moral traits. The objectives of this research were to study individual differences in positive characteristics from the point of view of the layperson, including non-moral individual characteristics, and to generate a replicable model of positive factors. Three studies based on a lexical approach were conducted. The first study generated a corpus of words which resulted in a refined list of socially shared positive characteristics. The second study produced a five-factor model of positive characteristics: erudition, peace, cheerfulness, honesty, and tenacity. The third study confirmed the model with a different sample. The five-positive-factor model not only showed positive associations with emotional, psychological and social well-being, but it also accounted for the variance beyond that accounted for by the Big Five factors in predicting these well-being dimensions. In addition, the presence of convergent and divergent validity of the five positive factors is shown with relation to the Values-in-Action (VIA classification of character strengths proposed by Peterson and Seligman (2004.

Factors Associated with Treatment Failure among Smear Positive TB Patients in Khorasan-e-Razavi and Sistan-Baluchistan Provinces, Iran

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Hekmatollah Khoubfekr, Narges Khanjani, Yunes Jahani, Mahmoud Moosazadeh

2016-12-01

Full Text Available Introduction: Tuberculosis (TB treatment failure is one of the major problems of the health sector in developing countries. Poor treatment of patients leads to drug resistance, relapse, death, and ultimately prevents TB control programs. This study was conducted to determine the factors affecting tuberculosis treatment failure in Khorasan and Sistan- Balochistan regions which have a high prevalence of TB. Methods: In this case - control study 270 patients with tuberculosis (90 cases, 180 controls were analyzed. New TB patients registered with failure to treatment according to the national protocol between March 2008 - March 2012 were chosen as cases and new TB patients with negative sputum smear in the same time frame were enrolled as control group. Demographic data and clinical treatment outcomes were collected through interviews and file records. Multivariate logistic regression analysis was used to determine the predictors of treatment failure in SPSS 19. Results: Independent factors and predictors of failure treatment included illiteracy, a three plus positive sputum smear, positive sputum smear at end of the second month, non-implementation of the Directly Observed Treatment Short strategy by healthcare staff, history of addiction and history of diabetes. Conclusion: Intervention programs for early detection and control of diabetes, drug control programs, giving priority to providing DOTS by health care workers, more individual care and attention to patients with initial smear p + 3 or those that remain sputum positive at the end of the second month or those who are less educated is necessary. J Microbiol Infect Dis 2016;6(4: 172-178

Cardiovascular risk and bipolar disorder: factors associated with a positive coronary calcium score in patients with bipolar disorder type 1

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Aline R. Wageck

2017-10-01

Full Text Available Objective: Cardiovascular disease is the leading cause of death in patients with bipolar disorder. The aim of this study was to evaluate the factors associated with positive coronary calcium score (CCS in individuals with bipolar disorder type 1. Methods: Patients from the Bipolar Disorder Program at Hospital de Clínicas de Porto Alegre, Brazil, underwent computed tomography scanning for calcium score measurement. Clinical and sociodemographic variables were compared between patients according to their CCS status: negative (CCS = 0 or positive (CCS > 0. Poisson regression analysis was used to examine the association of CCS with number of psychiatric hospitalizations. Results: Out of 41 patients evaluated, only 10 had a positive CCS. Individuals in the CCS-positive group were older (55.2±4.2 vs. 43.1±10.0 years; p = 0.001 and had more psychiatric hospitalizations (4.7±3.0 vs. 2.6±2.5; p = 0.04 when compared with CCS- negative subjects. The number of previous psychiatric hospitalizations correlated positively with CCS (p < 0.001. Conclusion: Age and number of psychiatric hospitalizations were significantly associated with higher CCS, which might be a potential method for diagnosis and stratification of cardiovascular disease in bipolar patients. There is a need for increased awareness of risk assessment in this population.

Infant feeding methods among HIV-positive mothers in Yei County ...

African Journals Online (AJOL)

2016-08-03

Aug 3, 2016 ... a mother is HIV-positive, exclusive replacement feeding. (e.g. with infant formula) is usually recommended provided it is affordable and safe. This is often not ... logistic regression model was used and odds ratio obtained for the factors that have significant association with choice of exclusive breast feeding, ...

On directional multiple-output quantile regression

Czech Academy of Sciences Publication Activity Database

Paindaveine, D.; Šiman, Miroslav

2011-01-01

Roč. 102, č. 2 (2011), s. 193-212 ISSN 0047-259X R&D Projects: GA MŠk(CZ) 1M06047 Grant - others:Commision EC(BE) Fonds National de la Recherche Scientifique Institutional research plan: CEZ:AV0Z10750506 Keywords : multivariate quantile * quantile regression * multiple-output regression * halfspace depth * portfolio optimization * value-at risk Subject RIV: BA - General Mathematics Impact factor: 0.879, year: 2011 http://library.utia.cas.cz/separaty/2011/SI/siman-0364128.pdf

On weighted and locally polynomial directional quantile regression

Czech Academy of Sciences Publication Activity Database

Boček, Pavel; Šiman, Miroslav

2017-01-01

Roč. 32, č. 3 (2017), s. 929-946 ISSN 0943-4062 R&D Projects: GA ČR GA14-07234S Institutional support: RVO:67985556 Keywords : Quantile regression * Nonparametric regression * Nonparametric regression Subject RIV: IN - Informatics, Computer Science OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.434, year: 2016 http://library.utia.cas.cz/separaty/2017/SI/bocek-0458380.pdf

A Bayesian goodness of fit test and semiparametric generalization of logistic regression with measurement data.

Science.gov (United States)

Schörgendorfer, Angela; Branscum, Adam J; Hanson, Timothy E

2013-06-01

Logistic regression is a popular tool for risk analysis in medical and population health science. With continuous response data, it is common to create a dichotomous outcome for logistic regression analysis by specifying a threshold for positivity. Fitting a linear regression to the nondichotomized response variable assuming a logistic sampling model for the data has been empirically shown to yield more efficient estimates of odds ratios than ordinary logistic regression of the dichotomized endpoint. We illustrate that risk inference is not robust to departures from the parametric logistic distribution. Moreover, the model assumption of proportional odds is generally not satisfied when the condition of a logistic distribution for the data is violated, leading to biased inference from a parametric logistic analysis. We develop novel Bayesian semiparametric methodology for testing goodness of fit of parametric logistic regression with continuous measurement data. The testing procedures hold for any cutoff threshold and our approach simultaneously provides the ability to perform semiparametric risk estimation. Bayes factors are calculated using the Savage-Dickey ratio for testing the null hypothesis of logistic regression versus a semiparametric generalization. We propose a fully Bayesian and a computationally efficient empirical Bayesian approach to testing, and we present methods for semiparametric estimation of risks, relative risks, and odds ratios when parametric logistic regression fails. Theoretical results establish the consistency of the empirical Bayes test. Results from simulated data show that the proposed approach provides accurate inference irrespective of whether parametric assumptions hold or not. Evaluation of risk factors for obesity shows that different inferences are derived from an analysis of a real data set when deviations from a logistic distribution are permissible in a flexible semiparametric framework. © 2013, The International Biometric

Multi-step polynomial regression method to model and forecast malaria incidence.

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Chandrajit Chatterjee

Full Text Available Malaria is one of the most severe problems faced by the world even today. Understanding the causative factors such as age, sex, social factors, environmental variability etc. as well as underlying transmission dynamics of the disease is important for epidemiological research on malaria and its eradication. Thus, development of suitable modeling approach and methodology, based on the available data on the incidence of the disease and other related factors is of utmost importance. In this study, we developed a simple non-linear regression methodology in modeling and forecasting malaria incidence in Chennai city, India, and predicted future disease incidence with high confidence level. We considered three types of data to develop the regression methodology: a longer time series data of Slide Positivity Rates (SPR of malaria; a smaller time series data (deaths due to Plasmodium vivax of one year; and spatial data (zonal distribution of P. vivax deaths for the city along with the climatic factors, population and previous incidence of the disease. We performed variable selection by simple correlation study, identification of the initial relationship between variables through non-linear curve fitting and used multi-step methods for induction of variables in the non-linear regression analysis along with applied Gauss-Markov models, and ANOVA for testing the prediction, validity and constructing the confidence intervals. The results execute the applicability of our method for different types of data, the autoregressive nature of forecasting, and show high prediction power for both SPR and P. vivax deaths, where the one-lag SPR values plays an influential role and proves useful for better prediction. Different climatic factors are identified as playing crucial role on shaping the disease curve. Further, disease incidence at zonal level and the effect of causative factors on different zonal clusters indicate the pattern of malaria prevalence in the city

Modeling the factors that influence knowledge transfer in mergers and acquisitions

Institute of Scientific and Technical Information of China (English)

YU Haiyan; LIANG Zhanping

2010-01-01

This paper constructs a model on the factors that influence knowledge transfer in mergers and acquisitions (M&A) and validates it via questionnaire surveys.Using 125 valid collected questionnaires,multiple linear regression analysis and hierarchical regression analysis showed that five out of the ten factors had a positive effect on knowledge transfer effect.The ranking of factor importance,from high to low,was knowledge explicitness,relationship quality,learning intent,advanced transfer activities,and learning capability,which is fairly consistent with positive factors observed in other interorganizational knowledge transfer researches.Our results also showed that one of the control variables (size of acquired firm) had neither a direct or indirect effect on knowledge transfer in M&A.Additionally,our research found that knowledge distance and degree of M&A integration had a positive influence on knowledge transfer effect at the early stage after M&A,but had a negative influence at the late stage.Based on this research,several suggestions for knowledge transfer in M&A are proposed.

Modeling the factors that influence knowledge transfer in mergers and acquisitions

Institute of Scientific and Technical Information of China (English)

YU; Haiyan; LIANG; Zhanping

2010-01-01

This paper constructs a model on the factors that influence knowledge transfer in mergers and acquisitions(M&A)and validates it via questionnaire surveys.Using 125valid collected questionnaires,multiple linear regression analysis and hierarchical regression analysis showed that five out of the ten factors had a positive effect on knowledge transfer effect.The ranking of factor importance,from high to low,was knowledge explicitness,relationship quality,learning intent,advanced transfer activities,and learning capability,which is fairly consistent with positive factors observed in other interorganizational knowledge transfer researches.Our results also showed that one of the control variables(size of acquired firm)had neither a direct or indirect effect on knowledge transfer in M&A.Additionally,our research found that knowledge distance and degree of M&A integration had a positive influence on knowledge transfer effect at the early stage after M&A,but had a negative influence at the late stage.Based on this research,several suggestions for knowledge transfer in M&A are proposed.

Effective dose in abdominal digital radiography: Patient factor

Energy Technology Data Exchange (ETDEWEB)

Jang, Ji Sung; Koo, Hyun Jung; Park, Jung Hoon; Cho, Young Chul; Do, Kyung Hyun [Dept. of Radiology, and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul(Korea, Republic of); Yang, Hyung Jin [Dept. of Medical Physics, Korea University, Seoul (Korea, Republic of)

2017-08-15

To identify independent patient factors associated with an increased radiation dose, and to evaluate the effect of patient position on the effective dose in abdominal digital radiography. We retrospectively evaluated the effective dose for abdominal digital radiography in 222 patients. The patients were divided into two groups based on the cut-off dose value of 0.311 mSv (the upper third quartile of dose distribution): group A (n = 166) and group B (n = 56). Through logistic regression, independent factors associated with a larger effective dose were identified. The effect of patient position on the effective dose was evaluated using a paired t-test. High body mass index (BMI) (≥ 23 kg/m2), presence of ascites, and spinal metallic instrumentation were significantly associated with a larger effective dose. Multivariate logistic regression analysis revealed that high BMI [odds ratio (OR), 25.201; p < 0.001] and ascites (OR, 25.132; p < 0.001) were significantly associated with a larger effective dose. The effective dose was significantly lesser (22.6%) in the supine position than in the standing position (p < 0.001). High BMI and ascites were independent factors associated with a larger effective dose in abdominal digital radiography. Significant dose reduction in patients with these factors may be achieved by placing the patient in the supine position during abdominal digital radiography.

Correction of X-ray diffraction profiles in linear-type PSPC by position factor

International Nuclear Information System (INIS)

Takahashi, Toshio

1992-01-01

PSPC (Position Sensitive Proportional Counter) makes it possible to obtain one-dimentional diffraction profiles without mechanical scanning. In a linear-type PSPC, the obtained profiles need correcting, because the position factor influences the intensity of the diffracted X-ray beam and the counting rate at each position on PSPC. The distances from the specimen are not the same at the center and at the edge of the detector, and the intensity decreases at the edge because of radiation and absorption. The counting rate varies with the incident angle of the diffracted beam at each position on PSPC. The position factor f i at channel i of the multichannel-analyser is given by f i = cos 4 α i ·exp{-μR(1/cosα i -1)} where R is the distance between the specimen and the center of PSPC, μ is the linear absorption coefficient and α i is the incident angle of the diffracted beam at channel i. The background profiles of silica gel powder were measured with CrKα and CuKα. The parameters of the model function were fitted to the profiles by the non-linear least squares method. The agreement between these parameters and the calculated values shows that the position factor can correct the measured profiles properly. (author)

[Socioeconomic factors conditioning obesity in adults. Evidence based on quantile regression and panel data].

Science.gov (United States)

Temporelli, Karina L; Viego, Valentina N

2016-08-01

Objective To measure the effect of socioeconomic variables on the prevalence of obesity. Factors such as income level, urbanization, incorporation of women into the labor market and access to unhealthy foods are considered in this paper. Method Econometric estimates of the proportion of obese men and women by country were calculated using models based on panel data and quantile regressions, with data from 192 countries for the period 2002-2005.Levels of per capita income, urbanization, income/big mac ratio price and labor indicators for female population were considered as explanatory variables. Results Factors that have influence over obesity in adults differ between men and women; accessibility to fast food is related to male obesity, while the employment mode causes higher rates in women. The underlying socioeconomic factors for obesity are also different depending on the magnitude of this problem in each country; in countries with low prevalence, a greater level of income favor the transition to obesogenic habits, while a higher income level mitigates the problem in those countries with high rates of obesity. Discussion Identifying the socio-economic causes of the significant increase in the prevalence of obesity is essential for the implementation of effective strategies for prevention, since this condition not only affects the quality of life of those who suffer from it but also puts pressure on health systems due to the treatment costs of associated diseases.

EMPIRICAL STUDY OF DIFFERENT FACTORS EFFECTS ON ARTICLES PUBLICATION REGARDING SURVEY INTERVIEWER CHARACTERISTICS USING MULTILEVEL REGRESSION MODEL

Directory of Open Access Journals (Sweden)

Alina MOROŞANU

2013-06-01

Full Text Available The purpose of this research work is to evaluate the effects which some factors could have on articles publication regarding survey interviewer characteristics. For this, the author studied the existing literature from the various fields in which articles on survey interviewer characteristics has been published and which can be found in online articles database. The analysis was performed on 243 articles achieved by researchers in the time period 1949-2012. Using statistical software R and applying multilevel regression model, the results showed that the time period when the studied articles are made and the interaction between the number of authors and the number of pages affect the most their publication in journals with a certain level of impact factor.

Clinic Attendance for Antiretroviral Pills Pick-Up among HIV-Positive People in Nepal: Roles of Perceived Family Support and Associated Factors.

Science.gov (United States)

Ayer, Rakesh; Kikuchi, Kimiyo; Ghimire, Mamata; Shibanuma, Akira; Pant, Madhab Raj; Poudel, Krishna C; Jimba, Masamine

2016-01-01

HIV-positive people's clinic attendance for medication pick-up is critical for successful HIV treatment. However, limited evidence exists on it especially in low-income settings such as Nepal. Moreover, the role of family support in clinic attendance remains under-explored. Therefore, this study was conducted to examine the association between perceived family support and regular clinic attendance and to assess factors associated with regular clinic attendance for antiretroviral pills pick-up among HIV-positive individuals in Nepal. A cross-sectional study was conducted among 423 HIV-positive people in three districts of Nepal. Clinic attendance was assessed retrospectively for the period of 12 months. To assess the factors associated, an interview survey was conducted using a semi-structured questionnaire from July to August, 2015. Multiple logistic regression models were used to assess the factors associated with regular clinic attendance. Of 423 HIV-positive people, only 32.6% attended the clinics regularly. They were more likely to attend them regularly when they received high family support (AOR = 3.98, 95% CI = 2.29, 6.92), participated in support programs (AOR = 1.68, 95% CI = 1.00, 2.82), and had knowledge on the benefits of antiretroviral therapy (AOR = 2.62, 95% CI = 1.15, 5.99). In contrast, they were less likely to attend them regularly when they commuted more than 60 minutes to the clinics (AOR = 0.53, 95% CI = 0.30, 0.93), when they self-rated their health status as being very good (AOR = 0.13, 95% CI = 0.04, 0.44), good (AOR = 0.14, 95% CI = 0.04, 0.46), and fair (AOR = 0.21, 95% CI = 0.06, 0.70). HIV-positive individuals are more likely to attend the clinics regularly when they receive high family support, know the benefits of antiretroviral therapy, and participate in support programs. To improve clinic attendance, family support should be incorporated with HIV care programs in resource limited settings. Service providers should also consider

Clinic Attendance for Antiretroviral Pills Pick-Up among HIV-Positive People in Nepal: Roles of Perceived Family Support and Associated Factors

Science.gov (United States)

Kikuchi, Kimiyo; Ghimire, Mamata; Shibanuma, Akira; Pant, Madhab Raj; Poudel, Krishna C.; Jimba, Masamine

2016-01-01

Introduction HIV-positive people’s clinic attendance for medication pick-up is critical for successful HIV treatment. However, limited evidence exists on it especially in low-income settings such as Nepal. Moreover, the role of family support in clinic attendance remains under-explored. Therefore, this study was conducted to examine the association between perceived family support and regular clinic attendance and to assess factors associated with regular clinic attendance for antiretroviral pills pick-up among HIV-positive individuals in Nepal. Methods A cross-sectional study was conducted among 423 HIV-positive people in three districts of Nepal. Clinic attendance was assessed retrospectively for the period of 12 months. To assess the factors associated, an interview survey was conducted using a semi-structured questionnaire from July to August, 2015. Multiple logistic regression models were used to assess the factors associated with regular clinic attendance. Results Of 423 HIV-positive people, only 32.6% attended the clinics regularly. They were more likely to attend them regularly when they received high family support (AOR = 3.98, 95% CI = 2.29, 6.92), participated in support programs (AOR = 1.68, 95% CI = 1.00, 2.82), and had knowledge on the benefits of antiretroviral therapy (AOR = 2.62, 95% CI = 1.15, 5.99). In contrast, they were less likely to attend them regularly when they commuted more than 60 minutes to the clinics (AOR = 0.53, 95% CI = 0.30, 0.93), when they self-rated their health status as being very good (AOR = 0.13, 95% CI = 0.04, 0.44), good (AOR = 0.14, 95% CI = 0.04, 0.46), and fair (AOR = 0.21, 95% CI = 0.06, 0.70). Conclusion HIV-positive individuals are more likely to attend the clinics regularly when they receive high family support, know the benefits of antiretroviral therapy, and participate in support programs. To improve clinic attendance, family support should be incorporated with HIV care programs in resource limited settings

Regression Models for Repairable Systems

Czech Academy of Sciences Publication Activity Database

Novák, Petr

2015-01-01

Roč. 17, č. 4 (2015), s. 963-972 ISSN 1387-5841 Institutional support: RVO:67985556 Keywords : Reliability analysis * Repair models * Regression Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.782, year: 2015 http://library.utia.cas.cz/separaty/2015/SI/novak-0450902.pdf

Impact of helminth diagnostic test performance on estimation of risk factors and outcomes in HIV-positive adults.

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Michael B Arndt

Full Text Available BACKGROUND: Traditional methods using microscopy for the detection of helminth infections have limited sensitivity. Polymerase chain reaction (PCR assays enhance detection of helminths, particularly low burden infections. However, differences in test performance may modify the ability to detect associations between helminth infection, risk factors, and sequelae. We compared these associations using microscopy and PCR. METHODS: This cross-sectional study was nested within a randomized clinical trial conducted at 3 sites in Kenya. We performed microscopy and real-time multiplex PCR for the stool detection and quantification of Ascaris lumbricoides, Necator americanus, Ancylostoma duodenale, Strongyloides stercoralis, and Schistosoma species. We utilized regression to evaluate associations between potential risk factors or outcomes and infection as detected by either method. RESULTS: Of 153 HIV-positive adults surveyed, 55(36.0% and 20(13.1% were positive for one or more helminth species by PCR and microscopy, respectively (p<0.001. PCR-detected infections were associated with farming (Prevalence Ratio 1.57, 95% CI: 1.02, 2.40, communal water source (PR 3.80, 95% CI: 1.01, 14.27, and no primary education (PR 1.54, 95% CI: 1.14, 2.33, whereas microscopy-detected infections were not associated with any risk factors under investigation. Microscopy-detected infections were associated with significantly lower hematocrit and hemoglobin (means of -3.56% and -0.77 g/dl and a 48% higher risk of anemia (PR 1.48, 95% CI: 1.17, 1.88 compared to uninfected. Such associations were absent for PCR-detected infections unless infection intensity was considered, Infections diagnosed with either method were associated with increased risk of eosinophilia (PCR PR 2.42, 95% CI: 1.02, 5.76; microscopy PR 2.92, 95% CI: 1.29, 6.60. CONCLUSION: Newer diagnostic methods, including PCR, improve the detection of helminth infections. This heightened sensitivity may improve the

Virtual machine consolidation enhancement using hybrid regression algorithms

Directory of Open Access Journals (Sweden)

Amany Abdelsamea

2017-11-01

Full Text Available Cloud computing data centers are growing rapidly in both number and capacity to meet the increasing demands for highly-responsive computing and massive storage. Such data centers consume enormous amounts of electrical energy resulting in high operating costs and carbon dioxide emissions. The reason for this extremely high energy consumption is not just the quantity of computing resources and the power inefficiency of hardware, but rather lies in the inefficient usage of these resources. VM consolidation involves live migration of VMs hence the capability of transferring a VM between physical servers with a close to zero down time. It is an effective way to improve the utilization of resources and increase energy efficiency in cloud data centers. VM consolidation consists of host overload/underload detection, VM selection and VM placement. Most of the current VM consolidation approaches apply either heuristic-based techniques, such as static utilization thresholds, decision-making based on statistical analysis of historical data; or simply periodic adaptation of the VM allocation. Most of those algorithms rely on CPU utilization only for host overload detection. In this paper we propose using hybrid factors to enhance VM consolidation. Specifically we developed a multiple regression algorithm that uses CPU utilization, memory utilization and bandwidth utilization for host overload detection. The proposed algorithm, Multiple Regression Host Overload Detection (MRHOD, significantly reduces energy consumption while ensuring a high level of adherence to Service Level Agreements (SLA since it gives a real indication of host utilization based on three parameters (CPU, Memory, Bandwidth utilizations instead of one parameter only (CPU utilization. Through simulations we show that our approach reduces power consumption by 6 times compared to single factor algorithms using random workload. Also using PlanetLab workload traces we show that MRHOD improves

Improving model predictions for RNA interference activities that use support vector machine regression by combining and filtering features

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Peek Andrew S

2007-06-01

Full Text Available Abstract Background RNA interference (RNAi is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathways. To dissect the factors that result in effective siRNA sequences a regression kernel Support Vector Machine (SVM approach was used to quantitatively model RNA interference activities. Results Eight overall feature mapping methods were compared in their abilities to build SVM regression models that predict published siRNA activities. The primary factors in predictive SVM models are position specific nucleotide compositions. The secondary factors are position independent sequence motifs (N-grams and guide strand to passenger strand sequence thermodynamics. Finally, the factors that are least contributory but are still predictive of efficacy are measures of intramolecular guide strand secondary structure and target strand secondary structure. Of these, the site of the 5' most base of the guide strand is the most informative. Conclusion The capacity of specific feature mapping methods and their ability to build predictive models of RNAi activity suggests a relative biological importance of these features. Some feature mapping methods are more informative in building predictive models and overall t-test filtering provides a method to remove some noisy features or make comparisons among datasets. Together, these features can yield predictive SVM regression models with increased predictive accuracy between predicted and observed activities both within datasets by cross validation, and between independently collected RNAi activity datasets. Feature filtering to remove features should be approached carefully in that it is possible to reduce feature set size without substantially reducing predictive models, but the features retained in the candidate models become increasingly distinct. Software to perform feature prediction and SVM training and testing on nucleic acid

Ridge Regression Signal Processing

Science.gov (United States)

Kuhl, Mark R.

1990-01-01

The introduction of the Global Positioning System (GPS) into the National Airspace System (NAS) necessitates the development of Receiver Autonomous Integrity Monitoring (RAIM) techniques. In order to guarantee a certain level of integrity, a thorough understanding of modern estimation techniques applied to navigational problems is required. The extended Kalman filter (EKF) is derived and analyzed under poor geometry conditions. It was found that the performance of the EKF is difficult to predict, since the EKF is designed for a Gaussian environment. A novel approach is implemented which incorporates ridge regression to explain the behavior of an EKF in the presence of dynamics under poor geometry conditions. The basic principles of ridge regression theory are presented, followed by the derivation of a linearized recursive ridge estimator. Computer simulations are performed to confirm the underlying theory and to provide a comparative analysis of the EKF and the recursive ridge estimator.

Elevated triglycerides and risk of myocardial infarction in HIV-positive persons

DEFF Research Database (Denmark)

Worm, Signe W; Kamara, David Alim; Reiss, Peter

2011-01-01

Objectives: To explore the relationship between elevated triglyceride levels and the risk of myocardial infarction (MI) in HIV-positive persons after adjustment for total cholesterol (TC), high-density lipoprotein–cholesterol (HDL-C) and nonlipid risk factors. Background: Although elevated...... triglyceride levels are commonly noted in HIV-positive individuals, it is unclear whether they represent an independent risk factor for MI. Methods: The incidence of MI during follow-up was stratified according to the latest triglyceride level. Multivariable Poisson regression models were used to describe...... the independent association between the latest triglyceride level and MI risk after adjusting for TC and HDL-C, nonlipids cardiovascular disease (CVD) risk factors, HIV and treatment-related factors. Results: The 33 308 persons included in the study from 1999 to 2008 experienced 580 MIs over 178 835 person...

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

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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

Schistosoma mansoni reinfection: Analysis of risk factors by classification and regression tree (CART modeling.

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Andréa Gazzinelli

Full Text Available Praziquantel (PZQ is an effective chemotherapy for schistosomiasis mansoni and a mainstay for its control and potential elimination. However, it does not prevent against reinfection, which can occur rapidly in areas with active transmission. A guide to ranking the risk factors for Schistosoma mansoni reinfection would greatly contribute to prioritizing resources and focusing prevention and control measures to prevent rapid reinfection. The objective of the current study was to explore the relationship among the socioeconomic, demographic, and epidemiological factors that can influence reinfection by S. mansoni one year after successful treatment with PZQ in school-aged children in Northeastern Minas Gerais state Brazil. Parasitological, socioeconomic, demographic, and water contact information were surveyed in 506 S. mansoni-infected individuals, aged 6 to 15 years, resident in these endemic areas. Eligible individuals were treated with PZQ until they were determined to be negative by the absence of S. mansoni eggs in the feces on two consecutive days of Kato-Katz fecal thick smear. These individuals were surveyed again 12 months from the date of successful treatment with PZQ. A classification and regression tree modeling (CART was then used to explore the relationship between socioeconomic, demographic, and epidemiological variables and their reinfection status. The most important risk factor identified for S. mansoni reinfection was their "heavy" infection at baseline. Additional analyses, excluding heavy infection status, showed that lower socioeconomic status and a lower level of education of the household head were also most important risk factors for S. mansoni reinfection. Our results provide an important contribution toward the control and possible elimination of schistosomiasis by identifying three major risk factors that can be used for targeted treatment and monitoring of reinfection. We suggest that control measures that target

Introduction to the use of regression models in epidemiology.

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Bender, Ralf

2009-01-01

Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.

Experimental Exploration of RSSI Model for the Vehicle Intelligent Position System

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Zhichao Cao

2015-01-01

Full Text Available Vehicle intelligent position systems based on Received Signal Strength Indicator (RSSI in Wireless Sensor Networks (WSNs are efficiently utilized. The vehicle’s position accuracy is of great importance for transportation behaviors, such as dynamic vehicle routing problems and multiple pedestrian routing choice behaviors and so on. Therefore, a precise position and available optimization is necessary for total parameters of conventional RSSI model. In this papar, we investigate the experimental performance of translating the power measurements to corresponding distance between each pair of nodes. The priori knowledge about the environment interference could impact the accuracy of vehicles’s position and the reliability of paremeters greatly. Based on the real-world outdoor experiments, we compares different regression analysis of the RSSI model, in order to establish a calibration scheme on RSSI model. We showed that the average error of RSSI model is able to decrease throughout the rules of environmental factor n and shadowing factor ? respectively. Moreover, the calculation complexity is reduced. Since variation tendency of environmental factor n, shadowing factor ? with distance and signal strength could be simulated respectively, RSSI model fulfills the precision of the vehicle intelligent position system.

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...

Elliptical multiple-output quantile regression and convex optimization

Czech Academy of Sciences Publication Activity Database

Hallin, M.; Šiman, Miroslav

2016-01-01

Roč. 109, č. 1 (2016), s. 232-237 ISSN 0167-7152 R&D Projects: GA ČR GA14-07234S Institutional support: RVO:67985556 Keywords : quantile regression * elliptical quantile * multivariate quantile * multiple-output regression Subject RIV: BA - General Mathematics Impact factor: 0.540, year: 2016 http://library.utia.cas.cz/separaty/2016/SI/siman-0458243.pdf

Predictive factors in patients eligible for pegfilgrastim prophylaxis focusing on RDI using ordered logistic regression analysis.

Science.gov (United States)

Kanbayashi, Yuko; Ishikawa, Takeshi; Kanazawa, Motohiro; Nakajima, Yuki; Kawano, Rumi; Tabuchi, Yusuke; Yoshioka, Tomoko; Ihara, Norihiko; Hosokawa, Toyoshi; Takayama, Koichi; Shikata, Keisuke; Taguchi, Tetsuya

2018-03-16

Although pegfilgrastim prophylaxis is expected to maintain the relative dose intensity (RDI) of chemotherapy and improve safety, information is limited. However, the optimal selection of patients eligible for pegfilgrastim prophylaxis is an important issue from a medical economics viewpoint. Therefore, this retrospective study identified factors that could predict these eligible patients to maintain the RDI. The participants included 166 cancer patients undergoing pegfilgrastim prophylaxis combined with chemotherapy in our outpatient chemotherapy center between March 2015 and April 2017. Variables were extracted from clinical records for regression analysis of factors related to maintenance of the RDI. RDI was classified into four categories: 100% = 0, 85% or predictive factors in patients eligible for pegfilgrastim prophylaxis to maintain the RDI. Threshold measures were examined using a receiver operating characteristic (ROC) analysis curve. Age [odds ratio (OR) 1.07, 95% confidence interval (CI) 1.04-1.11; P maintenance. ROC curve analysis of the group that failed to maintain the RDI indicated that the threshold for age was 70 years and above, with a sensitivity of 60.0% and specificity of 80.2% (area under the curve: 0.74). In conclusion, younger age, anemia (less), and administration of pegfilgrastim 24-72 h after chemotherapy were significant factors for RDI maintenance.

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

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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.

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

Risk factors for violence in psychosis: systematic review and meta-regression analysis of 110 studies.

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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

Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaging-genetic applications.

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Tao, Chenyang; Nichols, Thomas E; Hua, Xue; Ching, Christopher R K; Rolls, Edmund T; Thompson, Paul M; Feng, Jianfeng

2017-01-01

We propose a generalized reduced rank latent factor regression model (GRRLF) for the analysis of tensor field responses and high dimensional covariates. The model is motivated by the need from imaging-genetic studies to identify genetic variants that are associated with brain imaging phenotypes, often in the form of high dimensional tensor fields. GRRLF identifies from the structure in the data the effective dimensionality of the data, and then jointly performs dimension reduction of the covariates, dynamic identification of latent factors, and nonparametric estimation of both covariate and latent response fields. After accounting for the latent and covariate effects, GRLLF performs a nonparametric test on the remaining factor of interest. GRRLF provides a better factorization of the signals compared with common solutions, and is less susceptible to overfitting because it exploits the effective dimensionality. The generality and the flexibility of GRRLF also allow various statistical models to be handled in a unified framework and solutions can be efficiently computed. Within the field of neuroimaging, it improves the sensitivity for weak signals and is a promising alternative to existing approaches. The operation of the framework is demonstrated with both synthetic datasets and a real-world neuroimaging example in which the effects of a set of genes on the structure of the brain at the voxel level were measured, and the results compared favorably with those from existing approaches. Copyright © 2016. Published by Elsevier Inc.

Prevalence and correlates of positive mental health in Chinese adolescents.

Science.gov (United States)

Guo, Cheng; Tomson, Göran; Keller, Christina; Söderqvist, Fredrik

2018-02-17

Studies investigating the prevalence of positive mental health and its correlates are still scarce compared to the studies on mental disorders, although there is growing interest of assessing positive mental health in adolescents. So far, no other study examining the prevalence and determinants of positive mental health in Chinese adolescents has been found. The purpose of this study was to assess the prevalence and correlates of positive mental health in Chinese adolescents. This cross-sectional study used a questionnaire including Mental Health Continuum-Short Form (MHC-SF) and items regarding multiple aspects of adolescent life. The sample involved a total of 5399 students from grade 8 and 10 in Weifang, China. Multivariate Logistic regression analyses were performed to evaluate the associations between potential indicators regarding socio-economic situations, life style, social support and school life and positive mental health and calculate odds ratios and 95% confidence intervals. More than half (57.4%) of the participants were diagnosed as flourishing. The correlated factors of positive mental health in regression models included gender, perceived family economy, the occurrence of sibling(s), satisfaction of self-appearance, physical activity, sleep quality, stress, social trust, desire to learn, support from teachers and parents as well as whether being bullied at school (OR ranging from 1.23 to 2.75). The Hosmer-Lemeshow p-value for the final regression model (0.45) indicated adequate model fit. This study gives the first overview on prevalence and correlates of positive mental health in Chinese adolescents. The prevalence of positive mental health in Chinese adolescents is higher than reported in most of the previous studies also using MHC-SF. Our findings suggest that adolescents with advantageous socio-economic situations, life style, social support and school life are experiencing better positive mental health than others.

Estimating Loess Plateau Average Annual Precipitation with Multiple Linear Regression Kriging and Geographically Weighted Regression Kriging

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Qiutong Jin

2016-06-01

Full Text Available Estimating the spatial distribution of precipitation is an important and challenging task in hydrology, climatology, ecology, and environmental science. In order to generate a highly accurate distribution map of average annual precipitation for the Loess Plateau in China, multiple linear regression Kriging (MLRK and geographically weighted regression Kriging (GWRK methods were employed using precipitation data from the period 1980–2010 from 435 meteorological stations. The predictors in regression Kriging were selected by stepwise regression analysis from many auxiliary environmental factors, such as elevation (DEM, normalized difference vegetation index (NDVI, solar radiation, slope, and aspect. All predictor distribution maps had a 500 m spatial resolution. Validation precipitation data from 130 hydrometeorological stations were used to assess the prediction accuracies of the MLRK and GWRK approaches. Results showed that both prediction maps with a 500 m spatial resolution interpolated by MLRK and GWRK had a high accuracy and captured detailed spatial distribution data; however, MLRK produced a lower prediction error and a higher variance explanation than GWRK, although the differences were small, in contrast to conclusions from similar studies.

Positional dependence of the SNPP VIIRS SD BRDF degradation factor

Science.gov (United States)

Lei, Ning; Chen, Xuexia; Chang, Tiejun; Xiong, Xiaoxiong

2017-09-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite is a passive scanning radiometer and an imager. The VIIRS regularly performs on-orbit radiometric calibration of its reflective solar bands (RSBs) through observing an onboard sunlit solar diffuser (SD). The reflectance of the SD changes over time and the change is denoted as the SD bidirectional reflectance distribution function degradation factor. The degradation factor, measured by an onboard solar diffuser stability monitor, has been shown to be both incident sunlight and outgoing direction dependent. In this Proceeding, we investigate the factor's dependence on SD position. We develop a model to relate the SD degradation factor with the amount of solar exposure. We use Earth measurements to evaluate the effectiveness of the model.

Risk factors for cervical cancer among HPV positive women in Mexico Factores de riesgo de cáncer cervical en mujeres VPH positivas en México

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Yvonne N Flores

2008-02-01

Full Text Available OBJECTIVE: To identify factors that are associated with an increased risk of developing high-grade cervical intraepithelial neoplasia (CIN or cancer among human papillomavirus (HPV-positive women in Mexico. MATERIAL AND METHODS: A case-control study design was used. A total of 94 cases and 501 controls who met the study inclusion criteria were selected from the 7 732 women who participated in the Morelos HPV Study from May 1999 to June 2000. Risk factor information was obtained from interviews and from HPV viral load results. Odds ratios and 95 percent confidence intervals were estimated using unconditional multivariate regression. RESULTS: Increasing age, high viral load, a young age at first sexual intercourse, and a low socio-economic status are associated with an increased risk of disease among HPV-positive women. CONCLUSIONS: These results could have important implications for future screening activities in Mexico and other low resource countries.OBJETIVO: Identificar factores asociados con un mayor riesgo de desarrollar neoplasia intraepitelial cervical (NIC de alto grado o cáncer en mujeres con virus de papiloma humano (VPH, en México. MATERIAL Y MÉTODOS: Se utilizó un diseño de casos y controles. Un total de 94 casos y 501 controles fueron seleccionados de las 7 732 mujeres que participaron en el Estudio de VPH en Morelos, de mayo de 1999 a junio de 2000. La información sobre factores de riesgo se obtuvo de entrevistas y de los resultados de carga virales de VPH. Se estimaron razones de momios e intervalos de confianza de 95% con modelos multivariados de regresión no condicionada. RESULTADOS: El incremento de edad, la carga viral elevada, la edad temprana al inicio de la vida sexual y el nivel socioeconómico bajo se asocian con un mayor riesgo de enfermedad en mujeres VPH positivas. CONCLUSIONES: Estos resultados podrían tener implicaciones importantes a futuro para las actividades de tamizaje en México y en otros países de

Which sociodemographic factors are important on smoking behaviour of high school students? The contribution of classification and regression tree methodology in a broad epidemiological survey.

Science.gov (United States)

Ozge, C; Toros, F; Bayramkaya, E; Camdeviren, H; Sasmaz, T

2006-08-01

The purpose of this study is to evaluate the most important sociodemographic factors on smoking status of high school students using a broad randomised epidemiological survey. Using in-class, self administered questionnaire about their sociodemographic variables and smoking behaviour, a representative sample of total 3304 students of preparatory, 9th, 10th, and 11th grades, from 22 randomly selected schools of Mersin, were evaluated and discriminative factors have been determined using appropriate statistics. In addition to binary logistic regression analysis, the study evaluated combined effects of these factors using classification and regression tree methodology, as a new statistical method. The data showed that 38% of the students reported lifetime smoking and 16.9% of them reported current smoking with a male predominancy and increasing prevalence by age. Second hand smoking was reported at a 74.3% frequency with father predominance (56.6%). The significantly important factors that affect current smoking in these age groups were increased by household size, late birth rank, certain school types, low academic performance, increased second hand smoking, and stress (especially reported as separation from a close friend or because of violence at home). Classification and regression tree methodology showed the importance of some neglected sociodemographic factors with a good classification capacity. It was concluded that, as closely related with sociocultural factors, smoking was a common problem in this young population, generating important academic and social burden in youth life and with increasing data about this behaviour and using new statistical methods, effective coping strategies could be composed.

[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.

Tightness of M-estimators for multiple linear regression in time series

DEFF Research Database (Denmark)

Johansen, Søren; Nielsen, Bent

We show tightness of a general M-estimator for multiple linear regression in time series. The positive criterion function for the M-estimator is assumed lower semi-continuous and sufficiently large for large argument: Particular cases are the Huber-skip and quantile regression. Tightness requires...

Imaging-guided percutaneous needle biopsy for infectious spondylitis: Factors affecting culture positivity

Energy Technology Data Exchange (ETDEWEB)

Sung, Si Yoon; Kwon, Jong Won [Dept. of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of)

2015-11-15

To evaluate the variable factors affecting the results of percutaneous needle biopsies for infectious spondylitis. In all, 249 patients who underwent both MRI and percutaneous needle biopsies due to a suspicion of infectious spondylitis were evaluated with respect to the following factors: the usage of antibiotics before the procedure, the location of the biopsy, the guiding equipment used, the experience level of the operators, and the number of biopsies performed. The positivity of culture in cases of treated with antibiotics (16.3%) before the biopsy was lower than in the untreated cases (30.5%) (p = 0.004). Biopsies performed at the abscess (43.5%) and with fluoroscopic guidance (27.8%) showed higher culture positivity as well. The experience level of the operators and the number of biopsies had no effect on culture positivity. The usage of antibiotics before the biopsy, the biopsy's location, and the guiding equipment used affect the culture positivity, while the experience levels of the operators and the number of biopsies do not have an effect.

Imaging-guided percutaneous needle biopsy for infectious spondylitis: Factors affecting culture positivity

International Nuclear Information System (INIS)

Sung, Si Yoon; Kwon, Jong Won

2015-01-01

To evaluate the variable factors affecting the results of percutaneous needle biopsies for infectious spondylitis. In all, 249 patients who underwent both MRI and percutaneous needle biopsies due to a suspicion of infectious spondylitis were evaluated with respect to the following factors: the usage of antibiotics before the procedure, the location of the biopsy, the guiding equipment used, the experience level of the operators, and the number of biopsies performed. The positivity of culture in cases of treated with antibiotics (16.3%) before the biopsy was lower than in the untreated cases (30.5%) (p = 0.004). Biopsies performed at the abscess (43.5%) and with fluoroscopic guidance (27.8%) showed higher culture positivity as well. The experience level of the operators and the number of biopsies had no effect on culture positivity. The usage of antibiotics before the biopsy, the biopsy's location, and the guiding equipment used affect the culture positivity, while the experience levels of the operators and the number of biopsies do not have an effect

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.

Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

Science.gov (United States)

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

2018-03-01

Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

Science.gov (United States)

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

2017-01-01

Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

Analysis of Factors Influencing Labour Supplied to Non-Farm Sub ...

African Journals Online (AJOL)

acer

regression analysis reveal that educational level had negative coefficient, while occupation had positive coefficient ... component of the rural economy, its role in ... economic factors influencing labour ... Textbooks, Government publications,.

Human chorionic gonadotrophin regression rate as a predictive factor of postmolar gestational trophoblastic neoplasm in high-risk hydatidiform mole: a case-control study.

Science.gov (United States)

Kim, Bo Wook; Cho, Hanbyoul; Kim, Hyunki; Nam, Eun Ji; Kim, Sang Wun; Kim, Sunghoon; Kim, Young Tae; Kim, Jae-Hoon

2012-01-01

The aim of this study was early prediction of postmolar gestational trophoblastic neoplasm (GTN) after evacuation of high-risk mole, by comparison of human chorionic gonadotrophin (hCG) regression rates. Fifty patients with a high-risk mole initially and spontaneously regressing after molar evacuation were selected from January 1, 1996 to May 31, 2010 (spontaneous regression group). Fifty patients with a high-risk mole initially and progressing to postmolar GTN after molar evacuation were selected (postmolar GTN group). hCG regression rates represented as hCG/initial hCG were compared between the two groups. The sensitivity and specificity of these rates for prediction of postmolar GTN were assessed using receiver operating characteristic curves. Multivariate analyses of associations between risk factors and postmolar GTN progression were performed. The mean regression rate of hCG between the two groups was compared. hCG regression rates represented as hCG/initial hCG (%) were 0.36% in the spontaneous regression group and 1.45% in the postmolar GTN group in the second week (p=0.003). Prediction of postmolar GTN by hCG regression rate revealed a sensitivity of 48.0% and specificity of 89.5% with a cut-off value of 0.716% and area under the curve (AUC) of 0.759 in the 2nd week (pfactor for postmolar GTN. Crown Copyright © 2011. Published by Elsevier Ireland Ltd. All rights reserved.

Real estate value prediction using multivariate regression models

Science.gov (United States)

Manjula, R.; Jain, Shubham; Srivastava, Sharad; Rajiv Kher, Pranav

2017-11-01

The real estate market is one of the most competitive in terms of pricing and the same tends to vary significantly based on a lot of factors, hence it becomes one of the prime fields to apply the concepts of machine learning to optimize and predict the prices with high accuracy. Therefore in this paper, we present various important features to use while predicting housing prices with good accuracy. We have described regression models, using various features to have lower Residual Sum of Squares error. While using features in a regression model some feature engineering is required for better prediction. Often a set of features (multiple regressions) or polynomial regression (applying a various set of powers in the features) is used for making better model fit. For these models are expected to be susceptible towards over fitting ridge regression is used to reduce it. This paper thus directs to the best application of regression models in addition to other techniques to optimize the result.

Positive and Negative Thinking in Tinnitus: Factor Structure of the Tinnitus Cognitions Questionnaire.

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Handscomb, Lucy E; Hall, Deborah A; Shorter, Gillian W; Hoare, Derek J

Researchers and clinicians consider thinking to be important in the development and maintenance of tinnitus distress, and altering thoughts or thinking style is an object of many forms of psychological therapy for tinnitus. Those working with people with tinnitus require a reliable, psychometrically robust means of measuring both positive and negative thinking related to it. The Tinnitus Cognitions Questionnaire (TCQ) was designed as such a measure and its authors showed it to be reliable, with good psychometric properties. However, no research teams have yet carried out independent validation. This study aimed to use the TCQ to investigate thinking amongst members of the general population with both bothersome and nonbothersome tinnitus and also to verify its factor structure. Three hundred forty-two members of the public with tinnitus completed the TCQ online or on paper. They also rated their tinnitus on a scale as "not a problem," "a small problem," "a moderate problem," "a big problem," or a "very big problem." The authors tested the original factor structure of the TCQ using confirmatory factor analysis and then calculated the mean scores for each item, comparing mean total scores across "problem categories" for the full questionnaire and for the positive and negative subscales. The original two-factor structure of the TCQ was a good fit to the data when the correlation between positive and negative factors was fixed at zero (root mean square error of approximation = 0.064, 90% confidence interval = 0.058 to 0.070). Items pertaining to wishing the tinnitus would go away and despairing that it would ever get better had the highest mean scores. The mean total score for the "no problem" group (M = 31.17, SD = 16.03) was not significantly different from the mean total score for the "small problem" group (M = 34.00, SD = 12.44, p = 0.99). Differences between mean scores for all other groups were statistically significant. For the negative subscale, differences

Effects of socioeconomic position and clinical risk factors on spontaneous and iatrogenic preterm birth.

Science.gov (United States)

Joseph, K S; Fahey, John; Shankardass, Ketan; Allen, Victoria M; O'Campo, Patricia; Dodds, Linda; Liston, Robert M; Allen, Alexander C

2014-03-27

The literature shows a variable and inconsistent relationship between socioeconomic position and preterm birth. We examined risk factors for spontaneous and iatrogenic preterm birth, with a focus on socioeconomic position and clinical risk factors, in order to explain the observed inconsistency. We carried out a retrospective population-based cohort study of all singleton deliveries in Nova Scotia from 1988 to 2003. Data were obtained from the Nova Scotia Atlee Perinatal Database and the federal income tax T1 Family Files. Separate logistic models were used to quantify the association between socioeconomic position, clinical risk factors and spontaneous preterm birth and iatrogenic preterm birth. The study population included 132,714 singleton deliveries and the rate of preterm birth was 5.5%. Preterm birth rates were significantly higher among the women in the lowest (versus the highest) family income group for spontaneous (rate ratio 1.14, 95% confidence interval (CI) 1.03, 1.25) but not iatrogenic preterm birth (rate ratio 0.95, 95% CI 0.75, 1.19). Adjustment for maternal characteristics attenuated the family income-spontaneous preterm birth relationship but strengthened the relationship with iatrogenic preterm birth. Clinical risk factors such as hypertension were differentially associated with spontaneous (rate ratio 3.92, 95% CI 3.47, 4.44) and iatrogenic preterm (rate ratio 14.1, 95% CI 11.4, 17.4) but factors such as diabetes mellitus were not (rate ratio 4.38, 95% CI 3.21, 5.99 for spontaneous and 4.02, 95% CI 2.07, 7.80 for iatrogenic preterm birth). Socioeconomic position and clinical risk factors have different effects on spontaneous and iatrogenic preterm. Recent temporal increases in iatrogenic preterm birth appear to be responsible for the inconsistent relationship between socioeconomic position and preterm birth.

Multiple regression and beyond an introduction to multiple regression and structural equation modeling

CERN Document Server

Keith, Timothy Z

2014-01-01

Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. Covers both MR and SEM, while explaining their relevance to one another Also includes path analysis, confirmatory factor analysis, and latent growth modeling Figures and tables throughout provide examples and illustrate key concepts and techniques For additional resources, please visit: http://tzkeith.com/.

Robust median estimator in logisitc regression

Czech Academy of Sciences Publication Activity Database

Hobza, T.; Pardo, L.; Vajda, Igor

2008-01-01

Roč. 138, č. 12 (2008), s. 3822-3840 ISSN 0378-3758 R&D Projects: GA MŠk 1M0572 Grant - others:Instituto Nacional de Estadistica (ES) MPO FI - IM3/136; GA MŠk(CZ) MTM 2006-06872 Institutional research plan: CEZ:AV0Z10750506 Keywords : Logistic regression * Median * Robustness * Consistency and asymptotic normality * Morgenthaler * Bianco and Yohai * Croux and Hasellbroeck Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.679, year: 2008 http://library.utia.cas.cz/separaty/2008/SI/vajda-robust%20median%20estimator%20in%20logistic%20regression.pdf

Potential predictive factors of positive prostate biopsy in the Chinese ...

African Journals Online (AJOL)

Yomi

2012-01-16

Jan 16, 2012 ... Therefore, it might be inappropriate that we apply these western models to the. Chinese population that has a lower incidence of PCa. Therefore, this retrospective study aimed to determine predictive factors for a positive prostate biopsy in Chinese men. Our ultimate goal is to develop a simple model for ...

Studies on correlation of positive surgical margin with clinicopathological factors and prognoses in breast conserving surgery

International Nuclear Information System (INIS)

Nishimura, Reiki; Nagao, Kazuharu; Miyayama, Haruhiko

1999-01-01

Out of 484 cases with breast conserving surgery between April 1989 and March 1999, surgical procedures of 34 cases were changed to total mastectomy due to positive surgical margins. In this study we evaluated a clinical significance of surgical margin in relation to clinicopathological factors and prognoses. Ninety-nine cases (20.5%) had positive margins that were judged when cancer cells existed within 5 mm from margin. In multivariate analysis of factors for surgical margin, EIC-comedo status, ly, located site, proliferative activity, and age were significant and independent factors. Regarding local recurrence, positive margin, age, ER and proliferative activity were significant factors in multivariate analysis, especially in cases not receiving postoperative radiation therapy. Radiation therapy may be beneficial for patients with positive surgical margin. And patients with breast recurrence alone had significantly higher survival rates. Therefore, it is suggested that surgical margin may not reflect survival, although it is a significant factor for local recurrence. (author)

Studies on correlation of positive surgical margin with clinicopathological factors and prognoses in breast conserving surgery

Energy Technology Data Exchange (ETDEWEB)

Nishimura, Reiki; Nagao, Kazuharu; Miyayama, Haruhiko [Kumamoto City Hospital (Japan)

1999-09-01

Out of 484 cases with breast conserving surgery between April 1989 and March 1999, surgical procedures of 34 cases were changed to total mastectomy due to positive surgical margins. In this study we evaluated a clinical significance of surgical margin in relation to clinicopathological factors and prognoses. Ninety-nine cases (20.5%) had positive margins that were judged when cancer cells existed within 5 mm from margin. In multivariate analysis of factors for surgical margin, EIC-comedo status, ly, located site, proliferative activity, and age were significant and independent factors. Regarding local recurrence, positive margin, age, ER and proliferative activity were significant factors in multivariate analysis, especially in cases not receiving postoperative radiation therapy. Radiation therapy may be beneficial for patients with positive surgical margin. And patients with breast recurrence alone had significantly higher survival rates. Therefore, it is suggested that surgical margin may not reflect survival, although it is a significant factor for local recurrence. (author)

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.…

Predicting risk for portal vein thrombosis in acute pancreatitis patients: A comparison of radical basis function artificial neural network and logistic regression models.

Science.gov (United States)

Fei, Yang; Hu, Jian; Gao, Kun; Tu, Jianfeng; Li, Wei-Qin; Wang, Wei

2017-06-01

To construct a radical basis function (RBF) artificial neural networks (ANNs) model to predict the incidence of acute pancreatitis (AP)-induced portal vein thrombosis. The analysis included 353 patients with AP who had admitted between January 2011 and December 2015. RBF ANNs model and logistic regression model were constructed based on eleven factors relevant to AP respectively. Statistical indexes were used to evaluate the value of the prediction in two models. The predict sensitivity, specificity, positive predictive value, negative predictive value and accuracy by RBF ANNs model for PVT were 73.3%, 91.4%, 68.8%, 93.0% and 87.7%, respectively. There were significant differences between the RBF ANNs and logistic regression models in these parameters (Plogistic regression model. D-dimer, AMY, Hct and PT were important prediction factors of approval for AP-induced PVT. Copyright © 2017 Elsevier Inc. All rights reserved.

Associated Factors of Suicidal Thoughts in HIV-Positive Individuals

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Fatemeh Dabaghzadeh

2015-11-01

Full Text Available  Objective: As a first study, suicidal ideation and its correlates have been evaluated in Iranian HIV positive population .  Methods:One hundred and fifty HIV-positive individuals were recruited in this cross-sectional study. The Hospital Anxiety and Depression Scale (HADS, Positive and Negative Suicide Ideation (PANSI, Pittsburgh Sleep Quality Inventory (PSQI and Somatization subscale of Symptom Checklist 90 (SCL 90 as self- reported questionnaires were used to assess the patients’ anxiety and depression status, suicidal thoughts, sleep quality and physiological factors, respectively . Results:Antiretroviral therapy and efavirenz intake did not show any significant effects on the patients’ suicidal ideation. Anxiety (p<0.001, depression (p<0.001, poor physical activity (P<0.001 and sleep quality (p<0.001 were significantly associated with the patients’ negative suicidal ideation. From the patients’ demographic data, unemployment (p = 0.04, living alone (p = 0.01, and lack of family support (p = 0.01 were correlated with the patients’ negative suicidal thoughts . Conclusion:Although hospitals are the main referral centers for providing care for HIV-positive individuals in Tehran, Iran, conducting a multi-center study with sufficient sample size from different areas of our country that include individuals with different behaviors and cultures is essential to confirm the results of this study.

Menopausal symptoms and associated factors in HIV-positive women.

Science.gov (United States)

Lui-Filho, Jeffrey F; Valadares, Ana Lúcia R; Gomes, Debora de C; Amaral, Eliana; Pinto-Neto, Aarão M; Costa-Paiva, Lúcia

2013-10-01

To evaluate menopausal symptoms and their associated factors in HIV-positive women. A cross-sectional study was conducted with 537 women of 40-60 years of age, 273 of whom were HIV-positive and 264 HIV-negative. The women were interviewed to obtain data on their sociodemographic characteristics and menopausal symptoms. The mean age of the seropositive women was 47.7±5.8 years compared to 49.8±5.3 for the seronegative women (psymptoms in the seropositive group (p=0.009), specifically hot flashes (pHIV serological status and any of the menopausal symptoms. In this study, after controlling for confounding variables, HIV infection was not found to be associated with vasomotor, genitourinary or psychological symptoms or with insomnia. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Factors associated with involvement of four or more axillary nodes for sentinel lymph node-positive patients

International Nuclear Information System (INIS)

Katz, Angela; Niemierko, Andrzej; Gage, Irene; Evans, Sheila; Shaffer, Margaret; Smith, Frederick P.; Taghian, Alphonse; Magnant, Colette

2006-01-01

Purpose: Sentinel lymph node-positive (SLN+) patients who are unlikely to have 4 or more involved axillary nodes might be treated with less extensive regional nodal radiation. The purpose of this study was to define possible predictors of having 4 or more involved axillary nodes. Methods and Materials: The records of 224 patients with breast cancer and 1 to 3 involved SLNs, who underwent completion axillary dissection without neoadjuvant chemotherapy or hormonal therapy were reviewed. Factors associated with the presence of 4 or more involved axillary nodes (SLNs plus non-SLNs) were evaluated by Pearson chi-square test of association and by simple and multiple logistic-regression analysis. Results: Of 224 patients, 42 had involvement of 4 or more axillary nodes. On univariate analysis, the presence of 4 or more involved axillary nodes was positively associated with increased tumor size, lobular histology, lymphovascular space invasion (LVSI), increased number of involved SLNs, decreased number of uninvolved SLNs, and increased size of SLN metastasis. On multivariate analysis, the presence of 4 or more involved axillary nodes was associated with LVSI, increased number of involved SLNs, increased size of SLN metastasis, and lobular histology. Conclusions: Patients with 1 or more involved SLN, LVSI, or SLN macrometastasis should be treated to the supraclavicular fossa/axillary apex if they do not undergo completion axillary dissection. Other SLN+ patients might be adequately treated with less extensive radiation fields

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.

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.

Boosting structured additive quantile regression for longitudinal childhood obesity data.

Science.gov (United States)

Fenske, Nora; Fahrmeir, Ludwig; Hothorn, Torsten; Rzehak, Peter; Höhle, Michael

2013-07-25

Childhood obesity and the investigation of its risk factors has become an important public health issue. Our work is based on and motivated by a German longitudinal study including 2,226 children with up to ten measurements on their body mass index (BMI) and risk factors from birth to the age of 10 years. We introduce boosting of structured additive quantile regression as a novel distribution-free approach for longitudinal quantile regression. The quantile-specific predictors of our model include conventional linear population effects, smooth nonlinear functional effects, varying-coefficient terms, and individual-specific effects, such as intercepts and slopes. Estimation is based on boosting, a computer intensive inference method for highly complex models. We propose a component-wise functional gradient descent boosting algorithm that allows for penalized estimation of the large variety of different effects, particularly leading to individual-specific effects shrunken toward zero. This concept allows us to flexibly estimate the nonlinear age curves of upper quantiles of the BMI distribution, both on population and on individual-specific level, adjusted for further risk factors and to detect age-varying effects of categorical risk factors. Our model approach can be regarded as the quantile regression analog of Gaussian additive mixed models (or structured additive mean regression models), and we compare both model classes with respect to our obesity data.

Directional quantile regression in R

Czech Academy of Sciences Publication Activity Database

Boček, Pavel; Šiman, Miroslav

2017-01-01

Roč. 53, č. 3 (2017), s. 480-492 ISSN 0023-5954 R&D Projects: GA ČR GA14-07234S Institutional support: RVO:67985556 Keywords : multivariate quantile * regression quantile * halfspace depth * depth contour Subject RIV: BD - Theory of Information OBOR OECD: Applied mathematics Impact factor: 0.379, year: 2016 http://library.utia.cas.cz/separaty/2017/SI/bocek-0476587.pdf

Advanced colorectal neoplasia risk stratification by penalized logistic regression.

Science.gov (United States)

Lin, Yunzhi; Yu, Menggang; Wang, Sijian; Chappell, Richard; Imperiale, Thomas F

2016-08-01

Colorectal cancer is the second leading cause of death from cancer in the United States. To facilitate the efficiency of colorectal cancer screening, there is a need to stratify risk for colorectal cancer among the 90% of US residents who are considered "average risk." In this article, we investigate such risk stratification rules for advanced colorectal neoplasia (colorectal cancer and advanced, precancerous polyps). We use a recently completed large cohort study of subjects who underwent a first screening colonoscopy. Logistic regression models have been used in the literature to estimate the risk of advanced colorectal neoplasia based on quantifiable risk factors. However, logistic regression may be prone to overfitting and instability in variable selection. Since most of the risk factors in our study have several categories, it was tempting to collapse these categories into fewer risk groups. We propose a penalized logistic regression method that automatically and simultaneously selects variables, groups categories, and estimates their coefficients by penalizing the [Formula: see text]-norm of both the coefficients and their differences. Hence, it encourages sparsity in the categories, i.e. grouping of the categories, and sparsity in the variables, i.e. variable selection. We apply the penalized logistic regression method to our data. The important variables are selected, with close categories simultaneously grouped, by penalized regression models with and without the interactions terms. The models are validated with 10-fold cross-validation. The receiver operating characteristic curves of the penalized regression models dominate the receiver operating characteristic curve of naive logistic regressions, indicating a superior discriminative performance. © The Author(s) 2013.

Factors Impacting Online Ratings for Otolaryngologists.

Science.gov (United States)

Calixto, Nathaniel E; Chiao, Whitney; Durr, Megan L; Jiang, Nancy

2018-06-01

To identify factors associated with online patient ratings and comments for a nationwide sample of otolaryngologists. Ratings, demographic information, and written comments were obtained for a random sample of otolaryngologists from HealthGrades.com and Vitals.com . Online Presence Score (OPS) was based on 10 criteria, including professional website and social media profiles. Regression analyses identified factors associated with increased rating. We evaluated for correlations between OPS and other attributes with star rating and used chi-square tests to evaluate content differences between positive and negative comments. On linear regression, increased OPS was associated with higher ratings on HealthGrades and Vitals; higher ratings were also associated with younger age on Vitals and less experience on HealthGrades. However, detailed correlation studies showed weak correlation between OPS and rating; age and graduation year also showed low correlation with ratings. Negative comments more likely focused on surgeon-independent factors or poor bedside manner. Though younger otolaryngologists with greater online presence tend to have higher ratings, weak correlations suggest that age and online presence have only a small impact on the content found on ratings websites. While most written comments are positive, deficiencies in bedside manner or other physician-independent factors tend to elicit negative comments.

Geographically weighted regression model on poverty indicator

Science.gov (United States)

Slamet, I.; Nugroho, N. F. T. A.; Muslich

2017-12-01

In this research, we applied geographically weighted regression (GWR) for analyzing the poverty in Central Java. We consider Gaussian Kernel as weighted function. The GWR uses the diagonal matrix resulted from calculating kernel Gaussian function as a weighted function in the regression model. The kernel weights is used to handle spatial effects on the data so that a model can be obtained for each location. The purpose of this paper is to model of poverty percentage data in Central Java province using GWR with Gaussian kernel weighted function and to determine the influencing factors in each regency/city in Central Java province. Based on the research, we obtained geographically weighted regression model with Gaussian kernel weighted function on poverty percentage data in Central Java province. We found that percentage of population working as farmers, population growth rate, percentage of households with regular sanitation, and BPJS beneficiaries are the variables that affect the percentage of poverty in Central Java province. In this research, we found the determination coefficient R2 are 68.64%. There are two categories of district which are influenced by different of significance factors.

Correlation of results obtained by in-vivo optical spectroscopy with measured blood oxygen saturation using a positive linear regression fit

Science.gov (United States)

McCormick, Patrick W.; Lewis, Gary D.; Dujovny, Manuel; Ausman, James I.; Stewart, Mick; Widman, Ronald A.

1992-05-01

Near infrared light generated by specialized instrumentation was passed through artificially oxygenated human blood during simultaneous sampling by a co-oximeter. Characteristic absorption spectra were analyzed to calculate the ratio of oxygenated to reduced hemoglobin. A positive linear regression fit between diffuse transmission oximetry and measured blood oxygenation over the range 23% to 99% (r2 equals .98, p signal was observed in the patient over time. The procedure was able to be performed clinically without difficulty; rSO2 values recorded continuously demonstrate the usefulness of the technique. Using the same instrumentation, arterial input and cerebral response functions, generated by IV tracer bolus, were deconvoluted to measure mean cerebral transit time. Date collected over time provided a sensitive index of changes in cerebral blood flow as a result of therapeutic maneuvers.

Reproductive risk factors assessment for anaemia among pregnant women in India using a multinomial logistic regression model.

Science.gov (United States)

Perumal, Vanamail

2014-07-01

To assess reproductive risk factors for anaemia among pregnant women in urban and rural areas of India. The International Institute of Population Sciences, India, carried out third National Family Health Survey in 2005-2006 to estimate a key indicator from a sample of ever-married women in the reproductive age group 15-49 years. Data on various dimensions were collected using a structured questionnaire, and anaemia was measured using a portable HemoCue instrument. Anaemia prevalence among pregnant women was compared between rural and urban areas using chi-square test and odds ratio. Multinomial logistic regression analysis was used to determine risk factors. Anaemia prevalence was assessed among 3355 pregnant women from rural areas and 1962 pregnant women from urban areas. Moderate-to-severe anaemia in rural areas (32.4%) is significantly more common than in urban areas (27.3%) with an excess risk of 30%. Gestational age specific prevalence of anaemia significantly increases in rural areas after 6 months. Pregnancy duration is a significant risk factor in both urban and rural areas. In rural areas, increasing age at marriage and mass media exposure are significant protective factors of anaemia. However, more births in the last five years, alcohol consumption and smoking habits are significant risk factors. In rural areas, various reproductive factors and lifestyle characteristics constitute significant risk factors for moderate-to-severe anaemia. Therefore, intensive health education on reproductive practices and the impact of lifestyle characteristics are warranted to reduce anaemia prevalence. © 2014 John Wiley & Sons Ltd.

Positive and negative affectivity as risk factors for heavy drinking in the second half of life: a prospective cohort study.

Science.gov (United States)

Brunborg, Geir Scott

2017-05-01

To estimate the prospective relations between levels of propensity to experience positive affect (PA) and propensity to experience negative affect (NA) and risk of heavy drinking in a cohort of Norwegians aged 40-80 years. Clustered sampling was used to draw Norwegians aged 40-79 years in 2002/03 (t1). The relationship between PA and NA measured at t1 and heavy drinking measured in 2007/08 (t2) was estimated with random-intercept logistic regression. Norway. A total of 2142 (44.0% men) who consumed mean = 3.07 [standard deviation (SD) = 3.15] UK units of alcohol on average per week and were intoxicated less than once per week at t1. The Brief Measure of Positive and Negative Affect, quantity-frequency measure of alcohol use and frequency of drinking to intoxication. Heavy drinking at t2 (> 14 units per week and/or intoxication ≥ once per week) was regressed on PA and NA at t1. Controlling for alcohol consumption, gender, age, income and level of education (at t1) and change in PA and NA, there was little evidence for an association between level of PA and heavy drinking [odds ratio (OR) = 0.96, 95% confidence interval (CI) = 0.71, 1.29, Bayes factor = 0.15]. The level of NA at t1 was associated with greater risk of heavy drinking at t2 (OR = 1.40, 95% CI = 1.02, 1.93). There is little evidence for an association between the propensity to experience positive affect and heavy drinking among Norwegians aged 40-80 years. Norwegian adults in the second half of life with a high propensity to experience negative affect are at greater risk of heavy drinking approximately 5 years later than those with a low propensity to experience negative affect. © 2016 Society for the Study of Addiction.

CLINICOPATHOLOGICAL FACTORS ASSOCIATED WITH POSITIVE PREOPERATIVE AXILLARY ULTRASOUND SCANNING IN BREAST CANCER PATIENTS

Directory of Open Access Journals (Sweden)

Lona Jalini

2016-01-01

Full Text Available Background: Axillary lymph node status is the most important breast cancer prognostic factor. Preoperative axillary ultrasound examination (PAUS is used to triage patients for sentinel lymph node biopsy (SLNB or axillary lymph node dissection (ALND. We assessed the detection rate of lymph node metastases by PAUS in a screening unit and evaluated associations between clinicopathological factors and PAUS positivity. Patients and Methods: This was a single-centre retrospective analysis of data extracted from a hospital breast cancer database and clinical records. Clinical, radiological, and pathological and prognostic indices were compared between PAUS-positive and PAUS-negative patients subsequently found to have lymph node metastases on histopathological analysis. Results: Two hundred and two patients were eligible for analysis. 50.5% of lymph node-positive patients were correctly identified as PAUS positive. Patients with PAUS-positive lymph nodes had less favorable disease characteristics, namely clinically palpable lymph nodes, higher Nottingham prognostic (NPI index, high lymph node burden according to the European Society of Medical Oncology (ESMO group classification, and larger, grade 3 tumors with lymphovascular invasion and extranodal spread. Moreover, PAUS-positive patients had more macrometastases and lymph node involvement than PAUS-negative patients. Conclusion: PAUS-positive patients and PAUS-negative (SLNB-positive patients have different clinicopathological characteristics. The presence of LVI, extranodal spread, grade 3 histology, or large tumors with poor prognostic indices in PAUS-negative patients should be regarded with caution and perhaps prompt second-look ultrasound examination.

Modeling the number of car theft using Poisson regression

Science.gov (United States)

Zulkifli, Malina; Ling, Agnes Beh Yen; Kasim, Maznah Mat; Ismail, Noriszura

2016-10-01

Regression analysis is the most popular statistical methods used to express the relationship between the variables of response with the covariates. The aim of this paper is to evaluate the factors that influence the number of car theft using Poisson regression model. This paper will focus on the number of car thefts that occurred in districts in Peninsular Malaysia. There are two groups of factor that have been considered, namely district descriptive factors and socio and demographic factors. The result of the study showed that Bumiputera composition, Chinese composition, Other ethnic composition, foreign migration, number of residence with the age between 25 to 64, number of employed person and number of unemployed person are the most influence factors that affect the car theft cases. These information are very useful for the law enforcement department, insurance company and car owners in order to reduce and limiting the car theft cases in Peninsular Malaysia.

Regression analysis of nuclear plant capacity factors

International Nuclear Information System (INIS)

Stocks, K.J.; Faulkner, J.I.

1980-07-01

Operating data on all commercial nuclear power plants of the PWR, HWR, BWR and GCR types in the Western World are analysed statistically to determine whether the explanatory variables size, year of operation, vintage and reactor supplier are significant in accounting for the variation in capacity factor. The results are compared with a number of previous studies which analysed only United States reactors. The possibility of specification errors affecting the results is also examined. Although, in general, the variables considered are statistically significant, they explain only a small portion of the variation in the capacity factor. The equations thus obtained should certainly not be used to predict the lifetime performance of future large reactors

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.

Cardiovascular risk factors associated with lower baseline cognitive performance in HIV-positive persons.

Science.gov (United States)

Wright, E J; Grund, B; Robertson, K; Brew, B J; Roediger, M; Bain, M P; Drummond, F; Vjecha, M J; Hoy, J; Miller, C; Penalva de Oliveira, A C; Pumpradit, W; Shlay, J C; El-Sadr, W; Price, R W

2010-09-07

To determine factors associated with baseline neurocognitive performance in HIV-infected participants enrolled in the Strategies for Management of Antiretroviral Therapy (SMART) neurology substudy. Participants from Australia, North America, Brazil, and Thailand were administered a 5-test neurocognitive battery. Z scores and the neurocognitive performance outcome measure, the quantitative neurocognitive performance z score (QNPZ-5), were calculated using US norms. Neurocognitive impairment was defined as z scores penetration effectiveness rank of antiretroviral regimens were not. In this HIV-positive population with high CD4 cell counts, neurocognitive impairment was associated with prior CVD. Lower neurocognitive performance was associated with prior CVD, hypertension, and hypercholesterolemia, but not conventional HAD risk factors. The contribution of CVD and cardiovascular risk factors to the neurocognition of HIV-positive populations warrants further investigation.

Factors Predicting Sustainability of the Schoolwide Positive Behavior Intervention Support Model

Science.gov (United States)

Chitiyo, Jonathan; May, Michael E.

2018-01-01

The Schoolwide Positive Behavior Intervention Support model (SWPBIS) continues to gain widespread use across schools in the United States and abroad. Despite its widespread implementation, little research has examined factors that influence its sustainability. Informed by Rogers's diffusion theory, this study examined school personnel's…

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)

Effect of removing the common mode errors on linear regression analysis of noise amplitudes in position time series of a regional GPS network & a case study of GPS stations in Southern California

Science.gov (United States)

Jiang, Weiping; Ma, Jun; Li, Zhao; Zhou, Xiaohui; Zhou, Boye

2018-05-01

The analysis of the correlations between the noise in different components of GPS stations has positive significance to those trying to obtain more accurate uncertainty of velocity with respect to station motion. Previous research into noise in GPS position time series focused mainly on single component evaluation, which affects the acquisition of precise station positions, the velocity field, and its uncertainty. In this study, before and after removing the common-mode error (CME), we performed one-dimensional linear regression analysis of the noise amplitude vectors in different components of 126 GPS stations with a combination of white noise, flicker noise, and random walking noise in Southern California. The results show that, on the one hand, there are above-moderate degrees of correlation between the white noise amplitude vectors in all components of the stations before and after removal of the CME, while the correlations between flicker noise amplitude vectors in horizontal and vertical components are enhanced from un-correlated to moderately correlated by removing the CME. On the other hand, the significance tests show that, all of the obtained linear regression equations, which represent a unique function of the noise amplitude in any two components, are of practical value after removing the CME. According to the noise amplitude estimates in two components and the linear regression equations, more accurate noise amplitudes can be acquired in the two components.

APPLICATION OF MULTIPLE LOGISTIC REGRESSION, BAYESIAN LOGISTIC AND CLASSIFICATION TREE TO IDENTIFY THE SIGNIFICANT FACTORS INFLUENCING CRASH SEVERITY

Directory of Open Access Journals (Sweden)

MILAD TAZIK

2017-11-01

Full Text Available Identifying cases in which road crashes result in fatality or injury of drivers may help improve their safety. In this study, datasets of crashes happened in TehranQom freeway, Iran, were examined by three models (multiple logistic regression, Bayesian logistic and classification tree to analyse the contribution of several variables to fatal accidents. For multiple logistic regression and Bayesian logistic models, the odds ratio was calculated for each variable. The model which best suited the identification of accident severity was determined based on AIC and DIC criteria. Based on the results of these two models, rollover crashes (OR = 14.58, %95 CI: 6.8-28.6, not using of seat belt (OR = 5.79, %95 CI: 3.1-9.9, exceeding speed limits (OR = 4.02, %95 CI: 1.8-7.9 and being female (OR = 2.91, %95 CI: 1.1-6.1 were the most important factors in fatalities of drivers. In addition, the results of the classification tree model have verified the findings of the other models.

Positive semidefinite tensor factorizations of the two-electron integral matrix for low-scaling ab initio electronic structure.

Science.gov (United States)

Hoy, Erik P; Mazziotti, David A

2015-08-14

Tensor factorization of the 2-electron integral matrix is a well-known technique for reducing the computational scaling of ab initio electronic structure methods toward that of Hartree-Fock and density functional theories. The simplest factorization that maintains the positive semidefinite character of the 2-electron integral matrix is the Cholesky factorization. In this paper, we introduce a family of positive semidefinite factorizations that generalize the Cholesky factorization. Using an implementation of the factorization within the parametric 2-RDM method [D. A. Mazziotti, Phys. Rev. Lett. 101, 253002 (2008)], we study several inorganic molecules, alkane chains, and potential energy curves and find that this generalized factorization retains the accuracy and size extensivity of the Cholesky factorization, even in the presence of multi-reference correlation. The generalized family of positive semidefinite factorizations has potential applications to low-scaling ab initio electronic structure methods that treat electron correlation with a computational cost approaching that of the Hartree-Fock method or density functional theory.

Positive semidefinite tensor factorizations of the two-electron integral matrix for low-scaling ab initio electronic structure

Energy Technology Data Exchange (ETDEWEB)

Hoy, Erik P.; Mazziotti, David A., E-mail: damazz@uchicago.edu [Department of Chemistry and The James Franck Institute, The University of Chicago, Chicago, Illinois 60637 (United States)

2015-08-14

Tensor factorization of the 2-electron integral matrix is a well-known technique for reducing the computational scaling of ab initio electronic structure methods toward that of Hartree-Fock and density functional theories. The simplest factorization that maintains the positive semidefinite character of the 2-electron integral matrix is the Cholesky factorization. In this paper, we introduce a family of positive semidefinite factorizations that generalize the Cholesky factorization. Using an implementation of the factorization within the parametric 2-RDM method [D. A. Mazziotti, Phys. Rev. Lett. 101, 253002 (2008)], we study several inorganic molecules, alkane chains, and potential energy curves and find that this generalized factorization retains the accuracy and size extensivity of the Cholesky factorization, even in the presence of multi-reference correlation. The generalized family of positive semidefinite factorizations has potential applications to low-scaling ab initio electronic structure methods that treat electron correlation with a computational cost approaching that of the Hartree-Fock method or density functional theory.

Prevalence and Factors Associated with Fixed-Dose Combination Antiretroviral Drugs Adherence among HIV-Positive Pregnant Women on Option B Treatment in Mpumalanga Province, South Africa

Directory of Open Access Journals (Sweden)

Shandir Ramlagan

2018-01-01

Full Text Available The possibility for all babies to be born and remain HIV-negative for the first year of life is achievable in South Africa. HIV-positive mothers’ adherence to their antiretroviral medication is one of the crucial factors to achieve this target. Cross-sectional data were collected at 12 community health centres, over 12 months (2014–2015, from 673 HIV-positive women, less than 6 months pregnant, attending antenatal care, and on Option B treatment. Adherence measures included the Adults AIDS Clinical Trials Group (AACTG four-day measure, as well as the Visual Analog Scale (VAS seven-day measure. Bivariate analyses and multivariate logistic regressions are presented. 78.8% of respondents were adherent on AACTG, while 68.8% reported VAS adherence. Bivariate analyses for increased adherence show significant associations with older age, less/no alcohol usage, disclosure of HIV status, higher HIV knowledge, no desire to avoid ARV side effects, low stigma, and low depression. AACTG showed a negative association with intimate partner violence. Multivariable logistic regression on AACTG and VAS adherence rates resulted in unique contributions to increased adherence of older age, less/no alcohol usage, higher HIV knowledge, lack of depression, and non-disclosure. Programs targeting closer side effect monitoring, HIV disclosure, pre-natal depression, alcohol intake, and HIV knowledge need consideration.

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

Refractive regression after laser in situ keratomileusis.

Science.gov (United States)

Yan, Mabel K; Chang, John Sm; Chan, Tommy Cy

2018-04-26

Uncorrected refractive errors are a leading cause of visual impairment across the world. In today's society, laser in situ keratomileusis (LASIK) has become the most commonly performed surgical procedure to correct refractive errors. However, regression of the initially achieved refractive correction has been a widely observed phenomenon following LASIK since its inception more than two decades ago. Despite technological advances in laser refractive surgery and various proposed management strategies, post-LASIK regression is still frequently observed and has significant implications for the long-term visual performance and quality of life of patients. This review explores the mechanism of refractive regression after both myopic and hyperopic LASIK, predisposing risk factors and its clinical course. In addition, current preventative strategies and therapies are also reviewed. © 2018 Royal Australian and New Zealand College of Ophthalmologists.

Estimating the Influence of Accident Related Factors on Motorcycle Fatal Accidents using Logistic Regression (Case Study: Denpasar-Bali

Directory of Open Access Journals (Sweden)

Wedagama D.M.P.

2010-01-01

Full Text Available In Denpasar the capital of Bali Province, motorcycle accident contributes to about 80% of total road accidents. Out of those motorcycle accidents, 32% are fatal accidents. This study investigates the influence of accident related factors on motorcycle fatal accidents in the city of Denpasar during period 2006-2008 using a logistic regression model. The study found that the fatality of collision with pedestrians and right angle accidents were respectively about 0.44 and 0.40 times lower than collision with other vehicles and accidents due to other factors. In contrast, the odds that a motorcycle accident will be fatal due to collision with heavy and light vehicles were 1.67 times more likely than with other motorcycles. Collision with pedestrians, right angle accidents, and heavy and light vehicles were respectively accounted for 31%, 29%, and 63% of motorcycle fatal accidents.

A Study on the Estimation of the Scale Factor for Precise Point Positioning

Science.gov (United States)

Erdogan, Bahattin; Kayacik, Orhan

2017-04-01

Precise Point Positioning (PPP) technique is one of the most important subject in Geomatic Engineering. PPP technique needs only one GNSS receiver and users have preferred it instead of traditional relative positioning technique for several applications. Scientific software has been used for PPP solutions and the software may underestimate the formal errors of the estimated coordinates. The formal errors have major effects on statistical interpretation. Variance-Covariance (VCV) matrix derived from GNSS processing software plays important role for deformation analysis and scientists sometimes need to scale VCV matrix. In this study, 10 continuously operating reference stations have been considered for 11 days dated 2014. All points have been analyzed by Gipsy-OASIS v6.4 scientific software. The solutions were derived for different session durations as 2, 4, 6, 8, 12 and 24 hours to obtain repeatability of the coordinates and analyses were carried out in order to estimate scale factor for Gipsy-OASIS v6.4 PPP results. According to the first results scale factors slightly increase depending on the raises in respect of session duration. Keywords: Precise Point Positioning, Gipsy-OASIS v6.4, Variance-Covariance Matrix, Scale Factor

Investigating the effects of strategic positioning for development of modern banking services

Directory of Open Access Journals (Sweden)

Vahid Anvar Keivi

2014-05-01

Full Text Available During the past few years, there have been tremendous changes on banking services and many bank customers are able to do their daily banking activities using recent advances of technology such as internet banking, telephone banking, etc. In this paper, we present an empirical investigation on the effects of strategic positioning for development of modern banking services. The proposed study designs a questionnaire in Likert scale and distributes it among some 385 randomly selected people who live in Tehran in 2013. The questionnaire consists of seven factors including property positioning, advantage positioning, consumer positioning, user positioning, competitive advantage positioning, quality positioning and merchandise category positioning. Using Spearman correlation as well as stepwise regression technique, the study has determined positive and meaningful relationships between different components of strategy positioning development of modern banking services.

Cognitive Reserve as a Protective Factor in Older HIV-Positive Patients at Risk for Cognitive Decline

OpenAIRE

Foley, Jessica M.; Ettenhofer, Mark L.; Kim, Michelle S.; Behdin, Nina; Castellon, Steven A.; Hinkin, Charles H.

2012-01-01

The present study examined the impact of cognitive reserve in maintaining intact neuropsychological (NP) function among older HIV-positive individuals, a uniquely at-risk subgroup. Participants included 129 individuals classified by HIV serostatus, age group, and NP impairment. A three-way analysis of variance (ANOVA) followed by a series of within-group ANOVA and multiple regression analyses were conducted to investigate the pattern of cognitive reserve (vs. other protective) influence among...

A Comparative study of Personality as a common pathway in HIV Sero-positive and Alcohol dependent cases on Five Factor Model

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Kalpana Srivastava

2016-01-01

Full Text Available Aim: The aim of this study was to identify the personality traits of alcohol and human immunodeficiency virus (HIV-positive patients and to compare them with normal controls. Materials and Methods: This cross-sectional study included 100 consecutive patients with alcohol dependence and HIV each and a control group of 100 normal cases without any physical or psychiatric illness. A score of 2 or less on the General Health Questionnaire was taken as cutoff, and the participants were included in the study with written informed consent. All participants were assessed with the NEO personality inventory revised and sensation-seeking scale (SSS. Results: There were significant differences among the study group on all the five factors, i.e., neuroticism (N, extraversion (E, conscientiousness (C, openness to experience (O, and agreeableness (A. On factor “N,” HIV and alcohol group scored significantly more as compared to normal group. Odds ratio revealed high neuroticism to be a risk factor in alcohol-dependent and HIV cases (P < 0.05. The normal group scored significantly higher on factor “E” as compared to HIV and alcohol cases. High scores on factor “E” and “C” have a protective. Odds ratio found low score of factor “C” as a risk factor; however, “O” did not emerge as a risk factor. The logistic regression revealed that high scores on “N” and “E” and low “A” score had a significant association with alcohol dependence (P < 0.05. Among HIV cases, high score on “N” and “E” and low “C” score emerged significant. Alcohol cases scored significantly more on boredom susceptibility (BS on SSS as compared to HIV and normal controls. On disinhibition (DIS, HIV cases and alcohol cases scored significantly higher as compared to normal group (P < 0.05. Conclusion: High “N” scores on NEO personality inventory are significantly associated with alcohol dependence and HIV while high scores on “E” and “C” have a

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)

Risk Factors for Hepatitis B virus Surface Antigen Positive Prevalence in the Most Migratory Province of Iran: A Matched Case- Control Study

Directory of Open Access Journals (Sweden)

Gh. Karimi

2015-02-01

Full Text Available Background and Objective: Hepatitis B Virus Infection is one of the most common infectious diseases and also among the world's top ten causes of this group diseases-related mortality, so that 500,000 to 1.2 million annually die due to the consequences of this infection such as chronic hepatitis, cirrhosis and hepatocellular carcinoma. This study was conducted to determine risk factors for HBsAg-positive prevalence in Alborz Province. Materials and Methods: A 1:1 matched case-control study, 213 of cases reported HBsAg positive to the Alborz University of Medical Sciences in 2013 as case group with 213 of family members of patients with hepatitis C who have serologic markers Anti- HCV negative and HBsAg negative as the control group, were compared in terms of demographic characteristics, History of high risk behaviors, Iatrogenic exposures, community exposures and history of liver disease. Statistical analysis using logistic regression was performed by SPSS software version 18. Results: Reported cases with a mean age of 37.6±15.5 years, was more relevant to marginalized, immigrants and male gender. Nationality, being married, low level of education, family history of HBsAg positive, history of non-intravenous drug abuse, alcohol consumption, history of prison, employment in high risk occupations, sharing of razor, injuries with contaminated sharp instruments and history of jaundice in mother were found to be independent risk factors for HBsAg positive prevalence (OR: 0.27, 3.61, 1.68, 18.04, 12.21, 2.9, 7.52, 2.47, 5.55, 21.48, 11.3, respectively. Conclusions: Unfavorable situation of the marginalized and the prisoners, imported illegal immigrants, especially Afghans can be extended to high-risk behaviors and the threat of a disease surveillance system. Screening and vaccination aforementioned groups, health promotion of the marginalized and raise public knowledge is necessary.

Analysis of γ spectra in airborne radioactivity measurements using multiple linear regressions

International Nuclear Information System (INIS)

Bao Min; Shi Quanlin; Zhang Jiamei

2004-01-01

This paper describes the net peak counts calculating of nuclide 137 Cs at 662 keV of γ spectra in airborne radioactivity measurements using multiple linear regressions. Mathematic model is founded by analyzing every factor that has contribution to Cs peak counts in spectra, and multiple linear regression function is established. Calculating process adopts stepwise regression, and the indistinctive factors are eliminated by F check. The regression results and its uncertainty are calculated using Least Square Estimation, then the Cs peak net counts and its uncertainty can be gotten. The analysis results for experimental spectrum are displayed. The influence of energy shift and energy resolution on the analyzing result is discussed. In comparison with the stripping spectra method, multiple linear regression method needn't stripping radios, and the calculating result has relation with the counts in Cs peak only, and the calculating uncertainty is reduced. (authors)

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...

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.

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

Incidence and risk factors of herpes zoster among hiv-positive patients in the german competence network for HIV/AIDS (KompNet): a cohort study analysis.

Science.gov (United States)

Jansen, Klaus; Haastert, Burkhard; Michalik, Claudia; Guignard, Adrienne; Esser, Stefan; Dupke, Stephan; Plettenberg, Andreas; Skaletz-Rorowski, Adriane; Brockmeyer, Norbert H

2013-08-10

HIV infection is a risk factor for the development of Herpes zoster (HZ) and its complications. Prior to antiretroviral therapy (ART), HZ incidence in HIV-infected individuals ranged from 2.9-5.1/100 person-years. There is limited evidence for the impact of ART on HZ occurrence among HIV-infected adults. We analysed the incidence of, and risk factors for, HZ in a large cohort of German HIV-positive patients. The study population was taken from the German KompNet cohort, a nationwide multicenter HIV cohort study. The study population was defined by age (≥ 18 years), year of first positive HIV diagnosis, CD4 values ± 6 months from HIV diagnosis (t0), and month of HZ diagnosis. Incidences were estimated using a Poisson distribution, and uni- and multivariate Cox proportional Hazard ratio (HR) regression models were fitted to identify risk factors for developing an initial HZ episode. Independent variables were sex, age at HIV diagnosis, route of HIV transmission, ART status, CD4 count before HZ episode, immunosuppressive medication, and mode of data documentation (retrospective or prospective). HZ incidence in the overall study population was 1.2/100 person-years. In a subset of patients for that we were able to examine risk factors the following was observed: We examined 3,757 individuals whose mean age at t0 was 38 years. Of those individuals, 96% were diagnosed with HIV in 1996 or later, with a mean observation time of 5.8 years. HZ episodes (n = 362) were recorded in 326 patients (8.7%), resulting in annual HZ incidences of 1.7/100 person-years overall, and 1.6/100 person-years for initial HZ cases. The main risk factors associated with an initial HZ episode were: not partaking in ART compared with an ART regimen containing a non-nucleoside reverse-transcriptase inhibitor (HR 0.530, p study HZ incidences were lower than in previous studies relating to HIV-positive patients. We showed that ART is an important protective factor for HZ episodes.

First positive reactions to cannabis constitute a priority risk factor for cannabis dependence.

Science.gov (United States)

Le Strat, Yann; Ramoz, Nicolas; Horwood, John; Falissard, Bruno; Hassler, Christine; Romo, Lucia; Choquet, Marie; Fergusson, David; Gorwood, Philip

2009-10-01

To assess the association between first reactions to cannabis and the risk of cannabis dependence. A cross-sectional population-based assessment in 2007. A campus in a French region (Champagne-Ardennes). A total of 1472 participants aged 18-21 years who reported at least one life-time cannabis consumption, of 3056 students who were screened initially [the Susceptibility Addiction Gene Environment (SAGE) study]. Positive and negative effects of first cannabis consumptions, present cannabis dependence and related risk factors were assessed through questionnaires.   The effects of first cannabis consumptions were associated dose-dependently with cannabis dependence at age 18-21 years, both according to the transversal approach of the SAGE study and to the prospective cohort of the Christchurch Health and Development Study (CHDS) assessed at the age of 25 years. Participants of the SAGE study who reported five positive effects of their first cannabis consumption had odds of life-time cannabis dependence that were 28.7 (95% confidence interval: 14.6-56.5) higher than those who reported no positive effects. This association remains significant after controlling for potentially confounding factors, including individual and familial variables. This study suggests an association between positive reactions to first cannabis uses and risk of life-time cannabis dependence, this variable having a central role among, and through, other risk factors. © 2009 The Authors. Journal compilation © 2009 Society for the Study of Addiction.

The factors of retail brand positioning

Directory of Open Access Journals (Sweden)

Filipović Vinka

2010-01-01

Full Text Available This paper gives the basic characteristics of a retail process as a function of the development of a successful brand. The retail network is continuously progressing, developing its abilities, successfully adjusting to its environment, and which is the most important it is persistently following wishes and needs of its consumers, and is satisfying them through high-quality offers. The retail network is relatively a new business structure, which has a great potential for competitive advantage. Once, prestigious partners to retailers, which have represented successful brands, they are often perceived to be stripped of rank and to come back at the level of common suppliers. Also, the suppliers' brands have no longer the position as they had, their status has decreased and their former power is gone, as a more superior, compared to the retailers. The inertia, enjoying 'the old glory', thinking in the manner of the same well-established formula as well as the inability to adjust themselves to the changes occurring among consumers have led the majority of the brands to be stuck in the past. The companies have to stop this increasing phenomenon, if they do not want to face in the near future, even more dramatic and more harmful consequences. Since the main aim of the research, performed in this work, was to determine the importance of retail brand positioning, the retail environment was analyzed, with special emphases on the consumer role in retail, and factors of successful retail activities. As a special aspect of successful retail, the environment of retail place was determined and within this, the effects of the retail places' atmosphere. For setting the retail strategy framework, the following basic entities are observed: product, price, exclusivity, quick response, information technology, price strategy, logistics and competitiveness. .

Factor Structure and Initial Validation of a Multidimensional Measure of Difficulties in the Regulation of Positive Emotions: The DERS-Positive.

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Weiss, Nicole H; Gratz, Kim L; Lavender, Jason M

2015-05-01

Emotion regulation difficulties are a transdiagnostic construct relevant to numerous clinical difficulties. Although the Difficulties in Emotion Regulation Scale (DERS) is a multidimensional measure of maladaptive ways of responding to emotions, it focuses on difficulties with the regulation of negative emotions and does not assess emotion dysregulation in the form of problematic responding to positive emotions. The aim of this study was to develop and validate a measure of clinically relevant difficulties in the regulation of positive emotions (DERS-Positive). Findings revealed a three-factor structure and supported the internal consistency and construct validity of the total and subscale scores. © The Author(s) 2015.

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...

Going to sleep in the supine position is a modifiable risk factor for late pregnancy stillbirth; Findings from the New Zealand multicentre stillbirth case-control study.

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Lesley M E McCowan

Full Text Available Our objective was to test the primary hypothesis that maternal non-left, in particular supine going-to-sleep position, would be a risk factor for late stillbirth (≥28 weeks of gestation.A multicentre case-control study was conducted in seven New Zealand health regions, between February 2012 and December 2015. Cases (n = 164 were women with singleton pregnancies and late stillbirth, without congenital abnormality. Controls (n = 569 were women with on-going singleton pregnancies, randomly selected and frequency matched for health region and gestation. The primary outcome was adjusted odds of late stillbirth associated with self-reported going-to-sleep position, on the last night. The last night was the night before the late stillbirth was thought to have occurred or the night before interview for controls. Going-to-sleep position on the last night was categorised as: supine, left-side, right-side, propped or restless. Multivariable logistic regression adjusted for known confounders.Supine going-to-sleep position on the last night was associated with increased late stillbirth risk (adjusted odds ratios (aOR 3.67, 95% confidence interval (CI 1.74 to 7.78 with a population attributable risk of 9.4%. Other independent risk factors for late stillbirth (aOR, 95% CI were: BMI (1.04, 1.01 to 1.08 per unit, maternal age ≥40 (2.88, 1.31 to 6.32, birthweight <10th customised centile (2.76, 1.59 to 4.80, and <6 hours sleep on the last night (1.81, 1.14 to 2.88. The risk associated with supine-going-to-sleep position was greater for term (aOR 10.26, 3.00 to 35.04 than preterm stillbirths (aOR 3.12, 0.97 to 10.05.Supine going-to-sleep position is associated with a 3.7 fold increase in overall late stillbirth risk, independent of other common risk factors. A public health campaign encouraging women not to go-to-sleep supine in the third trimester has potential to reduce late stillbirth by approximately 9%.

Mortality risk prediction in burn injury: Comparison of logistic regression with machine learning approaches.

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Stylianou, Neophytos; Akbarov, Artur; Kontopantelis, Evangelos; Buchan, Iain; Dunn, Ken W

2015-08-01

Predicting mortality from burn injury has traditionally employed logistic regression models. Alternative machine learning methods have been introduced in some areas of clinical prediction as the necessary software and computational facilities have become accessible. Here we compare logistic regression and machine learning predictions of mortality from burn. An established logistic mortality model was compared to machine learning methods (artificial neural network, support vector machine, random forests and naïve Bayes) using a population-based (England & Wales) case-cohort registry. Predictive evaluation used: area under the receiver operating characteristic curve; sensitivity; specificity; positive predictive value and Youden's index. All methods had comparable discriminatory abilities, similar sensitivities, specificities and positive predictive values. Although some machine learning methods performed marginally better than logistic regression the differences were seldom statistically significant and clinically insubstantial. Random forests were marginally better for high positive predictive value and reasonable sensitivity. Neural networks yielded slightly better prediction overall. Logistic regression gives an optimal mix of performance and interpretability. The established logistic regression model of burn mortality performs well against more complex alternatives. Clinical prediction with a small set of strong, stable, independent predictors is unlikely to gain much from machine learning outside specialist research contexts. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.

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.

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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

Risk factors for low birth weight according to the multiple logistic regression model. A retrospective cohort study in José María Morelos municipality, Quintana Roo, Mexico.

Science.gov (United States)

Franco Monsreal, José; Tun Cobos, Miriam Del Ruby; Hernández Gómez, José Ricardo; Serralta Peraza, Lidia Esther Del Socorro

2018-01-17

Low birth weight has been an enigma for science over time. There have been many researches on its causes and its effects. Low birth weight is an indicator that predicts the probability of a child surviving. In fact, there is an exponential relationship between weight deficit, gestational age, and perinatal mortality. Multiple logistic regression is one of the most expressive and versatile statistical instruments available for the analysis of data in both clinical and epidemiology settings, as well as in public health. To assess in a multivariate fashion the importance of 17 independent variables in low birth weight (dependent variable) of children born in the Mayan municipality of José María Morelos, Quintana Roo, Mexico. Analytical observational epidemiological cohort study with retrospective temporality. Births that met the inclusion criteria occurred in the "Hospital Integral Jose Maria Morelos" of the Ministry of Health corresponding to the Maya municipality of Jose Maria Morelos during the period from August 1, 2014 to July 31, 2015. The total number of newborns recorded was 1,147; 84 of which (7.32%) had low birth weight. To estimate the independent association between the explanatory variables (potential risk factors) and the response variable, a multiple logistic regression analysis was performed using the IBM SPSS Statistics 22 software. In ascending numerical order values of odds ratio > 1 indicated the positive contribution of explanatory variables or possible risk factors: "unmarried" marital status (1.076, 95% confidence interval: 0.550 to 2.104); age at menarche ≤ 12 years (1.08, 95% confidence interval: 0.64 to 1.84); history of abortion(s) (1.14, 95% confidence interval: 0.44 to 2.93); maternal weight < 50 kg (1.51, 95% confidence interval: 0.83 to 2.76); number of prenatal consultations ≤ 5 (1.86, 95% confidence interval: 0.94 to 3.66); maternal age ≥ 36 years (3.5, 95% confidence interval: 0.40 to 30.47); maternal age ≤ 19 years (3

Comparing the index-flood and multiple-regression methods using L-moments

Science.gov (United States)

Malekinezhad, H.; Nachtnebel, H. P.; Klik, A.

In arid and semi-arid regions, the length of records is usually too short to ensure reliable quantile estimates. Comparing index-flood and multiple-regression analyses based on L-moments was the main objective of this study. Factor analysis was applied to determine main influencing variables on flood magnitude. Ward’s cluster and L-moments approaches were applied to several sites in the Namak-Lake basin in central Iran to delineate homogeneous regions based on site characteristics. Homogeneity test was done using L-moments-based measures. Several distributions were fitted to the regional flood data and index-flood and multiple-regression methods as two regional flood frequency methods were compared. The results of factor analysis showed that length of main waterway, compactness coefficient, mean annual precipitation, and mean annual temperature were the main variables affecting flood magnitude. The study area was divided into three regions based on the Ward’s method of clustering approach. The homogeneity test based on L-moments showed that all three regions were acceptably homogeneous. Five distributions were fitted to the annual peak flood data of three homogeneous regions. Using the L-moment ratios and the Z-statistic criteria, GEV distribution was identified as the most robust distribution among five candidate distributions for all the proposed sub-regions of the study area, and in general, it was concluded that the generalised extreme value distribution was the best-fit distribution for every three regions. The relative root mean square error (RRMSE) measure was applied for evaluating the performance of the index-flood and multiple-regression methods in comparison with the curve fitting (plotting position) method. In general, index-flood method gives more reliable estimations for various flood magnitudes of different recurrence intervals. Therefore, this method should be adopted as regional flood frequency method for the study area and the Namak-Lake basin

IPF-LASSO: Integrative L1-Penalized Regression with Penalty Factors for Prediction Based on Multi-Omics Data

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Anne-Laure Boulesteix

2017-01-01

Full Text Available As modern biotechnologies advance, it has become increasingly frequent that different modalities of high-dimensional molecular data (termed “omics” data in this paper, such as gene expression, methylation, and copy number, are collected from the same patient cohort to predict the clinical outcome. While prediction based on omics data has been widely studied in the last fifteen years, little has been done in the statistical literature on the integration of multiple omics modalities to select a subset of variables for prediction, which is a critical task in personalized medicine. In this paper, we propose a simple penalized regression method to address this problem by assigning different penalty factors to different data modalities for feature selection and prediction. The penalty factors can be chosen in a fully data-driven fashion by cross-validation or by taking practical considerations into account. In simulation studies, we compare the prediction performance of our approach, called IPF-LASSO (Integrative LASSO with Penalty Factors and implemented in the R package ipflasso, with the standard LASSO and sparse group LASSO. The use of IPF-LASSO is also illustrated through applications to two real-life cancer datasets. All data and codes are available on the companion website to ensure reproducibility.

Determinants of the probability of adopting quality protein maize (QPM technology in Tanzania: A logistic regression analysis

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Gregory, T.

2013-06-01

Full Text Available Adoption of technology is an important factor in economic development. The thrust of this study was to establish factors affecting adoption of QPM technology in Northern zone of Tanzania. Primary data was collected from a random sample of 120 smallholder maize farmers in four villages. Data collected were analysed using descriptive and quantitative methods. Logit model was used to determine factors that influence adoption of QPM technology. The regression results indicated that education of the household head, farmers’ participation on demonstration trials, attendance to field days, and numbers of livestock owned have positively influenced the rate of adoption of the technology. Access to credit, and poor QPM marketing problem perception by farmers negatively influenced the rate of adoption. The study recommended government to ensure efficiency input-output linkage for QPM production.

Effects of measurement errors on psychometric measurements in ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis, and linear discriminant analysis.

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Liu, Yan; Salvendy, Gavriel

2009-05-01

This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.

[A new method of calibration and positioning in quantitative analysis of multicomponents by single marker].

Science.gov (United States)

He, Bing; Yang, Shi-Yan; Zhang, Yan

2012-12-01

This paper aims to establish a new method of calibration and positioning in quantitative analysis of multicomponents by single marker (QAMS), using Shuanghuanglian oral liquid as the research object. Establishing relative correction factors with reference chlorogenic acid to other 11 active components (neochlorogenic acid, cryptochlorogenic acid, cafferic acid, forsythoside A, scutellarin, isochlorogenic acid B, isochlorogenic acid A, isochlorogenic acid C, baicalin and phillyrin wogonoside) in Shuanghuanglian oral liquid by 3 correction methods (multipoint correction, slope correction and quantitative factor correction). At the same time chromatographic peak was positioned by linear regression method. Only one standard uas used to determine the content of 12 components in Shuanghuanglian oral liquid, in stead of needing too many reference substance in quality control. The results showed that within the linear ranges, no significant differences were found in the quantitative results of 12 active constituents in 3 batches of Shuanghuanglian oral liquid determined by 3 correction methods and external standard method (ESM) or standard curve method (SCM). And this method is simpler and quicker than literature methods. The results were accurate and reliable, and had good reproducibility. While the positioning chromatographic peaks by linear regression method was more accurate than relative retention time in literature. The slope and the quantitative factor correction controlling the quality of Chinese traditional medicine is feasible and accurate.

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...

Incidence and risk factors of AIDS-defining cancers in a cohort of HIV-positive adults: Importance of the definition of incident cases.

Science.gov (United States)

Suárez-García, Inés; Jarrín, Inmaculada; Iribarren, José Antonio; López-Cortés, Luis Fernando; Lacruz-Rodrigo, José; Masiá, Mar; Gómez-Sirvent, Juan Luis; Hernández-Quero, José; Vidal, Francesc; Alejos-Ferreras, Belén; Moreno, Santiago; Del Amo, Julia

2013-05-01

The aim of this study was to investigate the incidence and risk factors for the development of AIDS-defining cancers (ADCs); and to investigate the effect of making different assumptions on the definition of incident cases. A multicentre cohort study was designed. Poisson regression was used to assess incidence and risk factors. To account for misclassification, incident cases were defined using lag-times of 0, 14 and 30 days after enrolment. A total of 6393 HIV-positive subjects were included in the study. The incidences of ADCs changed as the lag periods were varied from 0 to 30 days. Different risk factors emerged as the definition of incident cases was changed. For a lag time of 0, the risk of Kaposi sarcoma [KS] and non-Hodgkin lymphoma [NHL] increased at CD4 counts sex with men had a higher risk of KS. KS and NHL were not associated with viral load, gender, or hepatitis B or C. The results were similar for a lag-time of 14 and 30 days; however, hepatitis C was significantly associated with NHL. This analysis shows the importance of the definition of incident cases in cohort studies. Alternative definitions gave different incidence estimates, and may have implications for the analysis of risk factors. Copyright © 2011 Elsevier España, S.L. All rights reserved.

A Quantile Regression Approach to Estimating the Distribution of Anesthetic Procedure Time during Induction.

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Hsin-Lun Wu

Full Text Available Although procedure time analyses are important for operating room management, it is not easy to extract useful information from clinical procedure time data. A novel approach was proposed to analyze procedure time during anesthetic induction. A two-step regression analysis was performed to explore influential factors of anesthetic induction time (AIT. Linear regression with stepwise model selection was used to select significant correlates of AIT and then quantile regression was employed to illustrate the dynamic relationships between AIT and selected variables at distinct quantiles. A total of 1,060 patients were analyzed. The first and second-year residents (R1-R2 required longer AIT than the third and fourth-year residents and attending anesthesiologists (p = 0.006. Factors prolonging AIT included American Society of Anesthesiologist physical status ≧ III, arterial, central venous and epidural catheterization, and use of bronchoscopy. Presence of surgeon before induction would decrease AIT (p < 0.001. Types of surgery also had significant influence on AIT. Quantile regression satisfactorily estimated extra time needed to complete induction for each influential factor at distinct quantiles. Our analysis on AIT demonstrated the benefit of quantile regression analysis to provide more comprehensive view of the relationships between procedure time and related factors. This novel two-step regression approach has potential applications to procedure time analysis in operating room management.

Factorization and dilation problems for completely positive maps on von Neumann algebras

DEFF Research Database (Denmark)

Haagerup, Uffe; Musat, Magdalena

2011-01-01

We study factorization and dilation properties of Markov maps between von Neumann algebras equipped with normal faithful states, i.e., completely positive unital maps which preserve the given states and also intertwine their automorphism groups. The starting point for our investigation has been...

Forecasting peak asthma admissions in London: an application of quantile regression models

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Soyiri, Ireneous N.; Reidpath, Daniel D.; Sarran, Christophe

2013-07-01

Asthma is a chronic condition of great public health concern globally. The associated morbidity, mortality and healthcare utilisation place an enormous burden on healthcare infrastructure and services. This study demonstrates a multistage quantile regression approach to predicting excess demand for health care services in the form of asthma daily admissions in London, using retrospective data from the Hospital Episode Statistics, weather and air quality. Trivariate quantile regression models (QRM) of asthma daily admissions were fitted to a 14-day range of lags of environmental factors, accounting for seasonality in a hold-in sample of the data. Representative lags were pooled to form multivariate predictive models, selected through a systematic backward stepwise reduction approach. Models were cross-validated using a hold-out sample of the data, and their respective root mean square error measures, sensitivity, specificity and predictive values compared. Two of the predictive models were able to detect extreme number of daily asthma admissions at sensitivity levels of 76 % and 62 %, as well as specificities of 66 % and 76 %. Their positive predictive values were slightly higher for the hold-out sample (29 % and 28 %) than for the hold-in model development sample (16 % and 18 %). QRMs can be used in multistage to select suitable variables to forecast extreme asthma events. The associations between asthma and environmental factors, including temperature, ozone and carbon monoxide can be exploited in predicting future events using QRMs.

Multitask Quantile Regression under the Transnormal Model.

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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.

[Clinical investigation of the positioning accuracy of acute pulpitis pain].

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Wang, Jin; Sun, Wei; Ji, Aiping

2013-10-01

This study aims to investigate the positioning accuracy of acute pulpitis pain and its possible factors. The clinical symptoms and physical signs of 3 432 cases of acute pulpitis were recorded and analyzed by using questionnaire forms, which included age, gender, tooth position, infection origin, pain history, time of acute attack, duration and nature of pain, pain frequency, referred pain areas, percussion examination, temperature pulp test, pulp bleeding, and positioning accuracy. Univariate analysis and multivariate stepwise regression analysis were used for data processing. Pain location was accurately identified by 39.1% of the patients with acute pulpitis. Referred pain could reduce the positioning accuracy of pain (P 0.05). Some cases of acute pulpitis pain can be located accurately. Referred pain and periodontium infection origin are related to the positioning accuracy of acute pulpitis pain. The exact cause of this correlation needs further study.

Research and analyze of physical health using multiple regression analysis

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T. S. Kyi

2014-01-01

Full Text Available This paper represents the research which is trying to create a mathematical model of the "healthy people" using the method of regression analysis. The factors are the physical parameters of the person (such as heart rate, lung capacity, blood pressure, breath holding, weight height coefficient, flexibility of the spine, muscles of the shoulder belt, abdominal muscles, squatting, etc.., and the response variable is an indicator of physical working capacity. After performing multiple regression analysis, obtained useful multiple regression models that can predict the physical performance of boys the aged of fourteen to seventeen years. This paper represents the development of regression model for the sixteen year old boys and analyzed results.

Critical success factors for positive user experience in hotel websites:applying Herzberg’s two factor theory for user experience modeling

OpenAIRE

Sambhanthan, Arunasalam; Good, Alice

2013-01-01

This research presents the development of a critical success factor matrix for increasing positive user experience of hotel websites based upon user ratings. Firstly, a number of critical success factors for web usability have been identified through the initial literature review. Secondly, hotel websites were surveyed in terms of critical success factors identified through the literature review. Thirdly, Herzberg’s motivation theory has been applied to the user rating and the critical succ...

Bounded real and positive real balanced truncation using Σ-normalised coprime factors

NARCIS (Netherlands)

Trentelman, H.L.

2009-01-01

In this article, we will extend the method of balanced truncation using normalised right coprime factors of the system transfer matrix to balanced truncation with preservation of half line dissipativity. Special cases are preservation of positive realness and bounded realness. We consider a half

Factors that enable nurse-patient communication in a family planning context: a positive deviance study.

Science.gov (United States)

Kim, Young Mi; Heerey, Michelle; Kols, Adrienne

2008-10-01

Family planning programmes in developing countries need a better understanding of nurse-patient communication in order to improve the quality of counselling. To identify factors in the clinic and in the community that enable nurses and patients to communicate effectively with one another. The study explored the personal experiences of nurses and patients who communicate especially effectively during family planning consultations (so-called "positive deviants"). Sixty-four randomly selected public clinics located in East Java, Indonesia. Seven positive deviant nurses and 32 positive deviant patients were identified from among 64 nurses and 768 patients who participated in an earlier patient coaching study. Flooding prevented 5 patients from participating in the study, reducing their number to 27. Investigators conducted: (1) a content analysis of qualitative data collected by structured in-depth interviews and focus-group discussions (FGDs) with positive deviant nurses and patients, and (2) analyses of variance (ANOVA) of quantitative data on clinic, nurse, and patient characteristics. Positive deviant nurses identified four factors, listed in rough order of importance, that helped them communicate effectively: independent study to strengthen their knowledge and skills; communication aids; feedback from colleagues; and motivation stemming from a desire to help people, patients' appreciation, husband's support, and increased income. Positive deviant patients identified five enabling factors: motivation due to their need for a service; confidence in their own communication skills; positive feedback from nurses; belief in patients' right and responsibility to communicate with nurses; and communication aids. Insights from positive deviant nurses and patients suggest that efforts to improve nurse-patient communication should go beyond conventional communication skills training. Managers should consider a mix of clinic-based interventions (such as peer feedback

Boosted beta regression.

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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.

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.

Prevalence of and risk factors for MRSA colonization in HIV-positive outpatients in Singapore

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Kyaw Win

2012-11-01

Full Text Available Abstract Background Whilst there have been studies on the risks and outcomes of MRSA colonization and infections in HIV-positive patients, local data is limited on the risk factors for MRSA colonization among these patients. We undertook this study in a tertiary HIV care centre to document the risk factors for colonization and to determine the prevalence of MRSA colonization among HIV-positive outpatients in Singapore. Methods This was a cross-sectional study in which factors associated with MRSA positivity among patients with HIV infection were evaluated. A set of standardized questionnaire and data collection forms were available to interview all recruited patients. Following the interview, trained nurses collected swabs from the anterior nares/axilla/groin (NAG, throat and peri-anal regions. Information on demographics, clinical history, laboratory results and hospitalization history were retrieved from medical records. Results MRSA was detected in swab cultures from at least 1 site in 15 patients (5.1%. Inclusion of throat and/or peri-anal swabs increased the sensitivity of NAG screening by 20%. Predictors for MRSA colonization among HIV-positive patients were age, history of pneumonia, lymphoma, presence of a percutaneous device within the past 12 months, history of household members hospitalized more than two times within the past 12 months, and a most recent CD4 count less than 200. Conclusions This study highlights that a proportion of MRSA carriers would have been undetected without multiple-site screening cultures. This study could shed insight into identifying patients at risk of MRSA colonization upon hospital visit and this may suggest that a risk factor-based approach for MRSA surveillance focusing on high risk populations could be considered.

Whole pelvis radiotherapy for pathological node-positive prostate cancer. Oncological outcome and prognostic factors

Energy Technology Data Exchange (ETDEWEB)

Poelaert, Filip; Decaestecker, Karel; Claeys, Tom; Dhondt, Bert; Lumen, Nicolaas [Ghent University Hospital, Department of Urology, Ghent (Belgium); Fonteyne, Valerie; Ost, Piet [Ghent University Hospital, Department of Radiation Oncology, Ghent (Belgium); Troyer, Bart de [AZ Nikolaas, Department of Urology, Sint-Niklaas (Belgium); Meerleer, Gert de [University Hospitals Leuven, Department of Radiation Oncology, Leuven (Belgium); Visschere, Pieter de [Ghent University Hospital, Department of Radiology, Ghent (Belgium)

2017-06-15

The goal of this work was to investigate the oncological outcome of whole pelvis radiotherapy (wpRT) in pathologic pelvic lymph node-positive (pN1) prostate cancer (PCa), evaluate the location of relapse, and identify potential prognostic factors. All patients undergoing pelvic lymph node dissection (PLND) since the year 2000 at a single tertiary care center were evaluated. A total of 154 patients with pN1 PCa were treated with wpRT (39 in an adjuvant setting) and 2-3 years of androgen deprivation therapy (ADT). Kaplan-Meier analysis was performed to estimate biochemical recurrence-free survival (bRFS), clinical progression-free survival (cPFS), and prostate cancer-specific survival (CSS). Uni- and multivariate regression analyses were performed to identify prognostic factors. Estimated bRFS was 67%, cPFS was 71%, and CSS was 96% at 5 years. Median follow-up was 55 months (interquartile range 25-87). Multivariate analysis identified having only 1 positive lymph node, a shorter time between diagnosis and PLND, and older age as independent favorable prognostic factors for biochemical and clinical recurrence. The number of positive lymph nodes was prognostic for CSS (hazard ratio [HR] 1.34, 95% confidence interval 1.17-1.54) and OS (HR 1.22, 95% confidence interval 1.10-1.36). Bone metastases were the most frequent location of PCa relapse (n = 32, 64%). Patients with pN1 PCa treated with wpRT and 2-3 years ADT have an encouraging 5-year CSS. Understaging of the disease extent may be the most important enemy in definitive pN1 PCa treatment. (orig.) [German] Das Ziel dieser Studie war es, das onkologische Outcome der Bestrahlung des gesamten Beckens (wpRT) beim histologisch gesicherten nodal metastasierten Prostatakarzinom zu untersuchen, die Lokalisation eines eventuellen Rezidivs zu charakterisieren und moegliche prognostische Faktoren zu identifizieren. Alle Patienten, bei denen seit dem Jahr 2000 eine pelvine Lymphknotendissektion (PLND) durchgefuehrt worden war

Identifying the Factors That Influence Change in SEBD Using Logistic Regression Analysis

Science.gov (United States)

Camilleri, Liberato; Cefai, Carmel

2013-01-01

Multiple linear regression and ANOVA models are widely used in applications since they provide effective statistical tools for assessing the relationship between a continuous dependent variable and several predictors. However these models rely heavily on linearity and normality assumptions and they do not accommodate categorical dependent…

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...

Time to sputum conversion in smear positive pulmonary TB patients on category I DOTS and factors delaying it.

Science.gov (United States)

Parikh, Raunak; Nataraj, Gita; Kanade, Swapna; Khatri, Vijay; Mehta, Preeti

2012-08-01

Sputum smear positive pulmonary tuberculosis patients expel infectious viable bacilli for a period following commencement of treatment. Patients on Directly Observed Treatment Shortcourse (DOTS) receive intermittent therapy with multidrug regimen. To determine the time to sputum smear and culture conversion following initiation of DOTS treatment and study the factors that influence it. A prospective study was undertaken at a tertiary care teaching hospital in Mumbai over a one year period on a cohort of 71 sputum smear positive patients on Category I DOTS treatment. Patients were followed up weekly for upto 20 weeks or until they underwent smear and culture conversion whichever was earlier. At each follow up, specimens were collected and processed for microscopy and culture using standard protocol. 60/71 [84.55%] patients completed the study. 56/60 [93.3%] patients underwent sputum smear and culture conversion. The median time to smear and culture conversion was end of 5th week [day 35] and 6 1/2 weeks [day 45] respectively. Univariate and stepwise regression analysis showed that patients who had cavitatory disease, high pretreatment smear grade and a past history of tuberculosis were more likely to undergo delayed or nonconversion [P culture conversion under DOTS is similar to previous antituberculosis regimens. Since viable bacilli continue to be expelled for upto two months, infection control measures should be maintained for such time. Patients with cavitatory disease, high pretreatment smear grade or a past history of tuberculosis need to be monitored more closely.

Simulation Experiments in Practice: Statistical Design and Regression Analysis

OpenAIRE

Kleijnen, J.P.C.

2007-01-01

In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. The goal of this article is to change these traditional, naïve methods of design and analysis, because statistical theory proves that more information is obtained when applying Design Of Experiments (DOE) and linear regression analysis. Unfortunately, classic DOE and regression analysis assume a single simulation response that is normally and independen...

Vascular endothelial growth factor and basic fibroblast growth factor expression positively correlates with angiogenesis and peritumoural brain oedema in astrocytoma

International Nuclear Information System (INIS)

Jang, F.F.; Wei, W.

2008-01-01

Astrocytoma is the most malignant intracranial neoplasm and is characterized by high neovascularization and peritumoural brain oedema. Angiogenesis is a complicated process in oncogenesis regulated by the balance between angiogenic and antiangiogenic factors. The expression of two angiogenic growth factors, vascular endothelial growth factor and basic fibroblast growth factor were investigated using immunohistochemistry for astrocytoma from 82 patients and 11 normal human tissues. The expression of vascular endothelial growth factor and basic fibroblast growth factor positively correlate with the pathological grade of astrocytoma, microvessel density numbers and brain oedema, which may be responsible for the increased tumour neovascularization and peritumoural brain oedema. The results support the idea that inhibiting vascular endothelial growth factor and basic fibroblast growth factor are useful for the treatment of human astrocytoma and to improve patient's clinical outcomes and prognosis. (author)

Analysis of the Risk of Company's Bankruptcy in Polish Food and Beverage Production Sector Using the Cox Regression

Directory of Open Access Journals (Sweden)

Przemysław Dominiak

2011-01-01

Full Text Available Analysis of the risk of a company’s bankruptcy in Polish food and beverages production sector (NACE, No. 15 has been carried out using econometric modelling in the form of the Cox regression. The purpose of this paper was to find factors (models describing the risk of a company’s bankruptcy. The described approach to modelling of the risk of bankruptcy is – in the case of quantitative variables – the use of “raw” positions from financial accounts. (original abstract

Regression formulae for predicting hematologic and liver functions ...

African Journals Online (AJOL)

African Journal of Biomedical Research ... On the other hand platelet and white blood cell (WBC) counts in these workers correlated positively with years of service [r = 0.342 (P <0.001) and r = 0.130 (P<0.0001) ... The regression equation defining this relationship is: ALP concentration = 33.68 – 0.075 x years of service.

Educational and individual factors associated with positive change in and reaffirmation of medical students' intention to practice in underserved areas.

Science.gov (United States)

Boscardin, Christy K; Grbic, Douglas; Grumbach, Kevin; O'Sullivan, Patricia

2014-11-01

The projected U.S. physician shortage will disproportionately affect underserved areas. This study examined the impact of medical school educational experiences on positive changes in and reaffirmation of students' intention to practice in underserved areas (practice intention). Medical students (n = 7,361) from 113 U.S. MD-granting medical schools who graduated in 2009-2010 and responded to both the Association of American Medical Colleges' 2006 Matriculating Student Questionnaire and 2010 Graduation Questionnaire were included. Multilevel logistic regression analyses were conducted to determine factors associated with change in and reaffirmation of practice intention. After controlling for individual characteristics, community health field experience (adjusted odds ratio [OR]: 1.36; 95% CI: 1.18, 1.57), learning another language (OR: 1.41; 95% CI: 1.22, 1.63), cultural competence/awareness experience (OR: 1.38; 95% CI: 1.21, 1.58), becoming more aware of perspectives of individuals from different backgrounds (OR: 1.24; 95% CI: 1.04, 1.48), and attending schools with higher social mission scores (OR: 1.66; 95% CI: 1.28, 2.16) were all significantly associated with positive changes in practice intention from matriculation to graduation. Field experience in community health (OR: 1.24; 95% CI: 0.99, 1.53), learning another language (OR: 1.29; 95% CI: 1.01, 1.65), and attending schools with higher social mission scores (OR: 1.62; 95% CI: 1.09, 2.43) were all significantly associated with reaffirmation of practice intention at graduation. Multifaceted factors are associated with practice intention. This study suggests medical schools can play active roles in alleviating the physician shortage in underserved areas through targeted curricular interventions and recruitment.

Linear regression analysis: part 14 of a series on evaluation of scientific publications.

Science.gov (United States)

Schneider, Astrid; Hommel, Gerhard; Blettner, Maria

2010-11-01

Regression analysis is an important statistical method for the analysis of medical data. It enables the identification and characterization of relationships among multiple factors. It also enables the identification of prognostically relevant risk factors and the calculation of risk scores for individual prognostication. This article is based on selected textbooks of statistics, a selective review of the literature, and our own experience. After a brief introduction of the uni- and multivariable regression models, illustrative examples are given to explain what the important considerations are before a regression analysis is performed, and how the results should be interpreted. The reader should then be able to judge whether the method has been used correctly and interpret the results appropriately. The performance and interpretation of linear regression analysis are subject to a variety of pitfalls, which are discussed here in detail. The reader is made aware of common errors of interpretation through practical examples. Both the opportunities for applying linear regression analysis and its limitations are presented.

The effect of journal impact factor, reporting conflicts, and reporting funding sources, on standardized effect sizes in back pain trials: a systematic review and meta-regression.

Science.gov (United States)

Froud, Robert; Bjørkli, Tom; Bright, Philip; Rajendran, Dévan; Buchbinder, Rachelle; Underwood, Martin; Evans, David; Eldridge, Sandra

2015-11-30

Low back pain is a common and costly health complaint for which there are several moderately effective treatments. In some fields there is evidence that funder and financial conflicts are associated with trial outcomes. It is not clear whether effect sizes in back pain trials relate to journal impact factor, reporting conflicts of interest, or reporting funding. We performed a systematic review of English-language papers reporting randomised controlled trials of treatments for non-specific low back pain, published between 2006-2012. We modelled the relationship using 5-year journal impact factor, and categories of reported of conflicts of interest, and categories of reported funding (reported none and reported some, compared to not reporting these) using meta-regression, adjusting for sample size, and publication year. We also considered whether impact factor could be predicted by the direction of outcome, or trial sample size. We could abstract data to calculate effect size in 99 of 146 trials that met our inclusion criteria. Effect size is not associated with impact factor, reporting of funding source, or reporting of conflicts of interest. However, explicitly reporting 'no trial funding' is strongly associated with larger absolute values of effect size (adjusted β=1.02 (95 % CI 0.44 to 1.59), P=0.001). Impact factor increases by 0.008 (0.004 to 0.012) per unit increase in trial sample size (Psources of funding, and conflicts of interest reflects positively on research and publisher conduct in the field. Strong evidence of a large association between absolute magnitude of effect size and explicit reporting of 'no funding' suggests authors of unfunded trials are likely to report larger effect sizes, notwithstanding direction. This could relate in part to quality, resources, and/or how pragmatic a trial is.

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.

Statistical and regression analyses of detected extrasolar systems

Czech Academy of Sciences Publication Activity Database

Pintr, Pavel; Peřinová, V.; Lukš, A.; Pathak, A.

2013-01-01

Roč. 75, č. 1 (2013), s. 37-45 ISSN 0032-0633 Institutional support: RVO:61389021 Keywords : Exoplanets * Kepler candidates * Regression analysis Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 1.630, year: 2013 http://www.sciencedirect.com/science/article/pii/S0032063312003066

Building a new predictor for multiple linear regression technique-based corrective maintenance turnaround time.

Science.gov (United States)

Cruz, Antonio M; Barr, Cameron; Puñales-Pozo, Elsa

2008-01-01

This research's main goals were to build a predictor for a turnaround time (TAT) indicator for estimating its values and use a numerical clustering technique for finding possible causes of undesirable TAT values. The following stages were used: domain understanding, data characterisation and sample reduction and insight characterisation. Building the TAT indicator multiple linear regression predictor and clustering techniques were used for improving corrective maintenance task efficiency in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). Multiple linear regression was used for building a predictive TAT value model. The variables contributing to such model were clinical engineering department response time (CE(rt), 0.415 positive coefficient), stock service response time (Stock(rt), 0.734 positive coefficient), priority level (0.21 positive coefficient) and service time (0.06 positive coefficient). The regression process showed heavy reliance on Stock(rt), CE(rt) and priority, in that order. Clustering techniques revealed the main causes of high TAT values. This examination has provided a means for analysing current technical service quality and effectiveness. In doing so, it has demonstrated a process for identifying areas and methods of improvement and a model against which to analyse these methods' effectiveness.

Investigating the effects of climate variations on bacillary dysentery incidence in northeast China using ridge regression and hierarchical cluster analysis

Directory of Open Access Journals (Sweden)

Guo Junqiao

2008-09-01

Full Text Available Abstract Background The effects of climate variations on bacillary dysentery incidence have gained more recent concern. However, the multi-collinearity among meteorological factors affects the accuracy of correlation with bacillary dysentery incidence. Methods As a remedy, a modified method to combine ridge regression and hierarchical cluster analysis was proposed for investigating the effects of climate variations on bacillary dysentery incidence in northeast China. Results All weather indicators, temperatures, precipitation, evaporation and relative humidity have shown positive correlation with the monthly incidence of bacillary dysentery, while air pressure had a negative correlation with the incidence. Ridge regression and hierarchical cluster analysis showed that during 1987–1996, relative humidity, temperatures and air pressure affected the transmission of the bacillary dysentery. During this period, all meteorological factors were divided into three categories. Relative humidity and precipitation belonged to one class, temperature indexes and evaporation belonged to another class, and air pressure was the third class. Conclusion Meteorological factors have affected the transmission of bacillary dysentery in northeast China. Bacillary dysentery prevention and control would benefit from by giving more consideration to local climate variations.

Factors associated with specific causes of death amongst HIV-positive individuals in the D:A:D Study

DEFF Research Database (Denmark)

Smith, Colette; Sabin, Caroline A; Lundgren, Jens D

2010-01-01

To investigate any emerging trends in causes of death amongst HIV-positive individuals in the current cART era, and to investigate the factors associated with each specific cause of death.......To investigate any emerging trends in causes of death amongst HIV-positive individuals in the current cART era, and to investigate the factors associated with each specific cause of death....

Mitigating Errors in External Respiratory Surrogate-Based Models of Tumor Position

International Nuclear Information System (INIS)

Malinowski, Kathleen T.; McAvoy, Thomas J.; George, Rohini; Dieterich, Sonja; D'Souza, Warren D.

2012-01-01

Purpose: To investigate the effect of tumor site, measurement precision, tumor–surrogate correlation, training data selection, model design, and interpatient and interfraction variations on the accuracy of external marker-based models of tumor position. Methods and Materials: Cyberknife Synchrony system log files comprising synchronously acquired positions of external markers and the tumor from 167 treatment fractions were analyzed. The accuracy of Synchrony, ordinary-least-squares regression, and partial-least-squares regression models for predicting the tumor position from the external markers was evaluated. The quantity and timing of the data used to build the predictive model were varied. The effects of tumor–surrogate correlation and the precision in both the tumor and the external surrogate position measurements were explored by adding noise to the data. Results: The tumor position prediction errors increased during the duration of a fraction. Increasing the training data quantities did not always lead to more accurate models. Adding uncorrelated noise to the external marker-based inputs degraded the tumor–surrogate correlation models by 16% for partial-least-squares and 57% for ordinary-least-squares. External marker and tumor position measurement errors led to tumor position prediction changes 0.3–3.6 times the magnitude of the measurement errors, varying widely with model algorithm. The tumor position prediction errors were significantly associated with the patient index but not with the fraction index or tumor site. Partial-least-squares was as accurate as Synchrony and more accurate than ordinary-least-squares. Conclusions: The accuracy of surrogate-based inferential models of tumor position was affected by all the investigated factors, except for the tumor site and fraction index.

Mitigating Errors in External Respiratory Surrogate-Based Models of Tumor Position

Energy Technology Data Exchange (ETDEWEB)

Malinowski, Kathleen T. [Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD (United States); Fischell Department of Bioengineering, University of Maryland, College Park, MD (United States); McAvoy, Thomas J. [Fischell Department of Bioengineering, University of Maryland, College Park, MD (United States); Department of Chemical and Biomolecular Engineering and Institute of Systems Research, University of Maryland, College Park, MD (United States); George, Rohini [Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD (United States); Dieterich, Sonja [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA (United States); D' Souza, Warren D., E-mail: wdsou001@umaryland.edu [Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD (United States); Fischell Department of Bioengineering, University of Maryland, College Park, MD (United States)

2012-04-01

Purpose: To investigate the effect of tumor site, measurement precision, tumor-surrogate correlation, training data selection, model design, and interpatient and interfraction variations on the accuracy of external marker-based models of tumor position. Methods and Materials: Cyberknife Synchrony system log files comprising synchronously acquired positions of external markers and the tumor from 167 treatment fractions were analyzed. The accuracy of Synchrony, ordinary-least-squares regression, and partial-least-squares regression models for predicting the tumor position from the external markers was evaluated. The quantity and timing of the data used to build the predictive model were varied. The effects of tumor-surrogate correlation and the precision in both the tumor and the external surrogate position measurements were explored by adding noise to the data. Results: The tumor position prediction errors increased during the duration of a fraction. Increasing the training data quantities did not always lead to more accurate models. Adding uncorrelated noise to the external marker-based inputs degraded the tumor-surrogate correlation models by 16% for partial-least-squares and 57% for ordinary-least-squares. External marker and tumor position measurement errors led to tumor position prediction changes 0.3-3.6 times the magnitude of the measurement errors, varying widely with model algorithm. The tumor position prediction errors were significantly associated with the patient index but not with the fraction index or tumor site. Partial-least-squares was as accurate as Synchrony and more accurate than ordinary-least-squares. Conclusions: The accuracy of surrogate-based inferential models of tumor position was affected by all the investigated factors, except for the tumor site and fraction index.

Directional quantile regression in Octave (and MATLAB)

Czech Academy of Sciences Publication Activity Database

Boček, Pavel; Šiman, Miroslav

2016-01-01

Roč. 52, č. 1 (2016), s. 28-51 ISSN 0023-5954 R&D Projects: GA ČR GA14-07234S Institutional support: RVO:67985556 Keywords : quantile regression * multivariate quantile * depth contour * Matlab Subject RIV: IN - Informatics, Computer Science Impact factor: 0.379, year: 2016 http://library.utia.cas.cz/separaty/2016/SI/bocek-0458380.pdf

Socioeconomic position and incidence of ischemic stroke in denmark 2003-2012. A nationwide hospital-based study

DEFF Research Database (Denmark)

Andersen, Klaus Kaae; Steding-Jessen, Marianne; Dalton, Susanne Oksbjerg

2014-01-01

BACKGROUND: A greater burden of stroke risk factors in general is associated with a higher risk for stroke among people of lower than those of higher socioeconomic position. The relative impact of individual stroke risk factors is still unclear. METHODS AND RESULTS: We studied the relations between...... socioeconomic position, measured as household income and length of education, and all hospital admissions for a first ischemic stroke among 54 048 people over the age of 40 years in Denmark in 2003-2012 in comparison with the general Danish population (23.5 million person-years). We also studied...... the cardiovascular risk factor profile associated with socioeconomic position in stroke patients. Relative risks for stroke were estimated in log-linear Poisson regression models. The risk for hospitalization for a first ischemic stroke was almost doubled for people in the lowest income group, and the risk of those...

Positive matrix factorization and trajectory modelling for source identification: A new look at Indian Ocean Experiment ship observations

Science.gov (United States)

Bhanuprasad, S. G.; Venkataraman, Chandra; Bhushan, Mani

The sources of aerosols on a regional scale over India have only recently received attention in studies using back trajectory analysis and chemical transport modelling. Receptor modelling approaches such as positive matrix factorization (PMF) and the potential source contribution function (PSCF) are effective tools in source identification of urban and regional-scale pollution. In this work, PMF and PSCF analysis is applied to identify categories and locations of sources that influenced surface concentrations of aerosols in the Indian Ocean Experiment (INDOEX) domain measured on-board the research vessel Ron Brown [Quinn, P.K., Coffman, D.J., Bates, T.S., Miller, T.L., Johnson, J.E., Welton, E.J., et al., 2002. Aerosol optical properties during INDOEX 1999: means, variability, and controlling factors. Journal of Geophysical Research 107, 8020, doi:10.1029/2000JD000037]. Emissions inventory information is used to identify sources co-located with probable source regions from PSCF. PMF analysis identified six factors influencing PM concentrations during the INDOEX cruise of the Ron Brown including a biomass combustion factor (35-40%), three industrial emissions factors (35-40%), primarily secondary sulphate-nitrate, balance trace elements and Zn, and two dust factors (20-30%) of Si- and Ca-dust. The identified factors effectively predict the measured submicron PM concentrations (slope of regression line=0.90±0.20; R2=0.76). Probable source regions shifted based on changes in surface and elevated flows during different times in the ship cruise. They were in India in the early part of the cruise, but in west Asia, south-east Asia and Africa, during later parts of the cruise. Co-located sources include coal-fired electric utilities, cement, metals and petroleum production in India and west Asia, biofuel combustion for energy and crop residue burning in India, woodland/forest burning in north sub-Saharan Africa and forest burning in south-east Asia. Significant findings

THE POSITION OF STUDENTS AND TEACHERS IN THE TEADHING OF CONFLICT AS A FACTOR IN COMMUNICATION

Directory of Open Access Journals (Sweden)

Perica Ivanek

2012-09-01

Full Text Available In this empirical paper we consider the problem of communication and interaction between students and teachers in the classroom, looking at it from the aspect of the position of students and teachers in everyday teaching practice. Namely, we wanted to examine the attitudes of students and teachers related to the position of students and teachers on the occurrence of misunderstandings and conflicts in the classroom. The sample on which the study was conducted was made of third grade secondary vocational schools and high schools and their teachers. Dependent variable is descriptive: the position of students and teachers as a factor of conflict in communication between students and teachers, divided in to two groups of indicators (first: indicators that help to prevent conflicts-objective subjective position of students, and other: indicators that initiate the sole objective position of students and subjective position of the teacher. Research results to some extent, we should give a clearer picture of which segments are different perceptions of students and teachers related to the position as a factor in any conflict and misunderstanding in communication between the direct participants in the teaching process.

Selecting the correct weighting factors for linear and quadratic calibration curves with least-squares regression algorithm in bioanalytical LC-MS/MS assays and impacts of using incorrect weighting factors on curve stability, data quality, and assay performance.

Science.gov (United States)

Gu, Huidong; Liu, Guowen; Wang, Jian; Aubry, Anne-Françoise; Arnold, Mark E

2014-09-16

A simple procedure for selecting the correct weighting factors for linear and quadratic calibration curves with least-squares regression algorithm in bioanalytical LC-MS/MS assays is reported. The correct weighting factor is determined by the relationship between the standard deviation of instrument responses (σ) and the concentrations (x). The weighting factor of 1, 1/x, or 1/x(2) should be selected if, over the entire concentration range, σ is a constant, σ(2) is proportional to x, or σ is proportional to x, respectively. For the first time, we demonstrated with detailed scientific reasoning, solid historical data, and convincing justification that 1/x(2) should always be used as the weighting factor for all bioanalytical LC-MS/MS assays. The impacts of using incorrect weighting factors on curve stability, data quality, and assay performance were thoroughly investigated. It was found that the most stable curve could be obtained when the correct weighting factor was used, whereas other curves using incorrect weighting factors were unstable. It was also found that there was a very insignificant impact on the concentrations reported with calibration curves using incorrect weighting factors as the concentrations were always reported with the passing curves which actually overlapped with or were very close to the curves using the correct weighting factor. However, the use of incorrect weighting factors did impact the assay performance significantly. Finally, the difference between the weighting factors of 1/x(2) and 1/y(2) was discussed. All of the findings can be generalized and applied into other quantitative analysis techniques using calibration curves with weighted least-squares regression algorithm.

Napsin A and Thyroid Transcription Factor-1-Positive Cerebellar Tumor with Epidermal Growth Factor Receptor Mutation

Directory of Open Access Journals (Sweden)

Taiji Kuwata

2011-12-01

Full Text Available We present a very rare case of cerebellar metastasis of unknown origin, in which a primary lung adenocarcinoma was diagnosed by pathological examination of a cerebellar metastatic tumor, using immunohistochemical markers and epidermal growth factor receptor (EGFR mutation of primary lung cancer. A 69-year-old woman was admitted to our hospital because of a hemorrhagic cerebellar tumor and multiple small brain tumors. She underwent cerebellar tumor resection. On pathological examination, the tumor was diagnosed as adenocarcinoma. However, the primary tumor site was unidentifiable even with several imaging inspections. On immunohistochemical analysis, the resected tumor was positive for napsin A and thyroid transcription factor-1. In addition, an EGFR mutation was detected in the tumor. Therefore, primary lung cancer was diagnosed and the patient was started on gefitinib (250 mg/day therapy.

Can slide positivity rates predict malaria transmission?

Directory of Open Access Journals (Sweden)

Bi Yan

2012-04-01

Full Text Available Abstract Background Malaria is a significant threat to population health in the border areas of Yunnan Province, China. How to accurately measure malaria transmission is an important issue. This study aimed to examine the role of slide positivity rates (SPR in malaria transmission in Mengla County, Yunnan Province, China. Methods Data on annual malaria cases, SPR and socio-economic factors for the period of 1993 to 2008 were obtained from the Center for Disease Control and Prevention (CDC and the Bureau of Statistics, Mengla, China. Multiple linear regression models were conducted to evaluate the relationship between socio-ecologic factors and malaria incidence. Results The results show that SPR was significantly positively associated with the malaria incidence rates. The SPR (β = 1.244, p = 0.000 alone and combination (SPR, β = 1.326, p  Conclusion SPR is a strong predictor of malaria transmission, and can be used to improve the planning and implementation of malaria elimination programmes in Mengla and other similar locations. SPR might also be a useful indicator of malaria early warning systems in China.

Socioeconomic position, lifestyle factors and age at natural menopause: a systematic review and meta-analyses of studies across six continents

Science.gov (United States)

Schoenaker, Danielle AJM; Jackson, Caroline A; Rowlands, Jemma V; Mishra, Gita D

2014-01-01

Background: Age at natural menopause (ANM) is considered a marker of biological ageing and is increasingly recognized as a sentinel for chronic disease risk in later life. Socioeconomic position (SEP) and lifestyle factors are thought to be associated with ANM. Methods: We performed a systematic review and meta-analyses to determine the overall mean ANM, and the effect of SEP and lifestyle factors on ANM by calculating the weighted mean difference (WMD) and pooling adjusted hazard ratios. We explored heterogeneity using meta-regression and also included unpublished findings from the Australian Longitudinal Study on Women’s Health. Results: We identified 46 studies across 24 countries. Mean ANM was 48.8 years [95% confidence interval (CI): 48.3, 49.2], with between-study heterogeneity partly explained by geographical region. ANM was lowest among African, Latin American, Asian and Middle Eastern countries and highest in Europe and Australia, followed by the USA. Education was associated with later ANM (WMD middle vs low education 0.30, 95% CI: 0.10, 0.51; high vs low education 0.64, 95% CI 0.26, 1.02). A similar dose-response relationship was also observed for occupation. Smoking was associated with a 1-year reduction of ANM (WMD: -0.91, 95% CI: –1.34, –0.48). Being overweight and moderate/high physical activity were modestly associated with later ANM, but findings were less conclusive. Conclusions: ANM varies across populations, partly due to differences across geographical regions. SEP and some lifestyle factors are associated with ANM, but further research is needed to examine the impact of the associations between risk factors and ANM on future health outcomes. PMID:24771324

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

European Food Safety Authority; Analysis of the baseline survey of Salmonella in holdings with breeding pigs, in the EU, 2008; Part B: Analysis of factors potentially associated with Salmonella pen positivity

DEFF Research Database (Denmark)

Hald, Tine

or slaughter (production holdings) were sampled. In each selected holding, pooled fresh faecal samples were collected from 10 randomly chosen pens of breeding pigs over six months of age, representing the different stages of the breeding herd, and examined for the presence of Salmonella. Analyses at country......, multivariable regression analysis showed that the odds of Salmonella-positive pens with pigs increased with the number of breeding pigs in the holding and with the following pen-level factors: flooring systems other than slatted floors or solid floors with straw, presence of maiden gilts, number of pigs per pen...

Early life-course socioeconomic position, adult work-related factors and oral health disparities: cross-sectional analysis of the J-SHINE study.

Science.gov (United States)

Tsuboya, Toru; Aida, Jun; Kawachi, Ichiro; Katase, Kazuo; Osaka, Ken

2014-10-03

We examined the association between socioeconomic position (SEP) and oral health, and the associations of economic difficulties in childhood and workplace-related factors on these parameters. Cross-sectional study. A total of 3201 workers aged 25-50 years, living in and around Tokyo, Japan, from the J-SHINE (Japanese study of Stratification, Health, Income, and Neighborhood) study. The response rate was 31.6%. Self-rated oral health (SROH)-A logistic regression model was used to estimate ORs for the association between poor SROH and each indicator of SEP (annual household income, wealth, educational attainment, occupation and economic situation in childhood). Multiple imputation was used to address missing values. Each indicator of SEP, including childhood SEP, was significantly inversely associated with SROH, and all of the workplace-related factors (social support in the workplace, job stress, working hours and type of employment) were also significantly associated with SROH. Compared with professionals, blue-collar workers had a significantly higher OR of poor SROH and the association was substantially explained by the workplace-related factors; ORs ranged from 1.44 in the age-adjusted and sex-adjusted model to 1.18 in the multivariate model. Poverty during childhood at age 5 and at age 15 was associated with poorer SROH, and these two factors seemed to be independently associated with SROH. We found oral health disparity across SEP among workers in Japan. Approximately 60% of the association between occupation and SROH was explained by job-related factors. Economic difficulties during childhood appear to affect SROH in adulthood separately from sex, age and the current workplace-related factors. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Identifying Environmental and Social Factors Predisposing to Pathological Gambling Combining Standard Logistic Regression and Logic Learning Machine.

Science.gov (United States)

Parodi, Stefano; Dosi, Corrado; Zambon, Antonella; Ferrari, Enrico; Muselli, Marco

2017-12-01

Identifying potential risk factors for problem gambling (PG) is of primary importance for planning preventive and therapeutic interventions. We illustrate a new approach based on the combination of standard logistic regression and an innovative method of supervised data mining (Logic Learning Machine or LLM). Data were taken from a pilot cross-sectional study to identify subjects with PG behaviour, assessed by two internationally validated scales (SOGS and Lie/Bet). Information was obtained from 251 gamblers recruited in six betting establishments. Data on socio-demographic characteristics, lifestyle and cognitive-related factors, and type, place and frequency of preferred gambling were obtained by a self-administered questionnaire. The following variables associated with PG were identified: instant gratification games, alcohol abuse, cognitive distortion, illegal behaviours and having started gambling with a relative or a friend. Furthermore, the combination of LLM and LR indicated the presence of two different types of PG, namely: (a) daily gamblers, more prone to illegal behaviour, with poor money management skills and who started gambling at an early age, and (b) non-daily gamblers, characterised by superstitious beliefs and a higher preference for immediate reward games. Finally, instant gratification games were strongly associated with the number of games usually played. Studies on gamblers habitually frequently betting shops are rare. The finding of different types of PG by habitual gamblers deserves further analysis in larger studies. Advanced data mining algorithms, like LLM, are powerful tools and potentially useful in identifying risk factors for PG.

Study of risk factors affecting both hypertension and obesity outcome by using multivariate multilevel logistic regression models

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Sepedeh Gholizadeh

2016-07-01

Full Text Available Background:Obesity and hypertension are the most important non-communicable diseases thatin many studies, the prevalence and their risk factors have been performedin each geographic region univariately.Study of factors affecting both obesity and hypertension may have an important role which to be adrressed in this study. Materials &Methods:This cross-sectional study was conducted on 1000 men aged 20-70 living in Bushehr province. Blood pressure was measured three times and the average of them was considered as one of the response variables. Hypertension was defined as systolic blood pressure ≥140 (and-or diastolic blood pressure ≥90 and obesity was defined as body mass index ≥25. Data was analyzed by using multilevel, multivariate logistic regression model by MlwiNsoftware. Results:Intra class correlations in cluster level obtained 33% for high blood pressure and 37% for obesity, so two level model was fitted to data. The prevalence of obesity and hypertension obtained 43.6% (0.95%CI; 40.6-46.5, 29.4% (0.95%CI; 26.6-32.1 respectively. Age, gender, smoking, hyperlipidemia, diabetes, fruit and vegetable consumption and physical activity were the factors affecting blood pressure (p≤0.05. Age, gender, hyperlipidemia, diabetes, fruit and vegetable consumption, physical activity and place of residence are effective on obesity (p≤0.05. Conclusion: The multilevel models with considering levels distribution provide more precise estimates. As regards obesity and hypertension are the major risk factors for cardiovascular disease, by knowing the high-risk groups we can d careful planning to prevention of non-communicable diseases and promotion of society health.

Predicting Factors of INSURE Failure in Low Birth Weight Neonates with RDS; A Logistic Regression Model

OpenAIRE

Bita Najafian; Aminsaburi Aminsaburi; Seyyed Hassan Fakhraei; Abolfazl afjeh; Fatemeh Eghbal; Reza Noroozian

2015-01-01

Background:Respiratory Distress syndrome is the most common respiratory disease in premature neonate and the most important cause of death among them. We aimed to investigate factors to predict successful or failure of INSURE method as a therapeutic method of RDS. Methods:In a cohort study,45 neonates with diagnosed RDS and birth weight lower than 1500g were included and they underwent INSURE followed by NCPAP(Nasal Continuous Positive Airway Pressure). The patients were divided into failu...

Brucellosis in a high risk occupational group: sero prevalence and analysis of risk factors

International Nuclear Information System (INIS)

Mukhtar, F.

2010-01-01

Objectives: To estimate Brucella sero positivity among slaughterhouse workers of Lahore district and to elucidate risk factors associated with sero positivity to Brucella. Method: During the year 2008, a cross-sectional study was conducted in four slaughterhouses of Lahore district. A sample of 360 workers was selected from these slaughterhouses through stratified random sampling on proportional basis. Workers were interviewed using a structured questionnaire to obtain risk factor information and their blood samples were collected to be screened for the presence of anti-Brucella IgG using Enzyme Linked Immunosorbent Assay (ELISA) technique. Data management and analysis were performed using SPSS (statistical package for social sciences) version 16. Risk factors associated with sero positivity to anti-Brucella IgG were identified by constructing a logistic regression model. Results: Of the 360 serum samples tested, 21.7% (95% CI 17.44% - 25.96%) were positive by ELISA test. The logistic regression model identified age (OR 0.96, 95% CI 0.94-0.99), assistance in parturition of animal (OR 0.47, 95% CI 0.23-0.96), consuming raw milk (OR 2.25, 95% CI 1.04-4.87) and handling sheep (OR 0.30, 95% CI 0.09- 0.92) as risk factors for Brucella sero positivity among slaughterhouse workers of Lahore district. Conclusion: To reduce the burden of brucellosis, a national brucellosis control programme should be initiated with special emphasis on the high risk population of slaughterhouse workers. (author)

[Multiple linear regression and ROC curve analysis of the factors of lumbar spine bone mineral density].

Science.gov (United States)

Zhang, Xiaodong; Zhao, Yinxia; Hu, Shaoyong; Hao, Shuai; Yan, Jiewen; Zhang, Lingyan; Zhao, Jing; Li, Shaolin

2015-09-01

To investigate the correlation between the lumbar vertebra bone mineral density (BMD) and age, gender, height, weight, body mass index, waistline, hipline, bone marrow and abdomen fat, and to explore the key factor affecting the BMD. A total of 72 cases were randomly recruited. All the subjects underwent a spectroscopic examination of the third lumber vertebra with single-voxel method in 1.5T MR. Lipid fractions (FF%) were measured. Quantitative CT were also performed to get the BMD of L3 and the corresponding abdomen subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT). The statistical analysis were performed by SPSS 19.0. Multiple linear regression showed except the age and FF% showed significant difference (P0.05). The correlation of age and FF% with BMD was statistically negatively significant (r=-0.830, -0.521, P<0.05). The ROC curve analysis showed that the sensitivety and specificity of predicting osteoporosis were 81.8% and 86.9%, with a threshold of 58.5 years old. And it showed that the sensitivety and specificity of predicting osteoporosis were 90.9% and 55.7%, with a threshold of 52.8% for FF%. The lumbar vertebra BMD was significantly and negatively correlated with age and bone marrow FF%, but it was not significantly correlated with gender, height, weight, BMI, waistline, hipline, SAT and VAT. And age was the critical factor.

The Internal Structure of Positive and Negative Affect: A Confirmatory Factor Analysis of the PANAS

Science.gov (United States)

Tuccitto, Daniel E.; Giacobbi, Peter R., Jr.; Leite, Walter L.

2010-01-01

This study tested five confirmatory factor analytic (CFA) models of the Positive Affect Negative Affect Schedule (PANAS) to provide validity evidence based on its internal structure. A sample of 223 club sport athletes indicated their emotions during the past week. Results revealed that an orthogonal two-factor CFA model, specifying error…

Search Strategy of Detector Position For Neutron Source Multiplication Method by Using Detected-Neutron Multiplication Factor

International Nuclear Information System (INIS)

Endo, Tomohiro

2011-01-01

In this paper, an alternative definition of a neutron multiplication factor, detected-neutron multiplication factor kdet, is produced for the neutron source multiplication method..(NSM). By using kdet, a search strategy of appropriate detector position for NSM is also proposed. The NSM is one of the practical subcritical measurement techniques, i.e., the NSM does not require any special equipment other than a stationary external neutron source and an ordinary neutron detector. Additionally, the NSM method is based on steady-state analysis, so that this technique is very suitable for quasi real-time measurement. It is noted that the correction factors play important roles in order to accurately estimate subcriticality from the measured neutron count rates. The present paper aims to clarify how to correct the subcriticality measured by the NSM method, the physical meaning of the correction factors, and how to reduce the impact of correction factors by setting a neutron detector at an appropriate detector position

Propuesta de factores a considerar en el posicionamiento de los sitios web de salud (Proposal of Factors to be considered for positioning of Health Websites

Directory of Open Access Journals (Sweden)

Mercedes Moráguez Bergues

2014-04-01

Full Text Available Resumen El posicionamiento web se convierte en un factor esencial a tener presente cuando se desea promocionar un sitio web en Internet. Esta investigación trata sobre los factores SEO (Search Engine Optimization que influyen en el posicionamiento de un sitio Web en los buscadores y por tanto en su visibilidad. Se identificaron estos factores y se relacionaron con los atributos de usabilidad y accesibilidad de un sitio Web. Se exponen los resultados de la aplicación de dos cuestionarios: uno para el perfil editor y otro para el perfil usuario, lo cual permitió relacionar las problemáticas que influyen en el bajo posicionamiento de algunos sitios web de salud de la red de Infomed. Abstract The web positioning becomes an essential factor to keep in mind when you want to promote a website on the Internet. This paper analyzes the SEO factors (Search Engine Optimization that influence on the position of a website in search engines and therefore its visibility. These factors were identified and related to the attributes of usability and accessibility of a Website. Results from two surveys allowed connect the problems affecting the low positioning of some health websites of INFOMED network.

Analysis of Factors Affecting Inflation in Indonesia: an Islamic Perspective

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Elis Ratna Wulan

2015-04-01

Full Text Available This study aims to determine the factors affecting inflation. The research is descriptive quantitative in nature. The data used are reported exchange rates, interest rates, money supply and inflation during 2008-2012. The research data was analyzed using multiple linear regression analysis. The results showed in the year 2008-2012 the condition of each variable are (1 the rate of inflation has a negative trend, (2 the interest rate has a negative trend, (3 the money supply has a positive trend, (4 the value of exchange rate has a positive trend. The test results by using multiple linear regression analysis result that variable interest rates, the money supply and the exchange rate of the rupiah significant effect on the rate of inflation.

Convergence of genetic and environmental factors on parvalbumin-positive interneurons in schizophrenia

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Zhihong eJiang

2013-09-01

Full Text Available Schizophrenia etiology is thought to involve an interaction between genetic and environmental factors during postnatal brain development. However, there is a fundamental gap in our understanding of the molecular mechanisms by which environmental factors interact with genetic susceptibility to trigger symptom onset and disease progression. In this review, we summarize the most recent findings implicating oxidative stress as one mechanism by which environmental insults, especially early life social stress, impact the development of schizophrenia. Based on a review of the literature and the results of our own animal model, we suggest that environmental stressors such as social isolation render parvalbumin-positive interneurons vulnerable to oxidative stress. We previously reported that social isolation stress exacerbates many of the schizophrenia-like phenotypes seen in a conditional genetic mouse model of schizophrenia in which NMDARs are selectively ablated in half of cortical and hippocampal interneurons during early postnatal development (Belforte et al., 2010. We have since revealed that this social isolation-induced effect is caused by impairments in the antioxidant defense capacity in the parvalbumin-positive interneurons in which NMDARs are ablated. We propose that this effect is mediated by the down-regulation of PGC-1α, a master regulator of mitochondrial energy metabolism and anti-oxidant defense, following the deletion of NMDARs (Jiang et al, 2013. Other potential molecular mechanisms underlying redox dysfunction upon gene and environmental interaction will be discussed, with a focus on the unique properties of parvalbumin-positive interneurons.

Risk factors for genital human papillomavirus among men in Tanzania

DEFF Research Database (Denmark)

Olesen, Tina Bech; Mwaiselage, Julius; Iftner, Thomas

2017-01-01

, although not being statistically significant. In conclusion, HIV is a strong risk factor for HPV among men in Tanzania. Additionally, in HIV-positive men a high BMI seems to be associated with a lower risk of HPV. Finally, we observed a tendency toward a lower risk of HPV both among HIV-positive and HIV......The objective of the study was to assess risk factors for Human Papillomavirus (HPV) among men in Tanzania, both overall and in relation to HIV status. In a cross-sectional study conducted among 1,813 men in Tanzania, penile swabs were tested for HPV using Hybrid Capture 2 (HC2). Study participants...... were offered HIV testing. Risk factors for HPV (HC2 high-risk and/or low-risk positivity) were assessed using logistic regression with adjustment for age, lifetime number of sexual partners, and HIV status. Altogether, 372 men (20.5%) were HPV-positive. Among men tested for HIV (n = 1,483), the HIV...

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

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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.

Exploring the Factors that Influence Nurse Practitioner Role Transition

OpenAIRE

Barnes, Hilary

2015-01-01

The transition from registered nurse (RN) to nurse practitioner (NP) is often a stressful career change. Data are lacking on the factors affecting NP role transition. This study examined the relationships between NP role transition, prior RN experience, and a formal orientation. From a sample of 352 NPs, only a formal orientation contributed significantly to the regression model indicating a positive relationship with NP role transition (b = 6.24, p < .001). Knowledge of the factors that expl...

Spatiotemporal Pattern of PM2.5 Concentrations in Mainland China and Analysis of Its Influencing Factors using Geographically Weighted Regression

Science.gov (United States)

Luo, Jieqiong; Du, Peijun; Samat, Alim; Xia, Junshi; Che, Meiqin; Xue, Zhaohui

2017-01-01

Based on annual average PM2.5 gridded dataset, this study first analyzed the spatiotemporal pattern of PM2.5 across Mainland China during 1998-2012. Then facilitated with meteorological site data, land cover data, population and Gross Domestic Product (GDP) data, etc., the contributions of latent geographic factors, including socioeconomic factors (e.g., road, agriculture, population, industry) and natural geographical factors (e.g., topography, climate, vegetation) to PM2.5 were explored through Geographically Weighted Regression (GWR) model. The results revealed that PM2.5 concentrations increased while the spatial pattern remained stable, and the proportion of areas with PM2.5 concentrations greater than 35 μg/m3 significantly increased from 23.08% to 29.89%. Moreover, road, agriculture, population and vegetation showed the most significant impacts on PM2.5. Additionally, the Moran’s I for the residuals of GWR was 0.025 (not significant at a 0.01 level), indicating that the GWR model was properly specified. The local coefficient estimates of GDP in some cities were negative, suggesting the existence of the inverted-U shaped Environmental Kuznets Curve (EKC) for PM2.5 in Mainland China. The effects of each latent factor on PM2.5 in various regions were different. Therefore, regional measures and strategies for controlling PM2.5 should be formulated in terms of the local impacts of specific factors.

Efficacy of Intravitreal injection of 2-Methoxyestradiol in regression of neovascularization of a retinopathy of prematurity rat model.

Science.gov (United States)

Said, Azza Mohamed Ahmed; Zaki, Rania Gamal Eldin; Salah Eldin, Rania A; Nasr, Maha; Azab, Samar Saad; Elzankalony, Yaser Abdelmageuid

2017-04-04

Retinopathy of prematurity (ROP) is one of the targets for early detection and treatment to prevent childhood blindness in world health organization programs. The purpose of study was to evaluate the efficacy of intravitreal injection of 2-Methoxyestradiol (2-ME) nanoemulsion in regressing neovascularization of a ROP rat model. A prospective comparative case - control animal study conducted on 56 eyes of 28 healthy new born Sprague Dawley male albino rat. ROP was induced in 21 rats then two concentrations of 2-ME nanoparticles were injected in right eyes of 14 rats (low dose; study group I, high dose; study group II). A blank nanoemulsion was injected in the right eyes of seven rats (control positive group I). No injections performed in contralateral left eyes (control positive group II). Seven rats (14 eyes) were kept in room air (control negative group). On postnatal day 17, eyeballs were enucleated. Histological structure of the retina was examined using Hematoxylin and eosin staining. Vascular endothelial growth factor (VEGF) and glial fibrillary acidic protein (GFAP) expressions were detected by immunohistochemical studies. Intravitreal injection of 2-ME (in the two concentrations) caused marked regression of the new vascular tufts on the vitreal side with normal organization and thickness of the retina especially in study group II, which also show negative VEGF immunoreaction. Positive GFAP expression was detected in the control positive groups and study group (I). Intravitreal injection of 2-Methoxyestradiol nanoemulsion is a promising effective method in reduction of neovascularization of a ROP rat model.

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....

Desertification Susceptibility Mapping Using Logistic Regression Analysis in the Djelfa Area, Algeria

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Farid Djeddaoui

2017-10-01

Full Text Available The main goal of this work was to identify the areas that are most susceptible to desertification in a part of the Algerian steppe, and to quantitatively assess the key factors that contribute to this desertification. In total, 139 desertified zones were mapped using field surveys and photo-interpretation. We selected 16 spectral and geomorphic predictive factors, which a priori play a significant role in desertification. They were mainly derived from Landsat 8 imagery and Shuttle Radar Topographic Mission digital elevation model (SRTM DEM. Some factors, such as the topographic position index (TPI and curvature, were used for the first time in this kind of study. For this purpose, we adapted the logistic regression algorithm for desertification susceptibility mapping, which has been widely used for landslide susceptibility mapping. The logistic model was evaluated using the area under the receiver operating characteristic (ROC curve. The model accuracy was 87.8%. We estimated the model uncertainties using a bootstrap method. Our analysis suggests that the predictive model is robust and stable. Our results indicate that land cover factors, including normalized difference vegetation index (NDVI and rangeland classes, play a major role in determining desertification occurrence, while geomorphological factors have a limited impact. The predictive map shows that 44.57% of the area is classified as highly to very highly susceptible to desertification. The developed approach can be used to assess desertification in areas with similar characteristics and to guide possible actions to combat desertification.

Determining the Relationship between U.S. County-Level Adult Obesity Rate and Multiple Risk Factors by PLS Regression and SVM Modeling Approaches

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Chau-Kuang Chen

2015-02-01

Full Text Available Data from the Center for Disease Control (CDC has shown that the obesity rate doubled among adults within the past two decades. This upsurge was the result of changes in human behavior and environment. Partial least squares (PLS regression and support vector machine (SVM models were conducted to determine the relationship between U.S. county-level adult obesity rate and multiple risk factors. The outcome variable was the adult obesity rate. The 23 risk factors were categorized into four domains of the social ecological model including biological/behavioral factor, socioeconomic status, food environment, and physical environment. Of the 23 risk factors related to adult obesity, the top eight significant risk factors with high normalized importance were identified including physical inactivity, natural amenity, percent of households receiving SNAP benefits, and percent of all restaurants being fast food. The study results were consistent with those in the literature. The study showed that adult obesity rate was influenced by biological/behavioral factor, socioeconomic status, food environment, and physical environment embedded in the social ecological theory. By analyzing multiple risk factors of obesity in the communities, may lead to the proposal of more comprehensive and integrated policies and intervention programs to solve the population-based problem.

Linguistic positivity in historical texts reflects dynamic environmental and psychological factors.

Science.gov (United States)

Iliev, Rumen; Hoover, Joe; Dehghani, Morteza; Axelrod, Robert

2016-12-06

People use more positive words than negative words. Referred to as "linguistic positivity bias" (LPB), this effect has been found across cultures and languages, prompting the conclusion that it is a panhuman tendency. However, although multiple competing explanations of LPB have been proposed, there is still no consensus on what mechanism(s) generate LPB or even on whether it is driven primarily by universal cognitive features or by environmental factors. In this work we propose that LPB has remained unresolved because previous research has neglected an essential dimension of language: time. In four studies conducted with two independent, time-stamped text corpora (Google books Ngrams and the New York Times), we found that LPB in American English has decreased during the last two centuries. We also observed dynamic fluctuations in LPB that were predicted by changes in objective environment, i.e., war and economic hardships, and by changes in national subjective happiness. In addition to providing evidence that LPB is a dynamic phenomenon, these results suggest that cognitive mechanisms alone cannot account for the observed dynamic fluctuations in LPB. At the least, LPB likely arises from multiple interacting mechanisms involving subjective, objective, and societal factors. In addition to having theoretical significance, our results demonstrate the value of newly available data sources in addressing long-standing scientific questions.

Occlusal factors are not related to self-reported bruxism.

Science.gov (United States)

Manfredini, Daniele; Visscher, Corine M; Guarda-Nardini, Luca; Lobbezoo, Frank

2012-01-01

To estimate the contribution of various occlusal features of the natural dentition that may identify self-reported bruxers compared to nonbruxers. Two age- and sex-matched groups of self-reported bruxers (n = 67) and self-reported nonbruxers (n = 75) took part in the study. For each patient, the following occlusal features were clinically assessed: retruded contact position (RCP) to intercuspal contact position (ICP) slide length ( 4 mm, a deep bite), horizontal overlap (> 4 mm was considered a large horizontal overlap), incisor dental midline discrepancy (bruxism (dependent variable). Accuracy values to predict self-reported bruxism were unacceptable for all occlusal variables. The only variable remaining in the final regression model was laterotrusive interferences (P = .030). The percentage of explained variance for bruxism by the final multiple regression model was 4.6%. This model including only one occlusal factor showed low positive (58.1%) and negative predictive values (59.7%), thus showing a poor accuracy to predict the presence of self-reported bruxism (59.2%). This investigation suggested that the contribution of occlusion to the differentiation between bruxers and nonbruxers is negligible. This finding supports theories that advocate a much diminished role for peripheral anatomical-structural factors in the pathogenesis of bruxism.

Determinants of LSIL Regression in Women from a Colombian Cohort; Determinantes de la regresion de lesiones cervicales de bajo grado en una cohorte de mujeres colombianas.

Energy Technology Data Exchange (ETDEWEB)

Molano, Monica; Gonzalez, Mauricio; Gamboa, Oscar; Ortiz, Natasha; Luna, Joaquin; Hernandez, Gustavo; Posso, Hector; Murillo, Raul; Munoz, Nubia

2010-07-01

Objective: To analyze the role of Human Papillomavirus (HPV) and other risk factors in the regression of cervical lesions in women from the Bogota Cohort. Methods: 200 HPV positive women with abnormal cytology were included for regression analysis. The time of lesion regression was modeled using methods for interval censored survival time data. Median duration of total follow-up was 9 years. Results: 80 (40%) women were diagnosed with Atypical Squamous Cells of Undetermined Significance (ASCUS) or Atypical Glandular Cells of Undetermined Significance (AGUS) while 120 (60%) were diagnosed with Low Grade Squamous Intra-epithelial Lesions (LSIL). Globally, 40% of the lesions were still present at first year of follow up, while 1.5% was still present at 5 year check-up. The multivariate model showed similar regression rates for lesions in women with ASCUS/AGUS and women with LSIL (HR= 0.82, 95% CI 0.59-1.12). Women infected with HR HPV types and those with mixed infections had lower regression rates for lesions than did women infected with LR types (HR=0.526, 95% CI 0.33-0.84, for HR types and HR=0.378, 95% CI 0.20-0.69, for mixed infections). Furthermore, women over 30 years had a higher lesion regression rate than did women under 30 years (HR1.53, 95% CI 1.03-2.27). The study showed that the median time for lesion regression was 9 months while the median time for HPV clearance was 12 months. Conclusions: In the studied population, the type of infection and the age of the women are critical factors for the regression of cervical lesions.

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

THE PROGNOSIS OF RUSSIAN DEFENSE INDUSTRY DEVELOPMENT IMPLEMENTED THROUGH REGRESSION ANALYSIS

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L.M. Kapustina

2007-03-01

Full Text Available The article illustrates the results of investigation the major internal and external factors which influence the development of the defense industry, as well as the results of regression analysis which quantitatively displays the factorial contribution in the growth rate of Russian defense industry. On the basis of calculated regression dependences the authors fulfilled the medium-term prognosis of defense industry. Optimistic and inertial versions of defense product growth rate for the period up to 2009 are based on scenario conditions in Russian economy worked out by the Ministry of economy and development. In conclusion authors point out which factors and conditions have the largest impact on successful and stable operation of Russian defense industry.

Evaluation of Logistic Regression and Multivariate Adaptive Regression Spline Models for Groundwater Potential Mapping Using R and GIS

Directory of Open Access Journals (Sweden)

Soyoung Park

2017-07-01

Full Text Available This study mapped and analyzed groundwater potential using two different models, logistic regression (LR and multivariate adaptive regression splines (MARS, and compared the results. A spatial database was constructed for groundwater well data and groundwater influence factors. Groundwater well data with a high potential yield of ≥70 m3/d were extracted, and 859 locations (70% were used for model training, whereas the other 365 locations (30% were used for model validation. We analyzed 16 groundwater influence factors including altitude, slope degree, slope aspect, plan curvature, profile curvature, topographic wetness index, stream power index, sediment transport index, distance from drainage, drainage density, lithology, distance from fault, fault density, distance from lineament, lineament density, and land cover. Groundwater potential maps (GPMs were constructed using LR and MARS models and tested using a receiver operating characteristics curve. Based on this analysis, the area under the curve (AUC for the success rate curve of GPMs created using the MARS and LR models was 0.867 and 0.838, and the AUC for the prediction rate curve was 0.836 and 0.801, respectively. This implies that the MARS model is useful and effective for groundwater potential analysis in the study area.

Controlling attribute effect in linear regression

KAUST Repository

Calders, Toon; Karim, Asim A.; Kamiran, Faisal; Ali, Wasif Mohammad; Zhang, Xiangliang

2013-01-01

In data mining we often have to learn from biased data, because, for instance, data comes from different batches or there was a gender or racial bias in the collection of social data. In some applications it may be necessary to explicitly control this bias in the models we learn from the data. This paper is the first to study learning linear regression models under constraints that control the biasing effect of a given attribute such as gender or batch number. We show how propensity modeling can be used for factoring out the part of the bias that can be justified by externally provided explanatory attributes. Then we analytically derive linear models that minimize squared error while controlling the bias by imposing constraints on the mean outcome or residuals of the models. Experiments with discrimination-aware crime prediction and batch effect normalization tasks show that the proposed techniques are successful in controlling attribute effects in linear regression models. © 2013 IEEE.

Controlling attribute effect in linear regression

KAUST Repository

Calders, Toon

2013-12-01

In data mining we often have to learn from biased data, because, for instance, data comes from different batches or there was a gender or racial bias in the collection of social data. In some applications it may be necessary to explicitly control this bias in the models we learn from the data. This paper is the first to study learning linear regression models under constraints that control the biasing effect of a given attribute such as gender or batch number. We show how propensity modeling can be used for factoring out the part of the bias that can be justified by externally provided explanatory attributes. Then we analytically derive linear models that minimize squared error while controlling the bias by imposing constraints on the mean outcome or residuals of the models. Experiments with discrimination-aware crime prediction and batch effect normalization tasks show that the proposed techniques are successful in controlling attribute effects in linear regression models. © 2013 IEEE.

Optimism and positive and negative feelings in parents of young children with developmental delay.

Science.gov (United States)

Kurtz-Nelson, E; McIntyre, L L

2017-07-01

Parents' positive and negative feelings about their young children influence both parenting behaviour and child problem behaviour. Research has not previously examined factors that contribute to positive and negative feelings in parents of young children with developmental delay (DD). The present study sought to examine whether optimism, a known protective factor for parents of children with DD, was predictive of positive and negative feelings for these parents. Data were collected from 119 parents of preschool-aged children with developmental delay. Two separate hierarchical linear regression analyses were conducted to determine if optimism significantly predicted positive feelings and negative feelings and whether optimism moderated relations between parenting stress and parent feelings. Increased optimism was found to predict increased positive feelings and decreased negative feelings after controlling for child problem behaviour and parenting stress. In addition, optimism was found to moderate the relation between parenting stress and positive feelings. Results suggest that optimism may impact how parents perceive their children with DD. Future research should examine how positive and negative feelings impact positive parenting behaviour and the trajectory of problem behaviour specifically for children with DD. © 2017 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Simulation Experiments in Practice : Statistical Design and Regression Analysis

NARCIS (Netherlands)

Kleijnen, J.P.C.

2007-01-01

In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. Statistical theory proves that more information is obtained when applying Design Of Experiments (DOE) and linear regression analysis. Unfortunately, classic

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

Does an advantageous occupational position make women happier in contemporary Japan? Findings from the Japanese Study of Health, Occupation, and Psychosocial Factors Related Equity (J-HOPE

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Maki Umeda

2015-12-01

Full Text Available Occupational position is one of the determinants of psychological health, but this association may differ for men and women depending on the social context. In contemporary Japanese society, occupational gender segregation persists despite increased numbers of women participating in the labour market, which may contribute to gender specific patterns in the prevalence of poor psychological health. The present study examined gender specific associations between occupational position and psychological health in Japan, and the potential mediating effects of job control and effort–reward imbalance in these associations. We used data obtained from 7123 men and 2222 women, aged between 18 and 65 years, who participated in an occupational cohort study, the Japanese Study of Health, Occupation, and Psychosocial Factors Related Equity (J-HOPE, between 2011 and 2012. We used logistic regression to examine the association between occupational position and poor psychological health, adjusted for age, working hours, household income and education, as well as psychosocial work characteristics (job control and effort–reward imbalance. The prevalence of poor psychological health increased from manual/service occupations (23% to professionals/managers (38% among women, while it did not vary by occupational position among men. In women, the significant association between occupational position and psychological health was not explained by job control, but was attenuated by effort–reward imbalance. Our findings suggest that Japanese women in more advantaged occupational positions are likely to be at a greater risk for poor psychological health due to higher levels of effort–reward imbalance at work.

Landslide susceptibility mapping on a global scale using the method of logistic regression

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L. Lin

2017-08-01

Full Text Available This paper proposes a statistical model for mapping global landslide susceptibility based on logistic regression. After investigating explanatory factors for landslides in the existing literature, five factors were selected for model landslide susceptibility: relative relief, extreme precipitation, lithology, ground motion and soil moisture. When building the model, 70 % of landslide and nonlandslide points were randomly selected for logistic regression, and the others were used for model validation. To evaluate the accuracy of predictive models, this paper adopts several criteria including a receiver operating characteristic (ROC curve method. Logistic regression experiments found all five factors to be significant in explaining landslide occurrence on a global scale. During the modeling process, percentage correct in confusion matrix of landslide classification was approximately 80 % and the area under the curve (AUC was nearly 0.87. During the validation process, the above statistics were about 81 % and 0.88, respectively. Such a result indicates that the model has strong robustness and stable performance. This model found that at a global scale, soil moisture can be dominant in the occurrence of landslides and topographic factor may be secondary.

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-

Estimation of the laser cutting operating cost by support vector regression methodology

Science.gov (United States)

Jović, Srđan; Radović, Aleksandar; Šarkoćević, Živče; Petković, Dalibor; Alizamir, Meysam

2016-09-01

Laser cutting is a popular manufacturing process utilized to cut various types of materials economically. The operating cost is affected by laser power, cutting speed, assist gas pressure, nozzle diameter and focus point position as well as the workpiece material. In this article, the process factors investigated were: laser power, cutting speed, air pressure and focal point position. The aim of this work is to relate the operating cost to the process parameters mentioned above. CO2 laser cutting of stainless steel of medical grade AISI316L has been investigated. The main goal was to analyze the operating cost through the laser power, cutting speed, air pressure, focal point position and material thickness. Since the laser operating cost is a complex, non-linear task, soft computing optimization algorithms can be used. Intelligent soft computing scheme support vector regression (SVR) was implemented. The performance of the proposed estimator was confirmed with the simulation results. The SVR results are then compared with artificial neural network and genetic programing. According to the results, a greater improvement in estimation accuracy can be achieved through the SVR compared to other soft computing methodologies. The new optimization methods benefit from the soft computing capabilities of global optimization and multiobjective optimization rather than choosing a starting point by trial and error and combining multiple criteria into a single criterion.

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…

Impact of multicollinearity on small sample hydrologic regression models

Science.gov (United States)

Kroll, Charles N.; Song, Peter

2013-06-01

Often hydrologic regression models are developed with ordinary least squares (OLS) procedures. The use of OLS with highly correlated explanatory variables produces multicollinearity, which creates highly sensitive parameter estimators with inflated variances and improper model selection. It is not clear how to best address multicollinearity in hydrologic regression models. Here a Monte Carlo simulation is developed to compare four techniques to address multicollinearity: OLS, OLS with variance inflation factor screening (VIF), principal component regression (PCR), and partial least squares regression (PLS). The performance of these four techniques was observed for varying sample sizes, correlation coefficients between the explanatory variables, and model error variances consistent with hydrologic regional regression models. The negative effects of multicollinearity are magnified at smaller sample sizes, higher correlations between the variables, and larger model error variances (smaller R2). The Monte Carlo simulation indicates that if the true model is known, multicollinearity is present, and the estimation and statistical testing of regression parameters are of interest, then PCR or PLS should be employed. If the model is unknown, or if the interest is solely on model predictions, is it recommended that OLS be employed since using more complicated techniques did not produce any improvement in model performance. A leave-one-out cross-validation case study was also performed using low-streamflow data sets from the eastern United States. Results indicate that OLS with stepwise selection generally produces models across study regions with varying levels of multicollinearity that are as good as biased regression techniques such as PCR and PLS.

Risk factors associated with the community-acquired colonization of extended-spectrum beta-lactamase (ESBL) positive Escherichia Coli. an exploratory case-control study.

Science.gov (United States)

Leistner, Rasmus; Meyer, Elisabeth; Gastmeier, Petra; Pfeifer, Yvonne; Eller, Christoph; Dem, Petra; Schwab, Frank

2013-01-01

The number of extended-spectrum beta-lactamase (ESBL) positive (+) Escherichia coli is increasing worldwide. In contrast with many other multidrug-resistant bacteria, it is suspected that they predominantly spread within the community. The objective of this study was to assess factors associated with community-acquired colonization of ESBL (+) E. coli. We performed a matched case-control study at the Charité University Hospital Berlin between May 2011 and January 2012. Cases were defined as patients colonized with community-acquired ESBL (+) E. coli identified language most commonly spoken at home (mother tongue). An additional rectal swab was obtained together with the questionnaire to verify colonization status. Genotypes of ESBL (+) E. coli strains were determined by PCR and sequencing. Risk factors associated with ESBL (+) E. coli colonization were analyzed by a multivariable conditional logistic regression analysis. We analyzed 85 cases and 170 controls, respectively. In the multivariable analysis, speaking an Asian language most commonly at home (OR = 13.4, CI 95% 3.3-53.8; p<0.001) and frequently eating pork (≥ 3 meals per week) showed to be independently associated with ESBL colonization (OR = 3.5, CI 95% 1.8-6.6; p<0.001). The most common ESBL genotypes were CTX-M-1 with 44% (n = 37), CTX-M-15 with 28% (n = 24) and CTX-M-14 with 13% (n = 11). An Asian mother tongue and frequently consuming certain types of meat like pork can be independently associated with the colonization of ESBL-positive bacteria. We found neither frequent consumption of poultry nor previous use of antibiotics to be associated with ESBL colonization.

Assessing the Credit Risk of Corporate Bonds Based on Factor Analysis and Logistic Regress Analysis Techniques: Evidence from New Energy Enterprises in China

Directory of Open Access Journals (Sweden)

Yuanxin Liu

2018-05-01

Full Text Available In recent years, new energy sources have ushered in tremendous opportunities for development. The difficulties to finance new energy enterprises (NEEs can be estimated through issuing corporate bonds. However, there are few scientific and reasonable methods to assess the credit risk of NEE bonds, which is not conducive to the healthy development of NEEs. Based on this, this paper analyzes the advantages and risks of NEEs issuing bonds and the main factors affecting the credit risk of NEE bonds, constructs a hybrid model for assessing the credit risk of NEE bonds based on factor analysis and logistic regress analysis techniques, and verifies the applicability and effectiveness of the model employing relevant data from 46 Chinese NEEs. The results show that the main factors affecting the credit risk of NEE bonds are internal factors involving the company’s profitability, solvency, operational ability, growth potential, asset structure and viability, and external factors including macroeconomic environment and energy policy support. Based on the empirical results and the exact situation of China’s NEE bonds, this article finally puts forward several targeted recommendations.

Vector regression introduced

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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.

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

Logistic regression against a divergent Bayesian network

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Noel Antonio Sánchez Trujillo

2015-01-01

Full Text Available This article is a discussion about two statistical tools used for prediction and causality assessment: logistic regression and Bayesian networks. Using data of a simulated example from a study assessing factors that might predict pulmonary emphysema (where fingertip pigmentation and smoking are considered; we posed the following questions. Is pigmentation a confounding, causal or predictive factor? Is there perhaps another factor, like smoking, that confounds? Is there a synergy between pigmentation and smoking? The results, in terms of prediction, are similar with the two techniques; regarding causation, differences arise. We conclude that, in decision-making, the sum of both: a statistical tool, used with common sense, and previous evidence, taking years or even centuries to develop; is better than the automatic and exclusive use of statistical resources.

Antecedents of positive self-disclosure online: an empirical study of US college students' Facebook usage.

Science.gov (United States)

Chen, Hongliang

2017-01-01

This study investigates the factors predicting positive self-disclosure on social networking sites (SNSs). There is a formidable body of empirical research relating to online self-disclosure, but very few studies have assessed the antecedents of positive self-disclosure. To address this literature gap, the current study tests the effects of self-esteem, life satisfaction, social anxiety, privacy concerns, public self-consciousness (SC), and perceived collectivism on positive self-disclosure on SNSs. Data were collected online via Qualtrics in April 2013. Respondents were undergraduate students from the University of Connecticut. Using ordinary least squares regression, the current study found that self-esteem and perceived collectivism increased positive self-disclosure, life satisfaction, and privacy concerns decreased positive self-disclosure, and the effects of social anxiety and public SC were not significant.

An Analysis of Impact Factors for Positioning Performance in WLAN Fingerprinting Systems Using Ishikawa Diagrams and a Simulation Platform

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Keqiang Liu

2017-01-01

Full Text Available Many factors influence the positioning performance in WLAN RSSI fingerprinting systems, and summary of these factors is an important but challenging job. Moreover, impact analysis on nonalgorithm factors is significant to system application and quality control but little research has been conducted. This paper analyzes and summarizes the potential impact factors by using an Ishikawa diagram considering radio signal transmitting, propagating, receiving, and processing. A simulation platform was developed to facilitate the analysis experiment, and the paper classifies the potential factors into controllable, uncontrollable, nuisance, and held-constant factors considering simulation feasibility. It takes five nonalgorithm controllable factors including APs density, APs distribution, radio signal propagating attenuation factor, radio signal propagating noise, and RPs density into consideration and adopted the OFAT analysis method in experiment. The positioning result was achieved by using the deterministic and probabilistic algorithms, and the error was presented by RMSE and CDF. The results indicate that the high APs density, signal propagating attenuation factor, and RPs density, with the low signal propagating noise level, are favorable to better performance, while APs distribution has no particular impact pattern on the positioning error. Overall, this paper has made great potential contribution to the quality control of WLAN fingerprinting solutions.

Effect of folic acid on appetite in children: ordinal logistic and fuzzy logistic regressions.

Science.gov (United States)

Namdari, Mahshid; Abadi, Alireza; Taheri, S Mahmoud; Rezaei, Mansour; Kalantari, Naser; Omidvar, Nasrin

2014-03-01

Reduced appetite and low food intake are often a concern in preschool children, since it can lead to malnutrition, a leading cause of impaired growth and mortality in childhood. It is occasionally considered that folic acid has a positive effect on appetite enhancement and consequently growth in children. The aim of this study was to assess the effect of folic acid on the appetite of preschool children 3 to 6 y old. The study sample included 127 children ages 3 to 6 who were randomly selected from 20 preschools in the city of Tehran in 2011. Since appetite was measured by linguistic terms, a fuzzy logistic regression was applied for modeling. The obtained results were compared with a statistical ordinal logistic model. After controlling for the potential confounders, in a statistical ordinal logistic model, serum folate showed a significantly positive effect on appetite. A small but positive effect of folate was detected by fuzzy logistic regression. Based on fuzzy regression, the risk for poor appetite in preschool children was related to the employment status of their mothers. In this study, a positive association was detected between the levels of serum folate and improved appetite. For further investigation, a randomized controlled, double-blind clinical trial could be helpful to address causality. Copyright © 2014 Elsevier Inc. All rights reserved.

Anemia and risk factors in HAART naïve and HAART experienced HIV positive persons in south west Ethiopia: a comparative study.

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Lealem Gedefaw

Full Text Available BACKGROUND: Human immunodeficiency virus (HIV infection and its treatment cause a range of hematological abnormalities. Anemia is one of the commonly observed hematologic manifestations in HIV positive persons and it has multifactorial origin. OBJECTIVE: We aimed to determine the prevalence and risk factors of anemia in highly active antiretroviral therapy (HAART naïve and HAART experienced HIV positive persons. METHODS: A facility-based comparative cross sectional study was conducted in Jimma University Specialized Hospital from February 1 to March 30, 2012. A total of 234 HIV positive persons, 117 HAART naïve and 117 HAART experienced, were enrolled in this study. Blood and stool specimens were collected from each participant. Blood specimens were examined for complete blood count, CD4 count and blood film for malaria hemoparasite; whereas stool specimens were checked for ova of intestinal parasites. Socio-demographic characteristics and clinical data of the participants were collected using pre-tested questionnaire. Statistical analysis of the data (Chi-square, student's t-test, logistic regression was done using SPSS V-16. RESULTS: The overall prevalence of anemia was 23.1%. The prevalence of anemia in HAART naïve and HAART experienced persons was 29.9% and 16.2%, respectively (P = 0.014. Presence of opportunistic infections (P = 0.004, 95% CI = 1.69-15.46, CD4 count <200 cells/µl (P = 0.001, 95% CI = 2.57-36.89 and rural residence (P = 0.03, 95% CI = 1.12-10.39 were found to be predictors of anemia for HAART naïve participants. On the other hand, HAART regimen (ZDV/3TC/NVP (P = 0.019, 95% CI = 0.01-1.24 and the duration of HAART (P = 0.007, 95% CI = 0.003-0.40.24 were found to be predictors of anemia for HAART experienced groups. CONCLUSION: The prevalence of anemia in HAART naïve persons was higher than HAART experienced persons. Risk factors for anemia in HAART naïve and HAART experienced HIV positive persons were different. Hence

Internal and external environmental factors affecting the performance of hospital-based home nursing care.

Science.gov (United States)

Noh, J-W; Kwon, Y-D; Yoon, S-J; Hwang, J-I

2011-06-01

Numerous studies on HNC services have been carried out by signifying their needs, efficiency and effectiveness. However, no study has ever been performed to determine the critical factors associated with HNC's positive results despite the deluge of positive studies on the service. This study included all of the 89 training hospitals that were practising HNC service in Korea as of November 2006. The input factors affecting the performance were classified as either internal or external environmental factors. This analysis was conducted to understand the impact that the corresponding factors had on performance. Data were analysed by using multiple linear regressions. The internal and external environment variables affected the performance of HNC based on univariate analysis. The meaningful variables were internal environmental factors. Specifically, managerial resource (the number of operating beds and the outpatient/inpatient ratio) were meaningful when the multiple linear regression analysis was performed. Indeed, the importance of organizational culture (the passion of HNC nurses) was significant. This study, considering the limited market size of Korea, illustrates that the critical factor for the development of hospital-led HNC lies with internal environmental factors rather than external ones. Among the internal environmental factors, the hospitals' managerial resource-related factors (specifically, the passion of nurses) were the most important contributing element. © 2011 The Authors. International Nursing Review © 2011 International Council of Nurses.

Risk factors associated with the community-acquired colonization of extended-spectrum beta-lactamase (ESBL positive Escherichia Coli. an exploratory case-control study.

Directory of Open Access Journals (Sweden)

Rasmus Leistner

Full Text Available BACKGROUND: The number of extended-spectrum beta-lactamase (ESBL positive (+ Escherichia coli is increasing worldwide. In contrast with many other multidrug-resistant bacteria, it is suspected that they predominantly spread within the community. The objective of this study was to assess factors associated with community-acquired colonization of ESBL (+ E. coli. METHODS: We performed a matched case-control study at the Charité University Hospital Berlin between May 2011 and January 2012. Cases were defined as patients colonized with community-acquired ESBL (+ E. coli identified <72 h after hospital admission. Controls were patients that carried no ESBL-positive bacteria but an ESBL-negative E.coli identified <72 h after hospital admission. Two controls per case were chosen from potential controls according to admission date. Case and control patients completed a questionnaire assessing nutritional habits, travel habits, household situation and language most commonly spoken at home (mother tongue. An additional rectal swab was obtained together with the questionnaire to verify colonization status. Genotypes of ESBL (+ E. coli strains were determined by PCR and sequencing. Risk factors associated with ESBL (+ E. coli colonization were analyzed by a multivariable conditional logistic regression analysis. RESULTS: We analyzed 85 cases and 170 controls, respectively. In the multivariable analysis, speaking an Asian language most commonly at home (OR = 13.4, CI 95% 3.3-53.8; p<0.001 and frequently eating pork (≥ 3 meals per week showed to be independently associated with ESBL colonization (OR = 3.5, CI 95% 1.8-6.6; p<0.001. The most common ESBL genotypes were CTX-M-1 with 44% (n = 37, CTX-M-15 with 28% (n = 24 and CTX-M-14 with 13% (n = 11. CONCLUSION: An Asian mother tongue and frequently consuming certain types of meat like pork can be independently associated with the colonization of ESBL-positive bacteria. We found neither frequent consumption

Are there inequalities in choice of birthing position? Sociodemographic and labour factors associated with the supine position during the second stage of labour

NARCIS (Netherlands)

Rijnders, Marlies E. B.; van Diem, Mariet Th.; Scheepers, Peer L. H.; Lagro-Janssen, Antoine L. M.

Objective: to establish which factors are associated with birthing positions throughout the second stage of tabour and at the time of birth. Design: retrospective cohort study. Setting: primary care midwifery practices in the Netherlands. Participants: 665 low-risk women who received midwife-led

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.

Partial Least Squares Regression for Determining the Control Factors for Runoff and Suspended Sediment Yield during Rainfall Events

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Nufang Fang

2015-07-01

Full Text Available Multivariate statistics are commonly used to identify the factors that control the dynamics of runoff or sediment yields during hydrological processes. However, one issue with the use of conventional statistical methods to address relationships between variables and runoff or sediment yield is multicollinearity. The main objectives of this study were to apply a method for effectively identifying runoff and sediment control factors during hydrological processes and apply that method to a case study. The method combines the clustering approach and partial least squares regression (PLSR models. The case study was conducted in a mountainous watershed in the Three Gorges Area. A total of 29 flood events in three hydrological years in areas with different land uses were obtained. In total, fourteen related variables were separated from hydrographs using the classical hydrograph separation method. Twenty-nine rainfall events were classified into two rainfall regimes (heavy Rainfall Regime I and moderate Rainfall Regime II based on rainfall characteristics and K-means clustering. Four separate PLSR models were constructed to identify the main variables that control runoff and sediment yield for the two rainfall regimes. For Rainfall Regime I, the dominant first-order factors affecting the changes in sediment yield in our study were all of the four rainfall-related variables, flood peak discharge, maximum flood suspended sediment concentration, runoff, and the percentages of forest and farmland. For Rainfall Regime II, antecedent condition-related variables have more effects on both runoff and sediment yield than in Rainfall Regime I. The results suggest that the different control factors of the two rainfall regimes are determined by the rainfall characteristics and thus different runoff mechanisms.

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

The influences of working memory representations on long-range regression in text reading: An eye-tracking study

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Teppei eTanaka

2014-09-01

Full Text Available The present study investigated the relationship between verbal and visuospatial working memory capacity and long-range regression (i.e., word relocation processes in reading. We analyzed eye movements during a whodunit task, in which readers were asked to answer a content question while original text was being presented. The eye movements were more efficient in relocating a target word when the target was at recency positions within the text than when it was at primacy positions. Furthermore, both verbal and visuospatial working memory capacity partly predicted the efficiency of the initial long-range regression. The results indicate that working memory representations have a strong influence at the first stage of long-range regression by driving the first saccade movement toward the correct target position, suggesting that there is a dynamic interaction between internal working memory representations and external actions during text reading.

Identification of epidemiological risk factors for hepatitis C in Punjab, Pakistan

International Nuclear Information System (INIS)

Ghias, M.; Pervaiz, M.K.

2009-01-01

Hepatitis C virus (HCV) is one of the major health issues in Punjab, Pakistan. About 3% of the world population have been infected by hepatitis C virus. The objective of this study was to find out significantly associated factors with Hepatitis C in the region. Demographic, socio-economic and clinical factors were taken in consideration to determine the predictive strength of these associated factors by the logistic regression model approach. This was a hospital based case-control study of 400 patients; out of which 119 were controlled patients (HCV negative) while 281 were cases (HCV positive). Patients admitted in gastroenterology wards of Jinnah, Shaikh Zayed, and Mayo hospitals in Lahore city were interviewed to gather risk factors information. Data was collected in six months starting from April 2006 to September 2006. results from multiple linear logistic regression model for overall data showed that age (OR=1.035, p=0.001), history of blood transfusion (OR=9.204, p=0.004), history of hospitalization (OR=2.979, p=0.043), Tattooing (OR=27.484, p=0.013), family history of hepatitis (OR=4.069, p=0.000), surgical operation (OR=4.290, p=0.030) were found to have significant and positively association with Hepatitis C. Hence our estimated logit model can be used to predict the chance of hepatitis C under the presence or absence of certain significant factors. (author)

Multicenter European Prevalence Study of Neurocognitive Impairment and Associated Factors in HIV Positive Patients

DEFF Research Database (Denmark)

Haddow, Lewis J; Laverick, Rosanna; Daskalopoulou, Marina

2018-01-01

We conducted a cross-sectional study in 448 HIV positive patients attending five European outpatient clinics to determine prevalence of and factors associated with neurocognitive impairment (NCI) using computerized and pen-and-paper neuropsychological tests. NCI was defined as a normalized Z scor...

Deriving amplification factors from simple site parameters using generalized regression neural networks: implications for relevant site proxies

Science.gov (United States)

Boudghene Stambouli, Ahmed; Zendagui, Djawad; Bard, Pierre-Yves; Derras, Boumédiène

2017-07-01

Most modern seismic codes account for site effects using an amplification factor (AF) that modifies the rock acceleration response spectra in relation to a "site condition proxy," i.e., a parameter related to the velocity profile at the site under consideration. Therefore, for practical purposes, it is interesting to identify the site parameters that best control the frequency-dependent shape of the AF. The goal of the present study is to provide a quantitative assessment of the performance of various site condition proxies to predict the main AF features, including the often used short- and mid-period amplification factors, Fa and Fv, proposed by Borcherdt (in Earthq Spectra 10:617-653, 1994). In this context, the linear, viscoelastic responses of a set of 858 actual soil columns from Japan, the USA, and Europe are computed for a set of 14 real accelerograms with varying frequency contents. The correlation between the corresponding site-specific average amplification factors and several site proxies (considered alone or as multiple combinations) is analyzed using the generalized regression neural network (GRNN). The performance of each site proxy combination is assessed through the variance reduction with respect to the initial amplification factor variability of the 858 profiles. Both the whole period range and specific short- and mid-period ranges associated with the Borcherdt factors Fa and Fv are considered. The actual amplification factor of an arbitrary soil profile is found to be satisfactorily approximated with a limited number of site proxies (4-6). As the usual code practice implies a lower number of site proxies (generally one, sometimes two), a sensitivity analysis is conducted to identify the "best performing" site parameters. The best one is the overall velocity contrast between underlying bedrock and minimum velocity in the soil column. Because these are the most difficult and expensive parameters to measure, especially for thick deposits, other

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

Dairy farms testing positive for Mycobacterium avium ssp. paratuberculosis have poorer hygiene practices and are less cautious when purchasing cattle than test-negative herds.

Science.gov (United States)

Wolf, R; Barkema, H W; De Buck, J; Orsel, K

2016-06-01

Mycobacterium avium ssp. paratuberculosis (MAP), the causative agent of Johne's disease, is present on most dairy farms in Alberta, causing economic losses and presenting a potential public health concern. The objective of this cross-sectional study was to identify risk factors for Alberta dairy herds being MAP-positive based on environmental samples (ES). Risk assessments were conducted and ES were collected on 354 Alberta dairy farms (62% of eligible producers) voluntarily participating in the Alberta Johne's Disease Initiative. In univariate logistic regression, risk factors addressing animal and pen hygiene, as well as the use of feeding equipment to remove manure and manure application on pastures, were all associated with the number of positive ES. Furthermore, based on factor analysis, risk factors were clustered and could be summarized as 4 independent factors: (1) animal, pen, and feeder contamination; (2) shared equipment and pasture contamination; (3) calf diet; and (4) cattle purchase. Using these factor scores as independent variables in multivariate logistic regression models, a 1-unit increase in animal, pen, and feeder contamination resulted in 1.31 times higher odds of having at least 1 positive ES. Furthermore, a 1-unit increase in cattle purchase also resulted in 1.31 times the odds of having at least 1 positive ES. Finally, a 100-cow increase in herd size resulted in an odds ratio of 2.1 for having at least 1 positive ES. In conclusion, cleanliness of animals, pens, and feeders, as well as cattle purchase practices, affected risk of herd infection with MAP. Therefore, improvements in those management practices should be the focus of effective tools to control MAP on dairy farms. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Examining the Factor Structure of the Positive and Negative Affect Schedule (PANAS) in a Multiethnic Sample of Adolescents

Science.gov (United States)

Villodas, Feion; Villodas, Miguel T.; Roesch, Scott

2011-01-01

The psychometric properties of the Positive and Negative Affect Schedule were examined in a multiethnic sample of adolescents. Results from confirmatory factor analyses indicated that the original two-factor model did not adequately fit the data. Exploratory factor analyses revealed that four items were not pure markers of the factors. (Contains 1…

Facilitating factors of self-care among HIV-positive young women in Iran: a qualitative study.

Science.gov (United States)

Oskouie, Fatemeh; Kashefi, Farzaneh; Rafii, Forough; Gouya, Mohammad Mehdi; Vahid-Dastjerdi, Marzieh

2018-02-05

Background Providing care for chronic disease such as HIV is a growing challenge in the world. In order to address the challenges of linkage and care in chronic disease management, we need to identify factors that can influence people to get more involved in self-care. This study was part of an extensive qualitative study conducted in Tehran, Iran in 2016. Methods The data were collected through semi-structured interviews conducted on 25 women with HIV, and were analyzed using grounded theory. Four main themes were identified as facilitating self-care among participants: health system support, clinicians' support, family support and improved life expectancy. Sub-themes that emerged were free HIV tests; free medication; free membership in positive clubs; free psychological consultation; positive attitudes and friendly behavior from clinic staff; telephone follow up; support from husbands, mothers and peers; hope for recovery; hope for the future; and love for own children. Results Our results showed that, providing appropriate support and services, as well as a positive attitude of society towards HIV positive women, can contribute to adherence to self-care in young women with HIV. Conclusion Understanding the facilitating factors based on the patients' experiences can contribute to the development of new policies and procedures to improve the care of these patients.

Personality, Driving Behavior and Mental Disorders Factors as Predictors of Road Traffic Accidents Based on Logistic Regression.

Science.gov (United States)

Alavi, Seyyed Salman; Mohammadi, Mohammad Reza; Souri, Hamid; Mohammadi Kalhori, Soroush; Jannatifard, Fereshteh; Sepahbodi, Ghazal

2017-01-01

The aim of this study was to evaluate the effect of variables such as personality traits, driving behavior and mental illness on road traffic accidents among the drivers with accidents and those without road crash. In this cohort study, 800 bus and truck drivers were recruited. Participants were selected among drivers who referred to Imam Sajjad Hospital (Tehran, Iran) during 2013-2015. The Manchester driving behavior questionnaire (MDBQ), big five personality test (NEO personality inventory) and semi-structured interview (schizophrenia and affective disorders scale) were used. After two years, we surveyed all accidents due to human factors that involved the recruited drivers. The data were analyzed using the SPSS software by performing the descriptive statistics, t-test, and multiple logistic regression analysis methods. P values less than 0.05 were considered statistically significant. In terms of controlling the effective and demographic variables, the findings revealed significant differences between the two groups of drivers that were and were not involved in road accidents. In addition, it was found that depression and anxiety could increase the odds ratio (OR) of road accidents by 2.4- and 2.7-folds, respectively (P=0.04, P=0.004). It is noteworthy to mention that neuroticism alone can increase the odds of road accidents by 1.1-fold (P=0.009), but other personality factors did not have a significant effect on the equation. The results revealed that some mental disorders affect the incidence of road collisions. Considering the importance and sensitivity of driving behavior, it is necessary to evaluate multiple psychological factors influencing drivers before and after receiving or renewing their driver's license.

Personality, Driving Behavior and Mental Disorders Factors as Predictors of Road Traffic Accidents Based on Logistic Regression

Science.gov (United States)

Alavi, Seyyed Salman; Mohammadi, Mohammad Reza; Souri, Hamid; Mohammadi Kalhori, Soroush; Jannatifard, Fereshteh; Sepahbodi, Ghazal

2017-01-01

Background: The aim of this study was to evaluate the effect of variables such as personality traits, driving behavior and mental illness on road traffic accidents among the drivers with accidents and those without road crash. Methods: In this cohort study, 800 bus and truck drivers were recruited. Participants were selected among drivers who referred to Imam Sajjad Hospital (Tehran, Iran) during 2013-2015. The Manchester driving behavior questionnaire (MDBQ), big five personality test (NEO personality inventory) and semi-structured interview (schizophrenia and affective disorders scale) were used. After two years, we surveyed all accidents due to human factors that involved the recruited drivers. The data were analyzed using the SPSS software by performing the descriptive statistics, t-test, and multiple logistic regression analysis methods. P values less than 0.05 were considered statistically significant. Results: In terms of controlling the effective and demographic variables, the findings revealed significant differences between the two groups of drivers that were and were not involved in road accidents. In addition, it was found that depression and anxiety could increase the odds ratio (OR) of road accidents by 2.4- and 2.7-folds, respectively (P=0.04, P=0.004). It is noteworthy to mention that neuroticism alone can increase the odds of road accidents by 1.1-fold (P=0.009), but other personality factors did not have a significant effect on the equation. Conclusion: The results revealed that some mental disorders affect the incidence of road collisions. Considering the importance and sensitivity of driving behavior, it is necessary to evaluate multiple psychological factors influencing drivers before and after receiving or renewing their driver’s license. PMID:28293047

Personality, Driving Behavior and Mental Disorders Factors as Predictors of Road Traffic Accidents Based on Logistic Regression

Directory of Open Access Journals (Sweden)

Seyyed Salman Alavi

2017-01-01

Full Text Available Background: The aim of this study was to evaluate the effect of variables such as personality traits, driving behavior and mental illness on road traffic accidents among the drivers with accidents and those without road crash. Methods: In this cohort study, 800 bus and truck drivers were recruited. Participants were selected among drivers who referred to Imam Sajjad Hospital (Tehran, Iran during 2013-2015. The Manchester driving behavior questionnaire (MDBQ, big five personality test (NEO personality inventory and semi-structured interview (SADS were used. After two years, we surveyed all accidents due to human factors that involved the recruited drivers. The data were analyzed using the SPSS software by performing the descriptive statistics, t-test, and multiple logistic regression analysis methods. P values less than 0.05 were considered statistically significant. Results: In terms of controlling the effective and demographic variables, the findings revealed significant differences between the two groups of drivers that were and were not involved in road accidents. In addition, it was found that depression and anxiety could increase the odds ratio (OR of road accidents by 2.4- and 2.7-folds, respectively (P=0.04, P=0.004. It is noteworthy to mention that neuroticism alone can increase the odds of road accidents by 1.1-fold (P=0.009, but other personality factors did not have a significant effect on the equation. Conclusion: The results revealed that some mental disorders affect the incidence of road collisions. Considering the importance and sensitivity of driving behavior, it is necessary to evaluate multiple psychological factors influencing drivers before and after receiving or renewing their driver’s license.

An analysis of motivation factors for students' pursuit of leadership positions.

Science.gov (United States)

Phillips, Jennifer A; McLaughlin, Milena M; Gettig, Jacob P; Fajiculay, Jay R; Advincula, M Renee

2015-02-17

To identify factors that influence student involvement and leadership within organizations and to assess the impact of involvement in organizations on professional skill development. A printed survey was administered to fourth-year pharmacy students at one college of pharmacy (N=202). Most students (82%) indicated they were involved in at least one organization during pharmacy school and 58% reported holding a leadership position at some point. Factors with the largest impact on involvement in organizations were desire to present a well-rounded image to employers, ability to network, and interest in the activities sponsored by the organization. Involvement in professional organizations had a strong influence on their leadership, teamwork, confidence, and time-management skills. That presenting a well-rounded image to employers and having the ability to network with mentors and peers drove student involvement in professional organizations may be reflective of increasing competition for residencies and jobs.

Quality of life in breast cancer patients--a quantile regression analysis.

Science.gov (United States)

Pourhoseingholi, Mohamad Amin; Safaee, Azadeh; Moghimi-Dehkordi, Bijan; Zeighami, Bahram; Faghihzadeh, Soghrat; Tabatabaee, Hamid Reza; Pourhoseingholi, Asma

2008-01-01

Quality of life study has an important role in health care especially in chronic diseases, in clinical judgment and in medical resources supplying. Statistical tools like linear regression are widely used to assess the predictors of quality of life. But when the response is not normal the results are misleading. The aim of this study is to determine the predictors of quality of life in breast cancer patients, using quantile regression model and compare to linear regression. A cross-sectional study conducted on 119 breast cancer patients that admitted and treated in chemotherapy ward of Namazi hospital in Shiraz. We used QLQ-C30 questionnaire to assessment quality of life in these patients. A quantile regression was employed to assess the assocciated factors and the results were compared to linear regression. All analysis carried out using SAS. The mean score for the global health status for breast cancer patients was 64.92+/-11.42. Linear regression showed that only grade of tumor, occupational status, menopausal status, financial difficulties and dyspnea were statistically significant. In spite of linear regression, financial difficulties were not significant in quantile regression analysis and dyspnea was only significant for first quartile. Also emotion functioning and duration of disease statistically predicted the QOL score in the third quartile. The results have demonstrated that using quantile regression leads to better interpretation and richer inference about predictors of the breast cancer patient quality of life.

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression.

Science.gov (United States)

Chen, Qiang; Mei, Kun; Dahlgren, Randy A; Wang, Ting; Gong, Jian; Zhang, Minghua

2016-12-01

As an important regulator of pollutants in overland flow and interflow, land use has become an essential research component for determining the relationships between surface water quality and pollution sources. This study investigated the use of ordinary least squares (OLS) and geographically weighted regression (GWR) models to identify the impact of land use and population density on surface water quality in the Wen-Rui Tang River watershed of eastern China. A manual variable excluding-selecting method was explored to resolve multicollinearity issues. Standard regression coefficient analysis coupled with cluster analysis was introduced to determine which variable had the greatest influence on water quality. Results showed that: (1) Impact of land use on water quality varied with spatial and seasonal scales. Both positive and negative effects for certain land-use indicators were found in different subcatchments. (2) Urban land was the dominant factor influencing N, P and chemical oxygen demand (COD) in highly urbanized regions, but the relationship was weak as the pollutants were mainly from point sources. Agricultural land was the primary factor influencing N and P in suburban and rural areas; the relationship was strong as the pollutants were mainly from agricultural surface runoff. Subcatchments located in suburban areas were identified with urban land as the primary influencing factor during the wet season while agricultural land was identified as a more prevalent influencing factor during the dry season. (3) Adjusted R 2 values in OLS models using the manual variable excluding-selecting method averaged 14.3% higher than using stepwise multiple linear regressions. However, the corresponding GWR models had adjusted R 2 ~59.2% higher than the optimal OLS models, confirming that GWR models demonstrated better prediction accuracy. Based on our findings, water resource protection policies should consider site-specific land-use conditions within each watershed to

PROGNOSTIC FACTORS OF POSITIVE RESULTS OF MULTIFOCAL TRUS-GUIDED VESICOURETHRAL ANASTOMOSIS BIOPSY IN PATIENTS WITH BIOCHEMICAL RECURRENCE AFTER RADICAL PROSTATECTOMY

Directory of Open Access Journals (Sweden)

P. D. Demeshko

2014-07-01

Full Text Available Purpose. To evaluate influence of clinical, biochemical and histological factors to detection rate of local recurrence following radical prostatectomy (RPE using multifocal TRUS-guided vesicourethral anastomosis (VUA biopsy.Material and methods. 59 patients with newly diagnosed biochemical recurrence (BR after RPE were included into prospective study. All of them underwent multifocal TRUS-guided VUA biopsy. Сlinical variables (serum prostate-specifi c antigen [PSA] level and PSA kinetics, time RPE-BR, Gleason grade, stage after RPE and clinical findings were evaluated. Logistic regression and receiver operating characteristic (ROC curve analyses were performed.Results. The detection rate of local prostate recurrence with TRUS-guided VUA biopsy was 45,8 % (95 % CI 33,7–58,3. At multivariate analysis only PSA level at the moment of biopsy (≤ 1,5 ng/ml vs > 1,5 ng/ml and time RPE-BR (≤ 15 months vs > 15 months were significantly associated with positive results of multifocal TRUS-guided VUA biopsy (p < 0,05.Conclusion The detection rate of local prostate recurrence with TRUS-guided VUA biopsy depends on combination of independent predictors (PSA level at the moment of biopsy and time RPE—BR.

Mapping geogenic radon potential by regression kriging

Energy Technology Data Exchange (ETDEWEB)

Pásztor, László [Institute for Soil Sciences and Agricultural Chemistry, Centre for Agricultural Research, Hungarian Academy of Sciences, Department of Environmental Informatics, Herman Ottó út 15, 1022 Budapest (Hungary); Szabó, Katalin Zsuzsanna, E-mail: sz_k_zs@yahoo.de [Department of Chemistry, Institute of Environmental Science, Szent István University, Páter Károly u. 1, Gödöllő 2100 (Hungary); Szatmári, Gábor; Laborczi, Annamária [Institute for Soil Sciences and Agricultural Chemistry, Centre for Agricultural Research, Hungarian Academy of Sciences, Department of Environmental Informatics, Herman Ottó út 15, 1022 Budapest (Hungary); Horváth, Ákos [Department of Atomic Physics, Eötvös University, Pázmány Péter sétány 1/A, 1117 Budapest (Hungary)

2016-02-15

Radon ({sup 222}Rn) gas is produced in the radioactive decay chain of uranium ({sup 238}U) which is an element that is naturally present in soils. Radon is transported mainly by diffusion and convection mechanisms through the soil depending mainly on the physical and meteorological parameters of the soil and can enter and accumulate in buildings. Health risks originating from indoor radon concentration can be attributed to natural factors and is characterized by geogenic radon potential (GRP). Identification of areas with high health risks require spatial modeling, that is, mapping of radon risk. In addition to geology and meteorology, physical soil properties play a significant role in the determination of GRP. In order to compile a reliable GRP map for a model area in Central-Hungary, spatial auxiliary information representing GRP forming environmental factors were taken into account to support the spatial inference of the locally measured GRP values. Since the number of measured sites was limited, efficient spatial prediction methodologies were searched for to construct a reliable map for a larger area. Regression kriging (RK) was applied for the interpolation using spatially exhaustive auxiliary data on soil, geology, topography, land use and climate. RK divides the spatial inference into two parts. Firstly, the deterministic component of the target variable is determined by a regression model. The residuals of the multiple linear regression analysis represent the spatially varying but dependent stochastic component, which are interpolated by kriging. The final map is the sum of the two component predictions. Overall accuracy of the map was tested by Leave-One-Out Cross-Validation. Furthermore the spatial reliability of the resultant map is also estimated by the calculation of the 90% prediction interval of the local prediction values. The applicability of the applied method as well as that of the map is discussed briefly. - Highlights: • A new method

Mapping geogenic radon potential by regression kriging

International Nuclear Information System (INIS)

Pásztor, László; Szabó, Katalin Zsuzsanna; Szatmári, Gábor; Laborczi, Annamária; Horváth, Ákos

2016-01-01

Radon ( 222 Rn) gas is produced in the radioactive decay chain of uranium ( 238 U) which is an element that is naturally present in soils. Radon is transported mainly by diffusion and convection mechanisms through the soil depending mainly on the physical and meteorological parameters of the soil and can enter and accumulate in buildings. Health risks originating from indoor radon concentration can be attributed to natural factors and is characterized by geogenic radon potential (GRP). Identification of areas with high health risks require spatial modeling, that is, mapping of radon risk. In addition to geology and meteorology, physical soil properties play a significant role in the determination of GRP. In order to compile a reliable GRP map for a model area in Central-Hungary, spatial auxiliary information representing GRP forming environmental factors were taken into account to support the spatial inference of the locally measured GRP values. Since the number of measured sites was limited, efficient spatial prediction methodologies were searched for to construct a reliable map for a larger area. Regression kriging (RK) was applied for the interpolation using spatially exhaustive auxiliary data on soil, geology, topography, land use and climate. RK divides the spatial inference into two parts. Firstly, the deterministic component of the target variable is determined by a regression model. The residuals of the multiple linear regression analysis represent the spatially varying but dependent stochastic component, which are interpolated by kriging. The final map is the sum of the two component predictions. Overall accuracy of the map was tested by Leave-One-Out Cross-Validation. Furthermore the spatial reliability of the resultant map is also estimated by the calculation of the 90% prediction interval of the local prediction values. The applicability of the applied method as well as that of the map is discussed briefly. - Highlights: • A new method, regression

Factors Influencing the General Well-Being of Low-Income Korean Immigrant Elders

Science.gov (United States)

Lee, Kyoung Hag; Yoon, Dong Pil

2011-01-01

This study explores factors that influence the general well-being (anxiety, depression, positive well-being, self-control, vitality, and general health) of low-income Korean immigrant elders by interviewing 206 older adults living in Los Angeles County and Orange County, California. Ordinary least squares regression results reveal that lack of…

Modeling the potential risk factors of bovine viral diarrhea prevalence in Egypt using univariable and multivariable logistic regression analyses

Directory of Open Access Journals (Sweden)

Abdelfattah M. Selim

2018-03-01

Full Text Available Aim: The present cross-sectional study was conducted to determine the seroprevalence and potential risk factors associated with Bovine viral diarrhea virus (BVDV disease in cattle and buffaloes in Egypt, to model the potential risk factors associated with the disease using logistic regression (LR models, and to fit the best predictive model for the current data. Materials and Methods: A total of 740 blood samples were collected within November 2012-March 2013 from animals aged between 6 months and 3 years. The potential risk factors studied were species, age, sex, and herd location. All serum samples were examined with indirect ELIZA test for antibody detection. Data were analyzed with different statistical approaches such as Chi-square test, odds ratios (OR, univariable, and multivariable LR models. Results: Results revealed a non-significant association between being seropositive with BVDV and all risk factors, except for species of animal. Seroprevalence percentages were 40% and 23% for cattle and buffaloes, respectively. OR for all categories were close to one with the highest OR for cattle relative to buffaloes, which was 2.237. Likelihood ratio tests showed a significant drop of the -2LL from univariable LR to multivariable LR models. Conclusion: There was an evidence of high seroprevalence of BVDV among cattle as compared with buffaloes with the possibility of infection in different age groups of animals. In addition, multivariable LR model was proved to provide more information for association and prediction purposes relative to univariable LR models and Chi-square tests if we have more than one predictor.

Pregnancy failure in patients with obstetric antiphospholipid syndrome with conventional treatment: the influence of a triple positive antibody profile.

Science.gov (United States)

Latino, J O; Udry, S; Aranda, F M; Perés Wingeyer, S D A; Fernández Romero, D S; de Larrañaga, G F

2017-08-01

Conventional treatment of obstetric antiphospholipid syndrome fails in approximately 20-30% of pregnant women without any clearly identified risk factor. It is important to identify risk factors that are associated with these treatment failures. This study aimed to assess the impact of risk factors on pregnancy outcomes in women with obstetric antiphospholipid syndrome treated with conventional treatment. We carefully retrospectively selected 106 pregnancies in women with obstetric antiphospholipid syndrome treated with heparin + aspirin. Pregnancy outcomes were evaluated according to the following associated risk factors: triple positivity profile, double positivity profile, single positivity profile, history of thrombosis, autoimmune disease, more than four pregnancy losses, and high titers of anticardiolipin antibodies and/or anti-βeta-2-glycoprotein-I (aβ2GPI) antibodies. To establish the association between pregnancy outcomes and risk factors, a single binary logistic regressions analysis was performed. Risk factors associated with pregnancy loss with conventional treatment were: the presence of triple positivity (OR = 5.0, CI = 1.4-16.9, p = 0.01), high titers of aβ2GPI (OR = 4.4, CI = 1.2-16.1, p = 0.023) and a history of more than four pregnancy losses (OR = 3.5, CI = 1.2-10.0, p = 0.018). The presence of triple positivity was an independent risk factor associated with gestational complications (OR = 4.1, CI = 1.2-13.9, p = 0.02). Our findings reinforce the idea that triple positivity is a categorical risk factor for poor response to conventional treatment.

Spontaneous regression of metastases from melanoma: review of the literature

DEFF Research Database (Denmark)

Kalialis, Louise Vennegaard; Drzewiecki, Krzysztof T; Klyver, Helle

2009-01-01

Regression of metastatic melanoma is a rare event, and review of the literature reveals a total of 76 reported cases since 1866. The proposed mechanisms include immunologic, endocrine, inflammatory and metastatic tumour nutritional factors. We conclude from this review that although the precise...

[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.

Resilience and positive affect contribute to lower cancer-related fatigue among Chinese patients with gastric cancer.

Science.gov (United States)

Zou, Guiyuan; Li, Ye; Xu, Ruicai; Li, Ping

2018-04-01

To investigate the prevalence of cancer-related fatigue and explore the relationship between resilience, positive affect, and fatigue among Chinese patients with gastric cancer. Cancer-related fatigue is the most distressing symptom reported frequently by cancer patients during both treatment and survival phases. Resilience and positive affect as vital protective factors against cancer-related fatigue have been examined, but the underlying psychological mechanisms are not well understood. A cross-sectional study. Two hundred and three gastric cancer patients were enrolled from three hospitals in China. The Cancer Fatigue Scale, the positive affect subscale of the Positive and Negative Affect Schedule and the Connor-Davidson Resilience Scale (CD-RISC10) were administered. Hierarchical linear regression modelling was conducted to examine the association between resilience and cancer-related fatigue, and the mediating effect of positive affect. The incidence of clinically relevant fatigue among patients with gastric cancer was 91.6%. Regression analysis showed that resilience was negatively associated with cancer-related fatigue, explaining 15.4% of variance in cancer-related fatigue. Mediation analysis showed that high resilience was associated with increased positive affect, which was associated with decreased cancer-related fatigue. Cancer-related fatigue is prevalent among patients with gastric cancer. Positive affect may mediate the relationship between resilience and cancer-related fatigue. Interventions that attend to resilience training and promotion of positive affect may be the focus for future clinical and research endeavours. © 2017 John Wiley & Sons Ltd.

Is adult gait less susceptible than paediatric gait to hip joint centre regression equation error?

Science.gov (United States)

Kiernan, D; Hosking, J; O'Brien, T

2016-03-01

Hip joint centre (HJC) regression equation error during paediatric gait has recently been shown to have clinical significance. In relation to adult gait, it has been inferred that comparable errors with children in absolute HJC position may in fact result in less significant kinematic and kinetic error. This study investigated the clinical agreement of three commonly used regression equation sets (Bell et al., Davis et al. and Orthotrak) for adult subjects against the equations of Harrington et al. The relationship between HJC position error and subject size was also investigated for the Davis et al. set. Full 3-dimensional gait analysis was performed on 12 healthy adult subjects with data for each set compared to Harrington et al. The Gait Profile Score, Gait Variable Score and GDI-kinetic were used to assess clinical significance while differences in HJC position between the Davis and Harrington sets were compared to leg length and subject height using regression analysis. A number of statistically significant differences were present in absolute HJC position. However, all sets fell below the clinically significant thresholds (GPS <1.6°, GDI-Kinetic <3.6 points). Linear regression revealed a statistically significant relationship for both increasing leg length and increasing subject height with decreasing error in anterior/posterior and superior/inferior directions. Results confirm a negligible clinical error for adult subjects suggesting that any of the examined sets could be used interchangeably. Decreasing error with both increasing leg length and increasing subject height suggests that the Davis set should be used cautiously on smaller subjects. Copyright © 2016 Elsevier B.V. All rights reserved.

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

Predicting respiratory tumor motion with multi-dimensional adaptive filters and support vector regression

International Nuclear Information System (INIS)

Riaz, Nadeem; Wiersma, Rodney; Mao Weihua; Xing Lei; Shanker, Piyush; Gudmundsson, Olafur; Widrow, Bernard

2009-01-01

Intra-fraction tumor tracking methods can improve radiation delivery during radiotherapy sessions. Image acquisition for tumor tracking and subsequent adjustment of the treatment beam with gating or beam tracking introduces time latency and necessitates predicting the future position of the tumor. This study evaluates the use of multi-dimensional linear adaptive filters and support vector regression to predict the motion of lung tumors tracked at 30 Hz. We expand on the prior work of other groups who have looked at adaptive filters by using a general framework of a multiple-input single-output (MISO) adaptive system that uses multiple correlated signals to predict the motion of a tumor. We compare the performance of these two novel methods to conventional methods like linear regression and single-input, single-output adaptive filters. At 400 ms latency the average root-mean-square-errors (RMSEs) for the 14 treatment sessions studied using no prediction, linear regression, single-output adaptive filter, MISO and support vector regression are 2.58, 1.60, 1.58, 1.71 and 1.26 mm, respectively. At 1 s, the RMSEs are 4.40, 2.61, 3.34, 2.66 and 1.93 mm, respectively. We find that support vector regression most accurately predicts the future tumor position of the methods studied and can provide a RMSE of less than 2 mm at 1 s latency. Also, a multi-dimensional adaptive filter framework provides improved performance over single-dimension adaptive filters. Work is underway to combine these two frameworks to improve performance.

De-novo discovery of differentially abundant transcription factor binding sites including their positional preference.

Science.gov (United States)

Keilwagen, Jens; Grau, Jan; Paponov, Ivan A; Posch, Stefan; Strickert, Marc; Grosse, Ivo

2011-02-10

Transcription factors are a main component of gene regulation as they activate or repress gene expression by binding to specific binding sites in promoters. The de-novo discovery of transcription factor binding sites in target regions obtained by wet-lab experiments is a challenging problem in computational biology, which has not been fully solved yet. Here, we present a de-novo motif discovery tool called Dispom for finding differentially abundant transcription factor binding sites that models existing positional preferences of binding sites and adjusts the length of the motif in the learning process. Evaluating Dispom, we find that its prediction performance is superior to existing tools for de-novo motif discovery for 18 benchmark data sets with planted binding sites, and for a metazoan compendium based on experimental data from micro-array, ChIP-chip, ChIP-DSL, and DamID as well as Gene Ontology data. Finally, we apply Dispom to find binding sites differentially abundant in promoters of auxin-responsive genes extracted from Arabidopsis thaliana microarray data, and we find a motif that can be interpreted as a refined auxin responsive element predominately positioned in the 250-bp region upstream of the transcription start site. Using an independent data set of auxin-responsive genes, we find in genome-wide predictions that the refined motif is more specific for auxin-responsive genes than the canonical auxin-responsive element. In general, Dispom can be used to find differentially abundant motifs in sequences of any origin. However, the positional distribution learned by Dispom is especially beneficial if all sequences are aligned to some anchor point like the transcription start site in case of promoter sequences. We demonstrate that the combination of searching for differentially abundant motifs and inferring a position distribution from the data is beneficial for de-novo motif discovery. Hence, we make the tool freely available as a component of the open

Impact of Dobutamine in Patients With Septic Shock: A Meta-Regression Analysis.

Science.gov (United States)

Nadeem, Rashid; Sockanathan, Shivani; Singh, Mukesh; Hussain, Tamseela; Kent, Patrick; AbuAlreesh, Sarah

2017-05-01

Septic shock frequently requires vasopressor agents. Conflicting evidence exists for use of inotropes in patients with septic shock. Data from English studies on human adult septic shock patients were collected. A total of 83 studies were reviewed, while 11 studies with 21 data sets including 239 patients were pooled for meta-regression analysis. For VO2, pooled difference in means (PDM) was 0.274. For cardiac index (CI), PDM was 0.783. For delivery of oxygen, PDM was -0.890. For heart rate, PDM was -0.714. For left ventricle stroke work index, PDM was 0.375. For mean arterial pressure, PDM was -0.204. For mean pulmonary artery pressure, PDM was 0.085. For O2 extraction, PDM was 0.647. For PaCO2, PDM was -0.053. For PaO2, PDM was 0.282. For pulmonary artery occlusive pressure, PDM was 0.270. For pulmonary capillary wedge pressure, PDM was 0.300. For PVO2, PDM was -0.492. For right atrial pressure, PDM was 0.246. For SaO2, PDM was 0.604. For stroke volume index, PDM was 0.446. For SvO2, PDM was -0.816. For systemic vascular resistance, PDM was -0.600. For systemic vascular resistance index, PDM was 0.319. Meta-regression analysis was performed for VO2, DO2, CI, and O2 extraction. Age was found to be significant confounding factor for CI, DO2, and O2 extraction. APACHE score was not found to be a significant confounding factor for any of the parameters. Dobutamine seems to have a positive effect on cardiovascular parameters in patients with septic shock. Prospective studies with larger samples are required to further validate this observation.

T cell receptor (TCR-transgenic CD8 lymphocytes rendered insensitive to transforming growth factor beta (TGFβ signaling mediate superior tumor regression in an animal model of adoptive cell therapy

Directory of Open Access Journals (Sweden)

Quatromoni Jon G

2012-06-01

Full Text Available Abstract Tumor antigen-reactive T cells must enter into an immunosuppressive tumor microenvironment, continue to produce cytokine and deliver apoptotic death signals to affect tumor regression. Many tumors produce transforming growth factor beta (TGFβ, which inhibits T cell activation, proliferation and cytotoxicity. In a murine model of adoptive cell therapy, we demonstrate that transgenic Pmel-1 CD8 T cells, rendered insensitive to TGFβ by transduction with a TGFβ dominant negative receptor II (DN, were more effective in mediating regression of established B16 melanoma. Smaller numbers of DN Pmel-1 T cells effectively mediated tumor regression and retained the ability to produce interferon-γ in the tumor microenvironment. These results support efforts to incorporate this DN receptor in clinical trials of adoptive cell therapy for cancer.

Comparison of Linear and Non-linear Regression Analysis to Determine Pulmonary Pressure in Hyperthyroidism.

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Scarneciu, Camelia C; Sangeorzan, Livia; Rus, Horatiu; Scarneciu, Vlad D; Varciu, Mihai S; Andreescu, Oana; Scarneciu, Ioan

2017-01-01

This study aimed at assessing the incidence of pulmonary hypertension (PH) at newly diagnosed hyperthyroid patients and at finding a simple model showing the complex functional relation between pulmonary hypertension in hyperthyroidism and the factors causing it. The 53 hyperthyroid patients (H-group) were evaluated mainly by using an echocardiographical method and compared with 35 euthyroid (E-group) and 25 healthy people (C-group). In order to identify the factors causing pulmonary hypertension the statistical method of comparing the values of arithmetical means is used. The functional relation between the two random variables (PAPs and each of the factors determining it within our research study) can be expressed by linear or non-linear function. By applying the linear regression method described by a first-degree equation the line of regression (linear model) has been determined; by applying the non-linear regression method described by a second degree equation, a parabola-type curve of regression (non-linear or polynomial model) has been determined. We made the comparison and the validation of these two models by calculating the determination coefficient (criterion 1), the comparison of residuals (criterion 2), application of AIC criterion (criterion 3) and use of F-test (criterion 4). From the H-group, 47% have pulmonary hypertension completely reversible when obtaining euthyroidism. The factors causing pulmonary hypertension were identified: previously known- level of free thyroxin, pulmonary vascular resistance, cardiac output; new factors identified in this study- pretreatment period, age, systolic blood pressure. According to the four criteria and to the clinical judgment, we consider that the polynomial model (graphically parabola- type) is better than the linear one. The better model showing the functional relation between the pulmonary hypertension in hyperthyroidism and the factors identified in this study is given by a polynomial equation of second

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.

The Use of a Poisson Regression to Evaluate Antihistamines and Fatal Aircraft Mishaps in Instrument Meteorological Conditions.

Science.gov (United States)

Gildea, Kevin M; Hileman, Christy R; Rogers, Paul; Salazar, Guillermo J; Paskoff, Lawrence N

2018-04-01

Research indicates that first-generation antihistamine usage may impair pilot performance by increasing the likelihood of vestibular illusions, spatial disorientation, and/or cognitive impairment. Second- and third-generation antihistamines generally have fewer impairing side effects and are approved for pilot use. We hypothesized that toxicological findings positive for second- and third-generation antihistamines are less likely to be associated with pilots involved in fatal mishaps than first-generation antihistamines. The evaluated population consisted of 1475 U.S. civil pilots fatally injured between September 30, 2008, and October 1, 2014. Mishap factors evaluated included year, weather conditions, airman rating, recent airman flight time, quarter of year, and time of day. Due to the low prevalence of positive antihistamine findings, a count-based model was selected, which can account for rare outcomes. The means and variances were close for both regression models supporting the assumption that the data follow a Poisson distribution; first-generation antihistamine mishap airmen (N = 582, M = 0.17, S2 = 0.17) with second- and third-generation antihistamine mishap airmen (N = 116, M = 0.20, S2 = 0.18). The data indicate fewer airmen with second- and third-generation antihistamines than first-generation antihistamines in their system are fatally injured while flying in IMC conditions. Whether the lower incidence is a factor of greater usage of first-generation antihistamines versus second- and third-generation antihistamines by the pilot population or fewer deleterious side effects with second- and third-generation antihistamines is unclear. These results engender cautious optimism, but additional research is necessary to determine why these differences exist.Gildea KM, Hileman CR, Rogers P, Salazar GJ, Paskoff LN. The use of a Poisson regression to evaluate antihistamines and fatal aircraft mishaps in instrument meteorological conditions. Aerosp Med Hum Perform

Semiparametric nonlinear quantile regression model for financial returns

Czech Academy of Sciences Publication Activity Database

Avdulaj, Krenar; Baruník, Jozef

2017-01-01

Roč. 21, č. 1 (2017), s. 81-97 ISSN 1081-1826 R&D Projects: GA ČR(CZ) GBP402/12/G097 Institutional support: RVO:67985556 Keywords : copula quantile regression * realized volatility * value-at-risk Subject RIV: AH - Economic s OBOR OECD: Applied Economic s, Econometrics Impact factor: 0.649, year: 2016 http://library.utia.cas.cz/separaty/2017/E/avdulaj-0472346.pdf

On-line mixture-based alternative to logistic regression

Czech Academy of Sciences Publication Activity Database

Nagy, Ivan; Suzdaleva, Evgenia

2016-01-01

Roč. 26, č. 5 (2016), s. 417-437 ISSN 1210-0552 R&D Projects: GA ČR GA15-03564S Institutional support: RVO:67985556 Keywords : on-line modeling * on-line logistic regression * recursive mixture estimation * data dependent pointer Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.394, year: 2016 http://library.utia.cas.cz/separaty/2016/ZS/suzdaleva-0464463.pdf

Benefits of Seating and Positioning on the Wheelchairs and Factors that Interfere with its Use: a systematic review

Directory of Open Access Journals (Sweden)

Micaele Kedma Ribeiro de Moraes

2016-12-01

Full Text Available Seating and positioning are an assistive technology resource that aims to improve functional performance in the wheelchair. The aim of this paper was to find in the literature studies that addressed the benefits of seating and positioning in a wheelchair and factors that interfere with the prescription and use of this technology. Articles found that discuss the benefits addressed: the functionality and respiratory function; the pressure ulcer prevention; and user satisfaction and the family with assistive technology. Articles discussing the factors linked to prescription and use of adapting wheelchairs are those that address the environmental factors, components and wheelchair accessories. There are factors involved in the prescription process to achieve its benefits through its use, the prescribed process must have an interdisciplinary and biopsychosocial approach applied individually to each patient.

Prediction, Regression and Critical Realism

DEFF Research Database (Denmark)

Næss, Petter

2004-01-01

This paper considers the possibility of prediction in land use planning, and the use of statistical research methods in analyses of relationships between urban form and travel behaviour. Influential writers within the tradition of critical realism reject the possibility of predicting social...... phenomena. This position is fundamentally problematic to public planning. Without at least some ability to predict the likely consequences of different proposals, the justification for public sector intervention into market mechanisms will be frail. Statistical methods like regression analyses are commonly...... seen as necessary in order to identify aggregate level effects of policy measures, but are questioned by many advocates of critical realist ontology. Using research into the relationship between urban structure and travel as an example, the paper discusses relevant research methods and the kinds...

The Role of the Big Five Personality Factors in Mindfulness

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*Gh. Maleki

2014-12-01

Full Text Available Mindfulness is defined as paying attention ability on purpose, in the present moment, and nonjudgmentally. The purpose of this study was to study the relationship between mindfulness and big five factors of personality. In a correlational study, 304 (135 male and 169 female student of Shahid Beheshti Universitiy were selected by convenient sampling method. Mindful Attention Awareness Scale (MAAS and the short form of NEO questionnaire (NEO-FFI were used as the research tools. Data were analyzed through Pearson correlation and stepwise regressions. The results of Pearson correlation showed that mindfulness is positively correlated with extraversion, openness and conscientiousness and negatively correlated with neuroticisms (P<0.001. The results of stepwise regressions indicated predictive role of neuroticism, openness, extraversion, and conscientiousness factors in mindfulness ability of participants. According to the results of present study, these four factors of personality are significant predictors of mindfulness ability of participants. The results of this study were discussed toward the better understanding of mindfulness construct.

Learning Inverse Rig Mappings by Nonlinear Regression.

Science.gov (United States)

Holden, Daniel; Saito, Jun; Komura, Taku

2017-03-01

We present a framework to design inverse rig-functions-functions that map low level representations of a character's pose such as joint positions or surface geometry to the representation used by animators called the animation rig. Animators design scenes using an animation rig, a framework widely adopted in animation production which allows animators to design character poses and geometry via intuitive parameters and interfaces. Yet most state-of-the-art computer animation techniques control characters through raw, low level representations such as joint angles, joint positions, or vertex coordinates. This difference often stops the adoption of state-of-the-art techniques in animation production. Our framework solves this issue by learning a mapping between the low level representations of the pose and the animation rig. We use nonlinear regression techniques, learning from example animation sequences designed by the animators. When new motions are provided in the skeleton space, the learned mapping is used to estimate the rig controls that reproduce such a motion. We introduce two nonlinear functions for producing such a mapping: Gaussian process regression and feedforward neural networks. The appropriate solution depends on the nature of the rig and the amount of data available for training. We show our framework applied to various examples including articulated biped characters, quadruped characters, facial animation rigs, and deformable characters. With our system, animators have the freedom to apply any motion synthesis algorithm to arbitrary rigging and animation pipelines for immediate editing. This greatly improves the productivity of 3D animation, while retaining the flexibility and creativity of artistic input.

The likelihood of achieving quantified road safety targets: a binary logistic regression model for possible factors.

Science.gov (United States)

Sze, N N; Wong, S C; Lee, C Y

2014-12-01

In past several decades, many countries have set quantified road safety targets to motivate transport authorities to develop systematic road safety strategies and measures and facilitate the achievement of continuous road safety improvement. Studies have been conducted to evaluate the association between the setting of quantified road safety targets and road fatality reduction, in both the short and long run, by comparing road fatalities before and after the implementation of a quantified road safety target. However, not much work has been done to evaluate whether the quantified road safety targets are actually achieved. In this study, we used a binary logistic regression model to examine the factors - including vehicle ownership, fatality rate, and national income, in addition to level of ambition and duration of target - that contribute to a target's success. We analyzed 55 quantified road safety targets set by 29 countries from 1981 to 2009, and the results indicate that targets that are in progress and with lower level of ambitions had a higher likelihood of eventually being achieved. Moreover, possible interaction effects on the association between level of ambition and the likelihood of success are also revealed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Prevalence of positive gated myocardial SPECT in diabetic and non-diabetic women and impact of other factors; KIHD perspective

International Nuclear Information System (INIS)

Maseeh-uz-Zaman; Fatima, N.; Samad, A.; Rasheed, S.Z.; Ishaq, M.; Rehman, K.; Wali, A.

2009-01-01

The objective of the present study was to assess the prevalence of coronary artery disease (CAD) among diabetic (DM) and nondiabetic (NDM) women using Gated SPECT (GSPECT) and to study the impact of other. risk factors like hypertension (HTN), dyslipidemia, family history and menopause. This is a prospective cross-sectional study on a consecutive sample of 287 women referred to Nuclear Cardiology Department of Karachi Institute of Heart Diseases (KIHD) for GSPECT for evaluation of known or suspected CAD (from January 2009 till June 2009). Women with a history of DM diagnosed less than 5 years were excluded. Same day (reststress) GSPECT study was conducted and fixed or reversible perfusion defects were considered positive GSPECT for CAD. GSPECT was positive for CAD in 41/115 (36%, P 0.002) diabetic women and 37/172 (21 %, P 0.005) non-diabetic cohort. In diabetic cohort, GSPECT was positive in 5/9 (56%, P 0.013) women with diabetes only, 17/35 (48%, P 0.02) DM with HTN, 12/15 (80%, P value 0.02) DM with dyslipidemia and 11/43 (26%, P 0.001) DM with >2 risk factors. GSPECT was normal in all 3 diabetic women with positive family history for CAD. In nondiabetic cohort, GSPECT was positive in 9/32 (28%, P value 0.739) women with no risk factor, 5/58 (26%, P 0.866) HTN only, 2/5 (40%, P value 0.655) only dyslipidemic women, 1/12. (8%, P 0.004) with family history only and 4/23 (17%, P value 0.166) non-diabetic with >2 risk factors. Interestingly, 35/93 post-menopausal diabetic (38%, p value 0.017) had positive GSPECT while 33/123 non-diabetic postmenopausal women (27%, p 0.03) had positive perfusion scans. GSPECT was positive in 6/26 (23%, P 0.006) and 4/49 (8%, P 0.05) in diabetic and non-diabetic pre-menopausal women. The prevalence of CAD in our diabetic women is as high as internationally reported and diabetes is a strong risk factor for CAD. Dyslipidemia with diabetes is a major contributor to CAD than HTN and F/H. Diabetes erases the protective effect of estrogen

Prevalence of positive gated myocardial SPECT in diabetic and non-diabetic women and impact of other factors; KIHD perspective

Energy Technology Data Exchange (ETDEWEB)

Maseeh-uz-Zaman,; Fatima, N; Samad, A; Rasheed, S Z; Ishaq, M; Rehman, K; Wali, A [Karachi, Inst. of Heart Diseases, Karachi (Pakistan)

2009-07-15

The objective of the present study was to assess the prevalence of coronary artery disease (CAD) among diabetic (DM) and nondiabetic (NDM) women using Gated SPECT (GSPECT) and to study the impact of other. risk factors like hypertension (HTN), dyslipidemia, family history and menopause. This is a prospective cross-sectional study on a consecutive sample of 287 women referred to Nuclear Cardiology Department of Karachi Institute of Heart Diseases (KIHD) for GSPECT for evaluation of known or suspected CAD (from January 2009 till June 2009). Women with a history of DM diagnosed less than 5 years were excluded. Same day (reststress) GSPECT study was conducted and fixed or reversible perfusion defects were considered positive GSPECT for CAD. GSPECT was positive for CAD in 41/115 (36%, P 0.002) diabetic women and 37/172 (21 %, P 0.005) non-diabetic cohort. In diabetic cohort, GSPECT was positive in 5/9 (56%, P 0.013) women with diabetes only, 17/35 (48%, P 0.02) DM with HTN, 12/15 (80%, P value 0.02) DM with dyslipidemia and 11/43 (26%, P 0.001) DM with >2 risk factors. GSPECT was normal in all 3 diabetic women with positive family history for CAD. In nondiabetic cohort, GSPECT was positive in 9/32 (28%, P value 0.739) women with no risk factor, 5/58 (26%, P 0.866) HTN only, 2/5 (40%, P value 0.655) only dyslipidemic women, 1/12. (8%, P 0.004) with family history only and 4/23 (17%, P value 0.166) non-diabetic with >2 risk factors. Interestingly, 35/93 post-menopausal diabetic (38%, p value 0.017) had positive GSPECT while 33/123 non-diabetic postmenopausal women (27%, p 0.03) had positive perfusion scans. GSPECT was positive in 6/26 (23%, P 0.006) and 4/49 (8%, P 0.05) in diabetic and non-diabetic pre-menopausal women. The prevalence of CAD in our diabetic women is as high as internationally reported and diabetes is a strong risk factor for CAD. Dyslipidemia with diabetes is a major contributor to CAD than HTN and F/H. Diabetes erases the protective effect of estrogen

Alcohol abuse as the strongest risk factor for violent offending in patients with paranoid schizophrenia.

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Kudumija Slijepcevic, Marija; Jukic, Vlado; Novalic, Darko; Zarkovic-Palijan, Tija; Milosevic, Milan; Rosenzweig, Ivana

2014-04-01

To determine predictive risk factors for violent offending in patients with paranoid schizophrenia in Croatia. The cross-sectional study including male in-patients with paranoid schizophrenia with (N=104) and without (N=102) history of physical violence and violent offending was conducted simultaneously in several hospitals in Croatia during one-year period (2010-2011). Data on their sociodemographic characteristics, duration of untreated illness phase (DUP), alcohol abuse, suicidal behavior, personality features, and insight into illness were collected and compared between groups. Binary logistic regression model was used to determine the predictors of violent offending. Predictors of violent offending were older age, DUP before first contact with psychiatric services, and alcohol abuse. Regression model showed that the strongest positive predictive factor was harmful alcohol use, as determined by AUDIT test (odds ratio 37.01; 95% confidence interval 5.20-263.24). Psychopathy, emotional stability, and conscientiousness were significant positive predictive factors, while extroversion, pleasantness, and intellect were significant negative predictive factors for violent offending. This study found an association between alcohol abuse and the risk for violent offending in paranoid schizophrenia. We hope that this finding will help improve public and mental health prevention strategies in this vulnerable patient group.

Positive and Negative Factors of Economic Development in Economic History of South Korea

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Park Jong Min

2017-01-01

Full Text Available Purpose: the aim of the article is to analyze the Korean economic strategy from the beginning of its development until modern stage. Examination of how this strategy has changed depending on changes within domestic and international economic environment, assumptions, set goals, their effectiveness and significance of all the taken measures. It will demonstrate waypoints for the future economic development and will become a trigger towards recognition of the successful development of the Korean economy by other countries. Methods: the methodological bases of this article are the economic and statistical methods of analysis of the Korean economys, graphical methods displaying economic indicators. Results: economic history of South Korea over the past century shows the positive and negative factors of the development from an economically weak country into a developing country. The history of the Japanese occupation of Korea, lasting from 1910 to 1945, showed that for a country which has lost its national sovereignty, expropriated the state's economy has no effect after the restoration of independence, and that the economy cannot develop in conditions of chaos within the political, economic and social spheres. Even after the establishment of a military dictatorship, it is possible to note that despite limitations of citizens’ rights, the economy can still grow if the people want it. In addition to the development of internal political system, unstable factors in the process of promotion of social reforms and hastily adopted policy of "open doors" in order to enhance the international status are unreasonable political, economic and social changes. In turn, the inability to control currency exchange in Asian countries, which is a policy of economic development, has shown the existence of a risk of national bankruptcy. Moreover, the adoption of policies of excessive decrease of interest rates in order to revive the recession may be counterproductive

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)

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.

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.

Using occupancy modeling and logistic regression to assess the distribution of shrimp species in lowland streams, Costa Rica: Does regional groundwater create favorable habitat?

Science.gov (United States)

Snyder, Marcia; Freeman, Mary C.; Purucker, S. Thomas; Pringle, Catherine M.

2016-01-01

Freshwater shrimps are an important biotic component of tropical ecosystems. However, they can have a low probability of detection when abundances are low. We sampled 3 of the most common freshwater shrimp species, Macrobrachium olfersii, Macrobrachium carcinus, and Macrobrachium heterochirus, and used occupancy modeling and logistic regression models to improve our limited knowledge of distribution of these cryptic species by investigating both local- and landscape-scale effects at La Selva Biological Station in Costa Rica. Local-scale factors included substrate type and stream size, and landscape-scale factors included presence or absence of regional groundwater inputs. Capture rates for 2 of the sampled species (M. olfersii and M. carcinus) were sufficient to compare the fit of occupancy models. Occupancy models did not converge for M. heterochirus, but M. heterochirus had high enough occupancy rates that logistic regression could be used to model the relationship between occupancy rates and predictors. The best-supported models for M. olfersii and M. carcinus included conductivity, discharge, and substrate parameters. Stream size was positively correlated with occupancy rates of all 3 species. High stream conductivity, which reflects the quantity of regional groundwater input into the stream, was positively correlated with M. olfersii occupancy rates. Boulder substrates increased occupancy rate of M. carcinus and decreased the detection probability of M. olfersii. Our models suggest that shrimp distribution is driven by factors that function at local (substrate and discharge) and landscape (conductivity) scales.

[Determination of priority unfavorable environmental factors].

Science.gov (United States)

Zaikova, Z A; Burdukovskaya, A V; Belykh, A I

In the Irkutsk region there are recorded high indices of rates of morbidity, disability, mortality rate of the working-age population and low levels of life expectancy of the population, that is confirmed by ranking position levels among the all subjects of the Russian Federation. According to all mentioned indices of health the region is inside the top ten unfavorable regions of Russia. In relation to the problem in the state of health of the adult population the estimation of the causal relationships between environmental factors and certain health indices is actual. The list of studiedfactors included health indices that characterize the harmful working conditions of the working population and basic socioeconomic indices in the region. Estimation of causal-relationship relationships was performed with the use of methods of multivariate analysis - correlation and multiple linear regression. In the selection offactors for the construction of mathematical models of multiple regression there were used methods of the analysis of variables variability, pair correlation coefficients matrix and sequential switching covariates to eliminate the problems of multicollinearity, pre-standardization of indices for the elevation of the numerical stability of regression analysis algorithm. As a result of the execution of the analysis there were constructed statistical models for the dependence in the system variables “environment - public health”, which allowed to identify the most informative regression models for the adult population health according to indices of primary disability of the population, the mortality rate and life expectancy of the working age population. According to results of the analysis there were identified priority factors affecting on the health of the adult population of the Irkutsk region. To these factors there are referred the proportion of workplaces failing to meet sanitary standards for vibration and 8 socio-economic indices of living

Kepler AutoRegressive Planet Search

Science.gov (United States)

Caceres, Gabriel Antonio; Feigelson, Eric

2016-01-01

The Kepler AutoRegressive Planet Search (KARPS) project uses statistical methodology associated with autoregressive (AR) processes to model Kepler lightcurves in order to improve exoplanet transit detection in systems with high stellar variability. We also introduce a planet-search algorithm to detect transits in time-series residuals after application of the AR models. One of the main obstacles in detecting faint planetary transits is the intrinsic stellar variability of the host star. The variability displayed by many stars may have autoregressive properties, wherein later flux values are correlated with previous ones in some manner. Our analysis procedure consisting of three steps: pre-processing of the data to remove discontinuities, gaps and outliers; AR-type model selection and fitting; and transit signal search of the residuals using a new Transit Comb Filter (TCF) that replaces traditional box-finding algorithms. The analysis procedures of the project are applied to a portion of the publicly available Kepler light curve data for the full 4-year mission duration. Tests of the methods have been made on a subset of Kepler Objects of Interest (KOI) systems, classified both as planetary `candidates' and `false positives' by the Kepler Team, as well as a random sample of unclassified systems. We find that the ARMA-type modeling successfully reduces the stellar variability, by a factor of 10 or more in active stars and by smaller factors in more quiescent stars. A typical quiescent Kepler star has an interquartile range (IQR) of ~10 e-/sec, which may improve slightly after modeling, while those with IQR ranging from 20 to 50 e-/sec, have improvements from 20% up to 70%. High activity stars (IQR exceeding 100) markedly improve. A periodogram based on the TCF is constructed to concentrate the signal of these periodic spikes. When a periodic transit is found, the model is displayed on a standard period-folded averaged light curve. Our findings to date on real

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)

Tracking time-varying parameters with local regression

DEFF Research Database (Denmark)

Joensen, Alfred Karsten; Nielsen, Henrik Aalborg; Nielsen, Torben Skov

2000-01-01

This paper shows that the recursive least-squares (RLS) algorithm with forgetting factor is a special case of a varying-coe\\$cient model, and a model which can easily be estimated via simple local regression. This observation allows us to formulate a new method which retains the RLS algorithm, bu......, but extends the algorithm by including polynomial approximations. Simulation results are provided, which indicates that this new method is superior to the classical RLS method, if the parameter variations are smooth....

Influence of depressive symptoms on distress related to positive psychotic-like experiences in women.

Science.gov (United States)

Brañas, Antía; Barrigón, María Luisa; Lahera, Guillermo; Canal-Rivero, Manuel; Ruiz-Veguilla, Miguel

2017-12-01

The Community Assessment of Psychic Experiences (CAPE) is an effective instrument for detection of the presence of psychotic symptoms and associated distress in the general population. However, little research has studied distress associated with positive psychotic-like experiences (PLEs). Our aim is to study PLE-related distress using the CAPE. In this study we analysed factors associated with differences in PLE-related distress in a sample of 200 non-clinical participants recruited by snowball sampling. Presence of PLEs and related psychological distress was measured using the CAPE questionnaire. The influence of age, gender, educational level and drug use was studied. In univariate analysis we found that gender and CAPE positive, depressive and negative scores, were associated with CAPE positive distress. Using multiple linear regression, we found that only the effect of gender, and the interaction between frequency of depression and gender, remained statistically significant. In our sample interaction between gender and depressive symptoms is a determining factor in distress associated with positive PLEs. The results of this study may be useful for the implementation of prevention programs. Copyright © 2017 Elsevier B.V. All rights reserved.

Combining Alphas via Bounded Regression

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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.

A POSITIVE APPROACH TO COUNTER PROFESSIONAL BURNOUT

Directory of Open Access Journals (Sweden)

Natalia Evgenievna Vodopiyanova

2014-08-01

Full Text Available The aim of this research was to identify the positive determinants of preventing professional burnout. Based on the literature review and analysis of previous studies was found that positive working conditions can be considered as factors of burnout. It is revealed that such indicators of work engagement as vigor and enthusiasm interfere with burnout, and the preoccupation activity, on the contrary, promotes its emergence. Also with the help of regression analysis the contribution of indicators of enthusiasm by work in each subscale of professional burnout that will allow to analyse mechanisms of its prevention in more detail is revealed. The results of this research can be applied to a psychological assistance to representatives of an actor's profession, and also to counteraction to burnout in other professional groups. In particular, development of subjectivity of experts could be a basis for programs of burnout prevention: development of cognitive and existential activity of the subject of a vital and professional way, expansion of sensibleness of personal resources and skills of a constructive coping with professional and existential stresses.

Dirichlet Component Regression and its Applications to Psychiatric Data

OpenAIRE

Gueorguieva, Ralitza; Rosenheck, Robert; Zelterman, Daniel

2008-01-01

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 com...

Technological progress and regress in pre-industrial times

DEFF Research Database (Denmark)

Aiyar, Shekhar; Dalgaard, Carl-Johan Lars; Moav, Omer

2008-01-01

This paper offers micro-foundations for the dynamic relationship between technology and population in the pre-industrial world, accounting for both technological progress and the hitherto neglected but common phenomenon of technological regress. A positive feedback between population and the adop....... Inventions don't just get adopted once and forever; they have to be constantly practised and transmitted, or useful techniques may be forgotten. Jared Diamond, Ten Thousand Years of Solitude, 1993...

Interaction between body mass index and hormone-receptor status as a prognostic factor in lymph-node-positive breast cancer.

Directory of Open Access Journals (Sweden)

Il Yong Chung

Full Text Available The aim of this study was to determine the relationship between the body mass index (BMI at a breast cancer diagnosis and various factors including the hormone-receptor, menopause, and lymph-node status, and identify if there is a specific patient subgroup for which the BMI has an effect on the breast cancer prognosis. We retrospectively analyzed the data of 8,742 patients with non-metastatic invasive breast cancer from the research database of Asan Medical Center. The overall survival (OS and breast-cancer-specific survival (BCSS outcomes were compared among BMI groups using the Kaplan-Meier method and Cox proportional-hazards regression models with an interaction term. There was a significant interaction between BMI and hormone-receptor status for the OS (P = 0.029, and BCSS (P = 0.013 in lymph-node-positive breast cancers. Obesity in hormone-receptor-positive breast cancer showed a poorer OS (adjusted hazard ratio [HR] = 1.51, 95% confidence interval [CI] = 0.92 to 2.48 and significantly poorer BCSS (HR = 1.80, 95% CI = 1.08 to 2.99. In contrast, a high BMI in hormone-receptor-negative breast cancer revealed a better OS (HR = 0.44, 95% CI = 0.16 to 1.19 and BCSS (HR = 0.53, 95% CI = 0.19 to 1.44. Being underweight (BMI < 18.50 kg/m2 with hormone-receptor-negative breast cancer was associated with a significantly worse OS (HR = 1.98, 95% CI = 1.00-3.95 and BCSS (HR = 2.24, 95% CI = 1.12-4.47. There was no significant interaction found between the BMI and hormone-receptor status in the lymph-node-negative setting, and BMI did not interact with the menopause status in any subgroup. In conclusion, BMI interacts with the hormone-receptor status in a lymph-node-positive setting, thereby playing a role in the prognosis of breast cancer.

Organizational Factors and Intrapreneurial Competences

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Suzete Antonieta Lizote

2013-12-01

Full Text Available This study analyzes the relationship between organizational factors and entrepreneurial competencies of coordinators of undergraduate courses in two community universities in Santa Catarina, Brazil. The organizational factors studied were: management support, freedom at work, rewards, and time available and organizational limitations. Eight entrepreneurial competencies were considered; five included in an achievement set, and three in a planning set. The method was quantitative and descriptive, adopting a structured questionnaire as the data collection tool. Factor analysis, canonical analysis, and multiple regression analysis were performed. The results revealed a positive relationship between the constructs. The most relevant competencies were organizational limitations or uncertainty about tasks, and freedom at work, which indicates the importance having clarity about rules and decisions that should exist both at the level of performance expected of the coordinator, and the freedom that they must feel in their work.

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....

Factors of Consumer Behavior That Affect Purchasing Decisions on Blackberry Smartphone

Directory of Open Access Journals (Sweden)

Muhammad Tony Nawawi

2016-03-01

analysis used the method of multiple regression analysis and hypothesis testing and also testing conducted validity and reliability by using the help of SPSS (Statistical Program for the Science Society. The analysis shows that there is significant positive effect between the factors of cultural, social, personal, and psychological effect on purchasing decisions, with significance 0,000 < 0,05, and Adjusted R Square is worth 0,216, it means that 21,6% of purchase decisions are influenced by these factors.

Prediction of tissue-specific cis-regulatory modules using Bayesian networks and regression trees

Directory of Open Access Journals (Sweden)

Chen Xiaoyu

2007-12-01

Full Text Available Abstract Background In vertebrates, a large part of gene transcriptional regulation is operated by cis-regulatory modules. These modules are believed to be regulating much of the tissue-specificity of gene expression. Results We develop a Bayesian network approach for identifying cis-regulatory modules likely to regulate tissue-specific expression. The network integrates predicted transcription factor binding site information, transcription factor expression data, and target gene expression data. At its core is a regression tree modeling the effect of combinations of transcription factors bound to a module. A new unsupervised EM-like algorithm is developed to learn the parameters of the network, including the regression tree structure. Conclusion Our approach is shown to accurately identify known human liver and erythroid-specific modules. When applied to the prediction of tissue-specific modules in 10 different tissues, the network predicts a number of important transcription factor combinations whose concerted binding is associated to specific expression.

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...

Meta-regression analysis of commensal and pathogenic Escherichia coli survival in soil and water.

Science.gov (United States)

Franz, Eelco; Schijven, Jack; de Roda Husman, Ana Maria; Blaak, Hetty

2014-06-17

The extent to which pathogenic and commensal E. coli (respectively PEC and CEC) can survive, and which factors predominantly determine the rate of decline, are crucial issues from a public health point of view. The goal of this study was to provide a quantitative summary of the variability in E. coli survival in soil and water over a broad range of individual studies and to identify the most important sources of variability. To that end, a meta-regression analysis on available literature data was conducted. The considerable variation in reported decline rates indicated that the persistence of E. coli is not easily predictable. The meta-analysis demonstrated that for soil and water, the type of experiment (laboratory or field), the matrix subtype (type of water and soil), and temperature were the main factors included in the regression analysis. A higher average decline rate in soil of PEC compared with CEC was observed. The regression models explained at best 57% of the variation in decline rate in soil and 41% of the variation in decline rate in water. This indicates that additional factors, not included in the current meta-regression analysis, are of importance but rarely reported. More complete reporting of experimental conditions may allow future inference on the global effects of these variables on the decline rate of E. coli.

Does the Magnitude of the Link between Unemployment and Crime Depend on the Crime Level? A Quantile Regression Approach

Directory of Open Access Journals (Sweden)

Horst Entorf

2015-07-01

Full Text Available Two alternative hypotheses – referred to as opportunity- and stigma-based behavior – suggest that the magnitude of the link between unemployment and crime also depends on preexisting local crime levels. In order to analyze conjectured nonlinearities between both variables, we use quantile regressions applied to German district panel data. While both conventional OLS and quantile regressions confirm the positive link between unemployment and crime for property crimes, results for assault differ with respect to the method of estimation. Whereas conventional mean regressions do not show any significant effect (which would confirm the usual result found for violent crimes in the literature, quantile regression reveals that size and importance of the relationship are conditional on the crime rate. The partial effect is significantly positive for moderately low and median quantiles of local assault rates.

Differential Effects for Sexual Risk Behavior: An Application of Finite Mixture Regression

OpenAIRE

Lanza, Stephanie T.; Kugler, Kari C.; Mathur, Charu

2011-01-01

Understanding the multiple factors that place individuals at risk for sexual risk behavior is critical for developing effective intervention programs. Regression-based methods are commonly used to estimate the average effects of risk factors, however such results can be difficult to translate to prevention implications at the individual level. Although differential effects can be examined to some extent by including interaction terms, as risk factors and moderators are added to the model inte...

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...

Antecedents of positive self-disclosure online: an empirical study of US college students’ Facebook usage

Directory of Open Access Journals (Sweden)

Chen H