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Sample records for regression analyses female

  1. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

    Science.gov (United States)

    Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg

    2009-11-01

    G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

  2. Applications of MIDAS regression in analysing trends in water quality

    Science.gov (United States)

    Penev, Spiridon; Leonte, Daniela; Lazarov, Zdravetz; Mann, Rob A.

    2014-04-01

    We discuss novel statistical methods in analysing trends in water quality. Such analysis uses complex data sets of different classes of variables, including water quality, hydrological and meteorological. We analyse the effect of rainfall and flow on trends in water quality utilising a flexible model called Mixed Data Sampling (MIDAS). This model arises because of the mixed frequency in the data collection. Typically, water quality variables are sampled fortnightly, whereas the rain data is sampled daily. The advantage of using MIDAS regression is in the flexible and parsimonious modelling of the influence of the rain and flow on trends in water quality variables. We discuss the model and its implementation on a data set from the Shoalhaven Supply System and Catchments in the state of New South Wales, Australia. Information criteria indicate that MIDAS modelling improves upon simplistic approaches that do not utilise the mixed data sampling nature of the data.

  3. Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies.

    Science.gov (United States)

    Vatcheva, Kristina P; Lee, MinJae; McCormick, Joseph B; Rahbar, Mohammad H

    2016-04-01

    The adverse impact of ignoring multicollinearity on findings and data interpretation in regression analysis is very well documented in the statistical literature. The failure to identify and report multicollinearity could result in misleading interpretations of the results. A review of epidemiological literature in PubMed from January 2004 to December 2013, illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epidemiologic studies. We used simulated datasets and real life data from the Cameron County Hispanic Cohort to demonstrate the adverse effects of multicollinearity in the regression analysis and encourage researchers to consider the diagnostic for multicollinearity as one of the steps in regression analysis.

  4. 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

  5. Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies

    OpenAIRE

    Vatcheva, Kristina P.; Lee, MinJae; McCormick, Joseph B.; Rahbar, Mohammad H.

    2016-01-01

    The adverse impact of ignoring multicollinearity on findings and data interpretation in regression analysis is very well documented in the statistical literature. The failure to identify and report multicollinearity could result in misleading interpretations of the results. A review of epidemiological literature in PubMed from January 2004 to December 2013, illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epide...

  6. Analysing inequalities in Germany a structured additive distributional regression approach

    CERN Document Server

    Silbersdorff, Alexander

    2017-01-01

    This book seeks new perspectives on the growing inequalities that our societies face, putting forward Structured Additive Distributional Regression as a means of statistical analysis that circumvents the common problem of analytical reduction to simple point estimators. This new approach allows the observed discrepancy between the individuals’ realities and the abstract representation of those realities to be explicitly taken into consideration using the arithmetic mean alone. In turn, the method is applied to the question of economic inequality in Germany.

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

    Science.gov (United States)

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

    2013-01-01

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

  8. How to deal with continuous and dichotomic outcomes in epidemiological research: linear and logistic regression analyses

    NARCIS (Netherlands)

    Tripepi, Giovanni; Jager, Kitty J.; Stel, Vianda S.; Dekker, Friedo W.; Zoccali, Carmine

    2011-01-01

    Because of some limitations of stratification methods, epidemiologists frequently use multiple linear and logistic regression analyses to address specific epidemiological questions. If the dependent variable is a continuous one (for example, systolic pressure and serum creatinine), the researcher

  9. USE OF THE SIMPLE LINEAR REGRESSION MODEL IN MACRO-ECONOMICAL ANALYSES

    Directory of Open Access Journals (Sweden)

    Constantin ANGHELACHE

    2011-10-01

    Full Text Available The article presents the fundamental aspects of the linear regression, as a toolbox which can be used in macroeconomic analyses. The article describes the estimation of the parameters, the statistical tests used, the homoscesasticity and heteroskedasticity. The use of econometrics instrument in macroeconomics is an important factor that guarantees the quality of the models, analyses, results and possible interpretation that can be drawn at this level.

  10. Genetic analyses of partial egg production in Japanese quail using multi-trait random regression models.

    Science.gov (United States)

    Karami, K; Zerehdaran, S; Barzanooni, B; Lotfi, E

    2017-12-01

    1. The aim of the present study was to estimate genetic parameters for average egg weight (EW) and egg number (EN) at different ages in Japanese quail using multi-trait random regression (MTRR) models. 2. A total of 8534 records from 900 quail, hatched between 2014 and 2015, were used in the study. Average weekly egg weights and egg numbers were measured from second until sixth week of egg production. 3. Nine random regression models were compared to identify the best order of the Legendre polynomials (LP). The most optimal model was identified by the Bayesian Information Criterion. A model with second order of LP for fixed effects, second order of LP for additive genetic effects and third order of LP for permanent environmental effects (MTRR23) was found to be the best. 4. According to the MTRR23 model, direct heritability for EW increased from 0.26 in the second week to 0.53 in the sixth week of egg production, whereas the ratio of permanent environment to phenotypic variance decreased from 0.48 to 0.1. Direct heritability for EN was low, whereas the ratio of permanent environment to phenotypic variance decreased from 0.57 to 0.15 during the production period. 5. For each trait, estimated genetic correlations among weeks of egg production were high (from 0.85 to 0.98). Genetic correlations between EW and EN were low and negative for the first two weeks, but they were low and positive for the rest of the egg production period. 6. In conclusion, random regression models can be used effectively for analysing egg production traits in Japanese quail. Response to selection for increased egg weight would be higher at older ages because of its higher heritability and such a breeding program would have no negative genetic impact on egg production.

  11. Reducing Inter-Laboratory Differences between Semen Analyses Using Z Score and Regression Transformations

    Directory of Open Access Journals (Sweden)

    Esther Leushuis

    2016-12-01

    Full Text Available Background: Standardization of the semen analysis may improve reproducibility. We assessed variability between laboratories in semen analyses and evaluated whether a transformation using Z scores and regression statistics was able to reduce this variability. Materials and Methods: We performed a retrospective cohort study. We calculated between-laboratory coefficients of variation (CVB for sperm concentration and for morphology. Subsequently, we standardized the semen analysis results by calculating laboratory specific Z scores, and by using regression. We used analysis of variance for four semen parameters to assess systematic differences between laboratories before and after the transformations, both in the circulation samples and in the samples obtained in the prospective cohort study in the Netherlands between January 2002 and February 2004. Results: The mean CVB was 7% for sperm concentration (range 3 to 13% and 32% for sperm morphology (range 18 to 51%. The differences between the laboratories were statistically significant for all semen parameters (all P<0.001. Standardization using Z scores did not reduce the differences in semen analysis results between the laboratories (all P<0.001. Conclusion: There exists large between-laboratory variability for sperm morphology and small, but statistically significant, between-laboratory variation for sperm concentration. Standardization using Z scores does not eliminate between-laboratory variability.

  12. Logistic regression and multiple classification analyses to explore risk factors of under-5 mortality in bangladesh

    International Nuclear Information System (INIS)

    Bhowmik, K.R.; Islam, S.

    2016-01-01

    Logistic regression (LR) analysis is the most common statistical methodology to find out the determinants of childhood mortality. However, the significant predictors cannot be ranked according to their influence on the response variable. Multiple classification (MC) analysis can be applied to identify the significant predictors with a priority index which helps to rank the predictors. The main objective of the study is to find the socio-demographic determinants of childhood mortality at neonatal, post-neonatal, and post-infant period by fitting LR model as well as to rank those through MC analysis. The study is conducted using the data of Bangladesh Demographic and Health Survey 2007 where birth and death information of children were collected from their mothers. Three dichotomous response variables are constructed from children age at death to fit the LR and MC models. Socio-economic and demographic variables significantly associated with the response variables separately are considered in LR and MC analyses. Both the LR and MC models identified the same significant predictors for specific childhood mortality. For both the neonatal and child mortality, biological factors of children, regional settings, and parents socio-economic status are found as 1st, 2nd, and 3rd significant groups of predictors respectively. Mother education and household environment are detected as major significant predictors of post-neonatal mortality. This study shows that MC analysis with or without LR analysis can be applied to detect determinants with rank which help the policy makers taking initiatives on a priority basis. (author)

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

    NARCIS (Netherlands)

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

    2015-01-01

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

  14. Longitudinal changes in telomere length and associated genetic parameters in dairy cattle analysed using random regression models.

    Directory of Open Access Journals (Sweden)

    Luise A Seeker

    Full Text Available Telomeres cap the ends of linear chromosomes and shorten with age in many organisms. In humans short telomeres have been linked to morbidity and mortality. With the accumulation of longitudinal datasets the focus shifts from investigating telomere length (TL to exploring TL change within individuals over time. Some studies indicate that the speed of telomere attrition is predictive of future disease. The objectives of the present study were to 1 characterize the change in bovine relative leukocyte TL (RLTL across the lifetime in Holstein Friesian dairy cattle, 2 estimate genetic parameters of RLTL over time and 3 investigate the association of differences in individual RLTL profiles with productive lifespan. RLTL measurements were analysed using Legendre polynomials in a random regression model to describe TL profiles and genetic variance over age. The analyses were based on 1,328 repeated RLTL measurements of 308 female Holstein Friesian dairy cattle. A quadratic Legendre polynomial was fitted to the fixed effect of age in months and to the random effect of the animal identity. Changes in RLTL, heritability and within-trait genetic correlation along the age trajectory were calculated and illustrated. At a population level, the relationship between RLTL and age was described by a positive quadratic function. Individuals varied significantly regarding the direction and amount of RLTL change over life. The heritability of RLTL ranged from 0.36 to 0.47 (SE = 0.05-0.08 and remained statistically unchanged over time. The genetic correlation of RLTL at birth with measurements later in life decreased with the time interval between samplings from near unity to 0.69, indicating that TL later in life might be regulated by different genes than TL early in life. Even though animals differed in their RLTL profiles significantly, those differences were not correlated with productive lifespan (p = 0.954.

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

    Science.gov (United States)

    Austin, Peter C; Steyerberg, Ewout W

    2015-06-01

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

  16. [Is there either agenesis or regression of the Mullerian duct in female bird embryos under the influence of male hormone?].

    Science.gov (United States)

    Lutz-Ostertag, Y; Lutz, H

    1976-01-01

    The natural occurence of "Free-Martinism" in Birds and the chorio-allantoïc grafting experiments of testis fragments on female chick host-embryos allow to the authors to define the manner provoking the entire or partial disappearance of the müllerian ducts and to state exactly if the phenomenon is a agenesis or a regression.

  17. Correcting for multivariate measurement error by regression calibration in meta-analyses of epidemiological studies.

    NARCIS (Netherlands)

    Kromhout, D.

    2009-01-01

    Within-person variability in measured values of multiple risk factors can bias their associations with disease. The multivariate regression calibration (RC) approach can correct for such measurement error and has been applied to studies in which true values or independent repeat measurements of the

  18. Testing Mediation Using Multiple Regression and Structural Equation Modeling Analyses in Secondary Data

    Science.gov (United States)

    Li, Spencer D.

    2011-01-01

    Mediation analysis in child and adolescent development research is possible using large secondary data sets. This article provides an overview of two statistical methods commonly used to test mediated effects in secondary analysis: multiple regression and structural equation modeling (SEM). Two empirical studies are presented to illustrate the…

  19. Regression Analyses on the Butterfly Ballot Effect: A Statistical Perspective of the US 2000 Election

    Science.gov (United States)

    Wu, Dane W.

    2002-01-01

    The year 2000 US presidential election between Al Gore and George Bush has been the most intriguing and controversial one in American history. The state of Florida was the trigger for the controversy, mainly, due to the use of the misleading "butterfly ballot". Using prediction (or confidence) intervals for least squares regression lines…

  20. Alpins and thibos vectorial astigmatism analyses: proposal of a linear regression model between methods

    Directory of Open Access Journals (Sweden)

    Giuliano de Oliveira Freitas

    2013-10-01

    Full Text Available PURPOSE: To determine linear regression models between Alpins descriptive indices and Thibos astigmatic power vectors (APV, assessing the validity and strength of such correlations. METHODS: This case series prospectively assessed 62 eyes of 31 consecutive cataract patients with preoperative corneal astigmatism between 0.75 and 2.50 diopters in both eyes. Patients were randomly assorted among two phacoemulsification groups: one assigned to receive AcrySof®Toric intraocular lens (IOL in both eyes and another assigned to have AcrySof Natural IOL associated with limbal relaxing incisions, also in both eyes. All patients were reevaluated postoperatively at 6 months, when refractive astigmatism analysis was performed using both Alpins and Thibos methods. The ratio between Thibos postoperative APV and preoperative APV (APVratio and its linear regression to Alpins percentage of success of astigmatic surgery, percentage of astigmatism corrected and percentage of astigmatism reduction at the intended axis were assessed. RESULTS: Significant negative correlation between the ratio of post- and preoperative Thibos APVratio and Alpins percentage of success (%Success was found (Spearman's ρ=-0.93; linear regression is given by the following equation: %Success = (-APVratio + 1.00x100. CONCLUSION: The linear regression we found between APVratio and %Success permits a validated mathematical inference concerning the overall success of astigmatic surgery.

  1. Check-all-that-apply data analysed by Partial Least Squares regression

    DEFF Research Database (Denmark)

    Rinnan, Åsmund; Giacalone, Davide; Frøst, Michael Bom

    2015-01-01

    are analysed by multivariate techniques. CATA data can be analysed both by setting the CATA as the X and the Y. The former is the PLS-Discriminant Analysis (PLS-DA) version, while the latter is the ANOVA-PLS (A-PLS) version. We investigated the difference between these two approaches, concluding...

  2. Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression

    DEFF Research Database (Denmark)

    Scott, Neil W; Fayers, Peter M; Aaronson, Neil K

    2010-01-01

    Differential item functioning (DIF) methods can be used to determine whether different subgroups respond differently to particular items within a health-related quality of life (HRQoL) subscale, after allowing for overall subgroup differences in that scale. This article reviews issues that arise ...... when testing for DIF in HRQoL instruments. We focus on logistic regression methods, which are often used because of their efficiency, simplicity and ease of application....

  3. Analyses of Developmental Rate Isomorphy in Ectotherms: Introducing the Dirichlet Regression.

    Directory of Open Access Journals (Sweden)

    David S Boukal

    Full Text Available Temperature drives development in insects and other ectotherms because their metabolic rate and growth depends directly on thermal conditions. However, relative durations of successive ontogenetic stages often remain nearly constant across a substantial range of temperatures. This pattern, termed 'developmental rate isomorphy' (DRI in insects, appears to be widespread and reported departures from DRI are generally very small. We show that these conclusions may be due to the caveats hidden in the statistical methods currently used to study DRI. Because the DRI concept is inherently based on proportional data, we propose that Dirichlet regression applied to individual-level data is an appropriate statistical method to critically assess DRI. As a case study we analyze data on five aquatic and four terrestrial insect species. We find that results obtained by Dirichlet regression are consistent with DRI violation in at least eight of the studied species, although standard analysis detects significant departure from DRI in only four of them. Moreover, the departures from DRI detected by Dirichlet regression are consistently much larger than previously reported. The proposed framework can also be used to infer whether observed departures from DRI reflect life history adaptations to size- or stage-dependent effects of varying temperature. Our results indicate that the concept of DRI in insects and other ectotherms should be critically re-evaluated and put in a wider context, including the concept of 'equiproportional development' developed for copepods.

  4. Correlation and regression analyses of genetic effects for different types of cells in mammals under radiation and chemical treatment

    International Nuclear Information System (INIS)

    Slutskaya, N.G.; Mosseh, I.B.

    2006-01-01

    Data about genetic mutations under radiation and chemical treatment for different types of cells have been analyzed with correlation and regression analyses. Linear correlation between different genetic effects in sex cells and somatic cells have found. The results may be extrapolated on sex cells of human and mammals. (authors)

  5. Correcting for multivariate measurement error by regression calibration in meta-analyses of epidemiological studies

    DEFF Research Database (Denmark)

    Tybjærg-Hansen, Anne

    2009-01-01

    Within-person variability in measured values of multiple risk factors can bias their associations with disease. The multivariate regression calibration (RC) approach can correct for such measurement error and has been applied to studies in which true values or independent repeat measurements...... of the risk factors are observed on a subsample. We extend the multivariate RC techniques to a meta-analysis framework where multiple studies provide independent repeat measurements and information on disease outcome. We consider the cases where some or all studies have repeat measurements, and compare study......-specific, averaged and empirical Bayes estimates of RC parameters. Additionally, we allow for binary covariates (e.g. smoking status) and for uncertainty and time trends in the measurement error corrections. Our methods are illustrated using a subset of individual participant data from prospective long-term studies...

  6. Correlation, Regression and Path Analyses of Seed Yield Components in Crambe abyssinica, a Promising Industrial Oil Crop

    OpenAIRE

    Huang, Banglian; Yang, Yiming; Luo, Tingting; Wu, S.; Du, Xuezhu; Cai, Detian; Loo, van, E.N.; Huang Bangquan

    2013-01-01

    In the present study correlation, regression and path analyses were carried out to decide correlations among the agro- nomic traits and their contributions to seed yield per plant in Crambe abyssinica. Partial correlation analysis indicated that plant height (X1) was significantly correlated with branching height and the number of first branches (P <0.01); Branching height (X2) was significantly correlated with pod number of primary inflorescence (P <0.01) and number of secondary branch...

  7. Analyses of non-fatal accidents in an opencast mine by logistic regression model - a case study.

    Science.gov (United States)

    Onder, Seyhan; Mutlu, Mert

    2017-09-01

    Accidents cause major damage for both workers and enterprises in the mining industry. To reduce the number of occupational accidents, these incidents should be properly registered and carefully analysed. This study efficiently examines the Aegean Lignite Enterprise (ELI) of Turkish Coal Enterprises (TKI) in Soma between 2006 and 2011, and opencast coal mine occupational accident records were used for statistical analyses. A total of 231 occupational accidents were analysed for this study. The accident records were categorized into seven groups: area, reason, occupation, part of body, age, shift hour and lost days. The SPSS package program was used in this study for logistic regression analyses, which predicted the probability of accidents resulting in greater or less than 3 lost workdays for non-fatal injuries. Social facilities-area of surface installations, workshops and opencast mining areas are the areas with the highest probability for accidents with greater than 3 lost workdays for non-fatal injuries, while the reasons with the highest probability for these types of accidents are transporting and manual handling. Additionally, the model was tested for such reported accidents that occurred in 2012 for the ELI in Soma and estimated the probability of exposure to accidents with lost workdays correctly by 70%.

  8. Improved Dietary Guidelines for Vitamin D: Application of Individual Participant Data (IPD-Level Meta-Regression Analyses

    Directory of Open Access Journals (Sweden)

    Kevin D. Cashman

    2017-05-01

    Full Text Available Dietary Reference Values (DRVs for vitamin D have a key role in the prevention of vitamin D deficiency. However, despite adopting similar risk assessment protocols, estimates from authoritative agencies over the last 6 years have been diverse. This may have arisen from diverse approaches to data analysis. Modelling strategies for pooling of individual subject data from cognate vitamin D randomized controlled trials (RCTs are likely to provide the most appropriate DRV estimates. Thus, the objective of the present work was to undertake the first-ever individual participant data (IPD-level meta-regression, which is increasingly recognized as best practice, from seven winter-based RCTs (with 882 participants ranging in age from 4 to 90 years of the vitamin D intake–serum 25-hydroxyvitamin D (25(OHD dose-response. Our IPD-derived estimates of vitamin D intakes required to maintain 97.5% of 25(OHD concentrations >25, 30, and 50 nmol/L across the population are 10, 13, and 26 µg/day, respectively. In contrast, standard meta-regression analyses with aggregate data (as used by several agencies in recent years from the same RCTs estimated that a vitamin D intake requirement of 14 µg/day would maintain 97.5% of 25(OHD >50 nmol/L. These first IPD-derived estimates offer improved dietary recommendations for vitamin D because the underpinning modeling captures the between-person variability in response of serum 25(OHD to vitamin D intake.

  9. Improved Dietary Guidelines for Vitamin D: Application of Individual Participant Data (IPD)-Level Meta-Regression Analyses

    Science.gov (United States)

    Cashman, Kevin D.; Ritz, Christian; Kiely, Mairead

    2017-01-01

    Dietary Reference Values (DRVs) for vitamin D have a key role in the prevention of vitamin D deficiency. However, despite adopting similar risk assessment protocols, estimates from authoritative agencies over the last 6 years have been diverse. This may have arisen from diverse approaches to data analysis. Modelling strategies for pooling of individual subject data from cognate vitamin D randomized controlled trials (RCTs) are likely to provide the most appropriate DRV estimates. Thus, the objective of the present work was to undertake the first-ever individual participant data (IPD)-level meta-regression, which is increasingly recognized as best practice, from seven winter-based RCTs (with 882 participants ranging in age from 4 to 90 years) of the vitamin D intake–serum 25-hydroxyvitamin D (25(OH)D) dose-response. Our IPD-derived estimates of vitamin D intakes required to maintain 97.5% of 25(OH)D concentrations >25, 30, and 50 nmol/L across the population are 10, 13, and 26 µg/day, respectively. In contrast, standard meta-regression analyses with aggregate data (as used by several agencies in recent years) from the same RCTs estimated that a vitamin D intake requirement of 14 µg/day would maintain 97.5% of 25(OH)D >50 nmol/L. These first IPD-derived estimates offer improved dietary recommendations for vitamin D because the underpinning modeling captures the between-person variability in response of serum 25(OH)D to vitamin D intake. PMID:28481259

  10. Bisphenol-A exposures and behavioural aberrations: median and linear spline and meta-regression analyses of 12 toxicity studies in rodents.

    Science.gov (United States)

    Peluso, Marco E M; Munnia, Armelle; Ceppi, Marcello

    2014-11-05

    Exposures to bisphenol-A, a weak estrogenic chemical, largely used for the production of plastic containers, can affect the rodent behaviour. Thus, we examined the relationships between bisphenol-A and the anxiety-like behaviour, spatial skills, and aggressiveness, in 12 toxicity studies of rodent offspring from females orally exposed to bisphenol-A, while pregnant and/or lactating, by median and linear splines analyses. Subsequently, the meta-regression analysis was applied to quantify the behavioural changes. U-shaped, inverted U-shaped and J-shaped dose-response curves were found to describe the relationships between bisphenol-A with the behavioural outcomes. The occurrence of anxiogenic-like effects and spatial skill changes displayed U-shaped and inverted U-shaped curves, respectively, providing examples of effects that are observed at low-doses. Conversely, a J-dose-response relationship was observed for aggressiveness. When the proportion of rodents expressing certain traits or the time that they employed to manifest an attitude was analysed, the meta-regression indicated that a borderline significant increment of anxiogenic-like effects was present at low-doses regardless of sexes (β)=-0.8%, 95% C.I. -1.7/0.1, P=0.076, at ≤120 μg bisphenol-A. Whereas, only bisphenol-A-males exhibited a significant inhibition of spatial skills (β)=0.7%, 95% C.I. 0.2/1.2, P=0.004, at ≤100 μg/day. A significant increment of aggressiveness was observed in both the sexes (β)=67.9,C.I. 3.4, 172.5, P=0.038, at >4.0 μg. Then, bisphenol-A treatments significantly abrogated spatial learning and ability in males (Pbisphenol-A, e.g. ≤120 μg/day, were associated to behavioural aberrations in offspring. Copyright © 2014. Published by Elsevier Ireland Ltd.

  11. SPECIFICS OF THE APPLICATIONS OF MULTIPLE REGRESSION MODEL IN THE ANALYSES OF THE EFFECTS OF GLOBAL FINANCIAL CRISES

    Directory of Open Access Journals (Sweden)

    Željko V. Račić

    2010-12-01

    Full Text Available This paper aims to present the specifics of the application of multiple linear regression model. The economic (financial crisis is analyzed in terms of gross domestic product which is in a function of the foreign trade balance (on one hand and the credit cards, i.e. indebtedness of the population on this basis (on the other hand, in the USA (from 1999. to 2008. We used the extended application model which shows how the analyst should run the whole development process of regression model. This process began with simple statistical features and the application of regression procedures, and ended with residual analysis, intended for the study of compatibility of data and model settings. This paper also analyzes the values of some standard statistics used in the selection of appropriate regression model. Testing of the model is carried out with the use of the Statistics PASW 17 program.

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

    Science.gov (United States)

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

    2017-11-03

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

  13. Using synthetic data to evaluate multiple regression and principal component analyses for statistical modeling of daily building energy consumption

    Energy Technology Data Exchange (ETDEWEB)

    Reddy, T.A. (Energy Systems Lab., Texas A and M Univ., College Station, TX (United States)); Claridge, D.E. (Energy Systems Lab., Texas A and M Univ., College Station, TX (United States))

    1994-01-01

    Multiple regression modeling of monitored building energy use data is often faulted as a reliable means of predicting energy use on the grounds that multicollinearity between the regressor variables can lead both to improper interpretation of the relative importance of the various physical regressor parameters and to a model with unstable regressor coefficients. Principal component analysis (PCA) has the potential to overcome such drawbacks. While a few case studies have already attempted to apply this technique to building energy data, the objectives of this study were to make a broader evaluation of PCA and multiple regression analysis (MRA) and to establish guidelines under which one approach is preferable to the other. Four geographic locations in the US with different climatic conditions were selected and synthetic data sequence representative of daily energy use in large institutional buildings were generated in each location using a linear model with outdoor temperature, outdoor specific humidity and solar radiation as the three regression variables. MRA and PCA approaches were then applied to these data sets and their relative performances were compared. Conditions under which PCA seems to perform better than MRA were identified and preliminary recommendations on the use of either modeling approach formulated. (orig.)

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

    Science.gov (United States)

    Laszlo, Sarah; Federmeier, Kara D.

    2010-01-01

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

  15. 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.

  16. Dysmenorrhea and self-care strategies in Iranian female students: a regression modeling of pain severity and underlying factors.

    Science.gov (United States)

    Ghaderi, Fariba; Asghari Jafarabadi, Mohammad; Mohseni Bandpei, Mohammad Ali

    2016-07-18

    Dysmenorrhea is the most common gynecologic condition experienced by menstruating women and has significant medical and psychosocial impacts. The objective of this study was to determine the prevalence and the problems related to menstruation, self-care strategies and their relations with pain severity in female students of Tabriz University of Medical Sciences. This cross sectional study was carried out among 197 unmarried and healthy female medical students during April 2013 to July 2013. A standardized questionnaire was given to participants to complete, which included questions about demographic information, prevalence and severity of pain, self-care strategies and its effectiveness. The prevalence of dysmenorrhea was 98.4% (95% confidence interval=97.6%-99.2%). Almost 76% (149) of students reported limitation of daily activities. The most common method for relief pain were: taking analgesics (64.3%), rest (61.9%), taking herbal medicine (11.7%), and applying hot compress on area of pain (22.3%). Obtaining information about self-care strategies offered from family and friends 79 (41%) were more common than scientific articles 56 (28.7%) and the Internet 43 (22%). Significant relations were observed between self-care strategies' scales and pain severity. The results indicated that dysmenorrhea was highly prevalent among female medical students and is a major problem affecting their life. A variety of treatments is available for dysmenorrhea but most of the participants did not seek medical advice and they used self-care strategies. However, further studies focusing on health education and routine screening for menstrual problems are recommended.

  17. Structural vascular disease in Africans: performance of ethnic-specific waist circumference cut points using logistic regression and neural network analyses: the SABPA study

    OpenAIRE

    Botha, J.; De Ridder, J.H.; Potgieter, J.C.; Steyn, H.S.; Malan, L.

    2013-01-01

    A recently proposed model for waist circumference cut points (RPWC), driven by increased blood pressure, was demonstrated in an African population. We therefore aimed to validate the RPWC by comparing the RPWC and the Joint Statement Consensus (JSC) models via Logistic Regression (LR) and Neural Networks (NN) analyses. Urban African gender groups (N=171) were stratified according to the JSC and RPWC cut point models. Ultrasound carotid intima media thickness (CIMT), blood pressure (BP) and fa...

  18. Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing.

    Science.gov (United States)

    Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L

    2018-02-01

    A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R 2 ), using R 2 as the primary metric of assay agreement. However, the use of R 2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  19. Syphilis infection among female sex workers in Nagaland, Northeast India: analysing their vulnerability to the infection.

    Science.gov (United States)

    Medhi, G K; Mahanta, J; Hazarika, I; Armstrong, G; Adhikary, R; Mainkar, M; Paranjape, R S

    2013-03-01

    This paper describes the sex work characteristics and factors associated with syphilis among female sex workers (FSWs) in Dimapur district of high HIV prevalence Indian state, Nagaland. The study recruited 426 FSWs in 2006 using respondent-driven sampling. The prevalence of syphilis was 21.1% and HIV prevalence was 11.7%. Approximately half were under 25 years of age. Clients were solicited mainly in public places (32.7%), while hotels/lodges/rented rooms were the most common places of entertainment (57.2%). Condom use during the last sex was 36.5% with occasional and 27% with regular clients. Being married, being widowed/divorced/separated, being illiterate or having a history of drug use increased the likelihood of syphilis infection. Entertaining clients in bars/booze joints decreased the probability of syphilis. FSWs who moved between soliciting in public places or bars/booze joints and then entertaining in hotels/lodges/rented rooms had a higher vulnerability to syphilis. In summary, we found that the vulnerability to syphilis among mostly young FSWs in Dimapur varied according to their sex work characteristics, marital and educational status and drug use habits. They may be more vulnerable to HIV and sexually transmitted infections (HIV/STIs) due to the low rate of condom use. The findings have direct implications for HIV/STI prevention programmes in Northeast India.

  20. Classification and regression tree (CART) analyses of genomic signatures reveal sets of tetramers that discriminate temperature optima of archaea and bacteria

    Science.gov (United States)

    Dyer, Betsey D.; Kahn, Michael J.; LeBlanc, Mark D.

    2008-01-01

    Classification and regression tree (CART) analysis was applied to genome-wide tetranucleotide frequencies (genomic signatures) of 195 archaea and bacteria. Although genomic signatures have typically been used to classify evolutionary divergence, in this study, convergent evolution was the focus. Temperature optima for most of the organisms examined could be distinguished by CART analyses of tetranucleotide frequencies. This suggests that pervasive (nonlinear) qualities of genomes may reflect certain environmental conditions (such as temperature) in which those genomes evolved. The predominant use of GAGA and AGGA as the discriminating tetramers in CART models suggests that purine-loading and codon biases of thermophiles may explain some of the results. PMID:19054742

  1. Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic.

    Science.gov (United States)

    Bowden, Jack; Del Greco M, Fabiola; Minelli, Cosetta; Davey Smith, George; Sheehan, Nuala A; Thompson, John R

    2016-12-01

    : MR-Egger regression has recently been proposed as a method for Mendelian randomization (MR) analyses incorporating summary data estimates of causal effect from multiple individual variants, which is robust to invalid instruments. It can be used to test for directional pleiotropy and provides an estimate of the causal effect adjusted for its presence. MR-Egger regression provides a useful additional sensitivity analysis to the standard inverse variance weighted (IVW) approach that assumes all variants are valid instruments. Both methods use weights that consider the single nucleotide polymorphism (SNP)-exposure associations to be known, rather than estimated. We call this the `NO Measurement Error' (NOME) assumption. Causal effect estimates from the IVW approach exhibit weak instrument bias whenever the genetic variants utilized violate the NOME assumption, which can be reliably measured using the F-statistic. The effect of NOME violation on MR-Egger regression has yet to be studied. An adaptation of the I2 statistic from the field of meta-analysis is proposed to quantify the strength of NOME violation for MR-Egger. It lies between 0 and 1, and indicates the expected relative bias (or dilution) of the MR-Egger causal estimate in the two-sample MR context. We call it IGX2 . The method of simulation extrapolation is also explored to counteract the dilution. Their joint utility is evaluated using simulated data and applied to a real MR example. In simulated two-sample MR analyses we show that, when a causal effect exists, the MR-Egger estimate of causal effect is biased towards the null when NOME is violated, and the stronger the violation (as indicated by lower values of IGX2 ), the stronger the dilution. When additionally all genetic variants are valid instruments, the type I error rate of the MR-Egger test for pleiotropy is inflated and the causal effect underestimated. Simulation extrapolation is shown to substantially mitigate these adverse effects. We

  2. [Prevalence and factors associated with intimate partner abuse in female users of public health services in Mexico: a comparative analyses].

    Science.gov (United States)

    Ávila-Burgos, Leticia; Valdez-Santiagob, Rosario; Barroso-Quiab, Abigail; Híjar, Martha; Rojas, Rosalba; Del Río-Zolezzi, Aurora

    2014-01-01

    To analyze the evolution of the prevalence in intimate partner violence during the years 2003 and 2006 in Mexico, identifying factors associated with its severity, comparing our results with findings from 2003. Data from the Encuesta Nacional de Violencia contra las Mujeres (ENVIM 2006) was used; it has urban-rural national representation of female users of Mexican public health services. A total of 22,318 women above 14 years of age were interviewed. A multinomial logistic regression model was adjusted. The dependent variable was the Index of Intimate Partner Abuse. Intimate partner abuse increased 17% in comparison to the year 2003. Women's personal history of childhood abuse (ORA= 5.12, 95% CI4.15-6.30) and rape (ORA = 3.5, 95% CI = 2.66-4.62) were the most important women's factors that were found associated with severe violence. Male partner's daily alcohol consumption increased eleven fold the possibility of severe violence; higher disagreement with traditional female gender roles and higher education of both partners were protective factors. Factors associated with violence and their severities were consistent with findings reported in 2003. Intimate partner violence is a highly prevalent social problem which requires comprehensive strategies supporting empowerment of women through higher education, early detection and care of those battered, as well as structured interventions to prevent violence in future generations.

  3. The more total cognitive load is reduced by cues, the better retention and transfer of multimedia learning: A meta-analysis and two meta-regression analyses.

    Science.gov (United States)

    Xie, Heping; Wang, Fuxing; Hao, Yanbin; Chen, Jiaxue; An, Jing; Wang, Yuxin; Liu, Huashan

    2017-01-01

    Cueing facilitates retention and transfer of multimedia learning. From the perspective of cognitive load theory (CLT), cueing has a positive effect on learning outcomes because of the reduction in total cognitive load and avoidance of cognitive overload. However, this has not been systematically evaluated. Moreover, what remains ambiguous is the direct relationship between the cue-related cognitive load and learning outcomes. A meta-analysis and two subsequent meta-regression analyses were conducted to explore these issues. Subjective total cognitive load (SCL) and scores on a retention test and transfer test were selected as dependent variables. Through a systematic literature search, 32 eligible articles encompassing 3,597 participants were included in the SCL-related meta-analysis. Among them, 25 articles containing 2,910 participants were included in the retention-related meta-analysis and the following retention-related meta-regression, while there were 29 articles containing 3,204 participants included in the transfer-related meta-analysis and the transfer-related meta-regression. The meta-analysis revealed a statistically significant cueing effect on subjective ratings of cognitive load (d = -0.11, 95% CI = [-0.19, -0.02], p < 0.05), retention performance (d = 0.27, 95% CI = [0.08, 0.46], p < 0.01), and transfer performance (d = 0.34, 95% CI = [0.12, 0.56], p < 0.01). The subsequent meta-regression analyses showed that dSCL for cueing significantly predicted dretention for cueing (β = -0.70, 95% CI = [-1.02, -0.38], p < 0.001), as well as dtransfer for cueing (β = -0.60, 95% CI = [-0.92, -0.28], p < 0.001). Thus in line with CLT, adding cues in multimedia materials can indeed reduce SCL and promote learning outcomes, and the more SCL is reduced by cues, the better retention and transfer of multimedia learning.

  4. Influence of regression model and incremental test protocol on the relationship between lactate threshold using the maximal-deviation method and performance in female runners.

    Science.gov (United States)

    Machado, Fabiana Andrade; Nakamura, Fábio Yuzo; Moraes, Solange Marta Franzói De

    2012-01-01

    This study examined the influence of the regression model and initial intensity of an incremental test on the relationship between the lactate threshold estimated by the maximal-deviation method and the endurance performance. Sixteen non-competitive, recreational female runners performed a discontinuous incremental treadmill test. The initial speed was set at 7 km · h⁻¹, and increased every 3 min by 1 km · h⁻¹ with a 30-s rest between the stages used for earlobe capillary blood sample collection. Lactate-speed data were fitted by an exponential-plus-constant and a third-order polynomial equation. The lactate threshold was determined for both regression equations, using all the coordinates, excluding the first and excluding the first and second initial points. Mean speed of a 10-km road race was the performance index (3.04 ± 0.22 m · s⁻¹). The exponentially-derived lactate threshold had a higher correlation (0.98 ≤ r ≤ 0.99) and smaller standard error of estimate (SEE) (0.04 ≤ SEE ≤ 0.05 m · s⁻¹) with performance than the polynomially-derived equivalent (0.83 ≤ r ≤ 0.89; 0.10 ≤ SEE ≤ 0.13 m · s⁻¹). The exponential lactate threshold was greater than the polynomial equivalent (P performance index that is independent of the initial intensity of the incremental test and better than the polynomial equivalent.

  5. Predictors of success of external cephalic version and cephalic presentation at birth among 1253 women with non-cephalic presentation using logistic regression and classification tree analyses.

    Science.gov (United States)

    Hutton, Eileen K; Simioni, Julia C; Thabane, Lehana

    2017-08-01

    Among women with a fetus with a non-cephalic presentation, external cephalic version (ECV) has been shown to reduce the rate of breech presentation at birth and cesarean birth. Compared with ECV at term, beginning ECV prior to 37 weeks' gestation decreases the number of infants in a non-cephalic presentation at birth. The purpose of this secondary analysis was to investigate factors associated with a successful ECV procedure and to present this in a clinically useful format. Data were collected as part of the Early ECV Pilot and Early ECV2 Trials, which randomized 1776 women with a fetus in breech presentation to either early ECV (34-36 weeks' gestation) or delayed ECV (at or after 37 weeks). The outcome of interest was successful ECV, defined as the fetus being in a cephalic presentation immediately following the procedure, as well as at the time of birth. The importance of several factors in predicting successful ECV was investigated using two statistical methods: logistic regression and classification and regression tree (CART) analyses. Among nulliparas, non-engagement of the presenting part and an easily palpable fetal head were independently associated with success. Among multiparas, non-engagement of the presenting part, gestation less than 37 weeks and an easily palpable fetal head were found to be independent predictors of success. These findings were consistent with results of the CART analyses. Regardless of parity, descent of the presenting part was the most discriminating factor in predicting successful ECV and cephalic presentation at birth. © 2017 Nordic Federation of Societies of Obstetrics and Gynecology.

  6. Analyses of polycyclic aromatic hydrocarbon (PAH) and chiral-PAH analogues-methyl-β-cyclodextrin guest-host inclusion complexes by fluorescence spectrophotometry and multivariate regression analysis.

    Science.gov (United States)

    Greene, LaVana; Elzey, Brianda; Franklin, Mariah; Fakayode, Sayo O

    2017-03-05

    The negative health impact of polycyclic aromatic hydrocarbons (PAHs) and differences in pharmacological activity of enantiomers of chiral molecules in humans highlights the need for analysis of PAHs and their chiral analogue molecules in humans. Herein, the first use of cyclodextrin guest-host inclusion complexation, fluorescence spectrophotometry, and chemometric approach to PAH (anthracene) and chiral-PAH analogue derivatives (1-(9-anthryl)-2,2,2-triflouroethanol (TFE)) analyses are reported. The binding constants (K b ), stoichiometry (n), and thermodynamic properties (Gibbs free energy (ΔG), enthalpy (ΔH), and entropy (ΔS)) of anthracene and enantiomers of TFE-methyl-β-cyclodextrin (Me-β-CD) guest-host complexes were also determined. Chemometric partial-least-square (PLS) regression analysis of emission spectra data of Me-β-CD-guest-host inclusion complexes was used for the determination of anthracene and TFE enantiomer concentrations in Me-β-CD-guest-host inclusion complex samples. The values of calculated K b and negative ΔG suggest the thermodynamic favorability of anthracene-Me-β-CD and enantiomeric of TFE-Me-β-CD inclusion complexation reactions. However, anthracene-Me-β-CD and enantiomer TFE-Me-β-CD inclusion complexations showed notable differences in the binding affinity behaviors and thermodynamic properties. The PLS regression analysis resulted in square-correlation-coefficients of 0.997530 or better and a low LOD of 3.81×10 -7 M for anthracene and 3.48×10 -8 M for TFE enantiomers at physiological conditions. Most importantly, PLS regression accurately determined the anthracene and TFE enantiomer concentrations with an average low error of 2.31% for anthracene, 4.44% for R-TFE and 3.60% for S-TFE. The results of the study are highly significant because of its high sensitivity and accuracy for analysis of PAH and chiral PAH analogue derivatives without the need of an expensive chiral column, enantiomeric resolution, or use of a polarized

  7. Exploring reasons for the observed inconsistent trial reports on intra-articular injections with hyaluronic acid in the treatment of osteoarthritis: Meta-regression analyses of randomized trials.

    Science.gov (United States)

    Johansen, Mette; Bahrt, Henriette; Altman, Roy D; Bartels, Else M; Juhl, Carsten B; Bliddal, Henning; Lund, Hans; Christensen, Robin

    2016-08-01

    The aim was to identify factors explaining inconsistent observations concerning the efficacy of intra-articular hyaluronic acid compared to intra-articular sham/control, or non-intervention control, in patients with symptomatic osteoarthritis, based on randomized clinical trials (RCTs). A systematic review and meta-regression analyses of available randomized trials were conducted. The outcome, pain, was assessed according to a pre-specified hierarchy of potentially available outcomes. Hedges׳s standardized mean difference [SMD (95% CI)] served as effect size. REstricted Maximum Likelihood (REML) mixed-effects models were used to combine study results, and heterogeneity was calculated and interpreted as Tau-squared and I-squared, respectively. Overall, 99 studies (14,804 patients) met the inclusion criteria: Of these, only 71 studies (72%), including 85 comparisons (11,216 patients), had adequate data available for inclusion in the primary meta-analysis. Overall, compared with placebo, intra-articular hyaluronic acid reduced pain with an effect size of -0.39 [-0.47 to -0.31; P hyaluronic acid. Based on available trial data, intra-articular hyaluronic acid showed a better effect than intra-articular saline on pain reduction in osteoarthritis. Publication bias and the risk of selective outcome reporting suggest only small clinical effect compared to saline. Copyright © 2016 Elsevier Inc. All rights reserved.

  8. Item Response Theory Modeling and Categorical Regression Analyses of the Five-Factor Model Rating Form: A Study on Italian Community-Dwelling Adolescent Participants and Adult Participants.

    Science.gov (United States)

    Fossati, Andrea; Widiger, Thomas A; Borroni, Serena; Maffei, Cesare; Somma, Antonella

    2017-06-01

    To extend the evidence on the reliability and construct validity of the Five-Factor Model Rating Form (FFMRF) in its self-report version, two independent samples of Italian participants, which were composed of 510 adolescent high school students and 457 community-dwelling adults, respectively, were administered the FFMRF in its Italian translation. Adolescent participants were also administered the Italian translation of the Borderline Personality Features Scale for Children-11 (BPFSC-11), whereas adult participants were administered the Italian translation of the Triarchic Psychopathy Measure (TriPM). Cronbach α values were consistent with previous findings; in both samples, average interitem r values indicated acceptable internal consistency for all FFMRF scales. A multidimensional graded item response theory model indicated that the majority of FFMRF items had adequate discrimination parameters; information indices supported the reliability of the FFMRF scales. Both categorical (i.e., item-level) and scale-level regression analyses suggested that the FFMRF scores may predict a nonnegligible amount of variance in the BPFSC-11 total score in adolescent participants, and in the TriPM scale scores in adult participants.

  9. Effective behaviour change techniques for physical activity and healthy eating in overweight and obese adults; systematic review and meta-regression analyses.

    Science.gov (United States)

    Samdal, Gro Beate; Eide, Geir Egil; Barth, Tom; Williams, Geoffrey; Meland, Eivind

    2017-03-28

    This systematic review aims to explain the heterogeneity in results of interventions to promote physical activity and healthy eating for overweight and obese adults, by exploring the differential effects of behaviour change techniques (BCTs) and other intervention characteristics. The inclusion criteria specified RCTs with ≥ 12 weeks' duration, from January 2007 to October 2014, for adults (mean age ≥ 40 years, mean BMI ≥ 30). Primary outcomes were measures of healthy diet or physical activity. Two reviewers rated study quality, coded the BCTs, and collected outcome results at short (≤6 months) and long term (≥12 months). Meta-analyses and meta-regressions were used to estimate effect sizes (ES), heterogeneity indices (I 2 ) and regression coefficients. We included 48 studies containing a total of 82 outcome reports. The 32 long term reports had an overall ES = 0.24 with 95% confidence interval (CI): 0.15 to 0.33 and I 2  = 59.4%. The 50 short term reports had an ES = 0.37 with 95% CI: 0.26 to 0.48, and I 2  = 71.3%. The number of BCTs unique to the intervention group, and the BCTs goal setting and self-monitoring of behaviour predicted the effect at short and long term. The total number of BCTs in both intervention arms and using the BCTs goal setting of outcome, feedback on outcome of behaviour, implementing graded tasks, and adding objects to the environment, e.g. using a step counter, significantly predicted the effect at long term. Setting a goal for change; and the presence of reporting bias independently explained 58.8% of inter-study variation at short term. Autonomy supportive and person-centred methods as in Motivational Interviewing, the BCTs goal setting of behaviour, and receiving feedback on the outcome of behaviour, explained all of the between study variations in effects at long term. There are similarities, but also differences in effective BCTs promoting change in healthy eating and physical activity and

  10. 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...

  11. Personal, social, and game-related correlates of active and non-active gaming among dutch gaming adolescents: survey-based multivariable, multilevel logistic regression analyses.

    Science.gov (United States)

    Simons, Monique; de Vet, Emely; Chinapaw, Mai Jm; de Boer, Michiel; Seidell, Jacob C; Brug, Johannes

    2014-04-04

    Playing video games contributes substantially to sedentary behavior in youth. A new generation of video games-active games-seems to be a promising alternative to sedentary games to promote physical activity and reduce sedentary behavior. At this time, little is known about correlates of active and non-active gaming among adolescents. The objective of this study was to examine potential personal, social, and game-related correlates of both active and non-active gaming in adolescents. A survey assessing game behavior and potential personal, social, and game-related correlates was conducted among adolescents (12-16 years, N=353) recruited via schools. Multivariable, multilevel logistic regression analyses, adjusted for demographics (age, sex and educational level of adolescents), were conducted to examine personal, social, and game-related correlates of active gaming ≥1 hour per week (h/wk) and non-active gaming >7 h/wk. Active gaming ≥1 h/wk was significantly associated with a more positive attitude toward active gaming (OR 5.3, CI 2.4-11.8; Pgames (OR 0.30, CI 0.1-0.6; P=.002), a higher score on habit strength regarding gaming (OR 1.9, CI 1.2-3.2; P=.008) and having brothers/sisters (OR 6.7, CI 2.6-17.1; Pgame engagement (OR 0.95, CI 0.91-0.997; P=.04). Non-active gaming >7 h/wk was significantly associated with a more positive attitude toward non-active gaming (OR 2.6, CI 1.1-6.3; P=.035), a stronger habit regarding gaming (OR 3.0, CI 1.7-5.3; P7 h/wk. Active gaming is most strongly (negatively) associated with attitude with respect to non-active games, followed by observed active game behavior of brothers and sisters and attitude with respect to active gaming (positive associations). On the other hand, non-active gaming is most strongly associated with observed non-active game behavior of friends, habit strength regarding gaming and attitude toward non-active gaming (positive associations). Habit strength was a correlate of both active and non-active gaming

  12. Personal, Social, and Game-Related Correlates of Active and Non-Active Gaming Among Dutch Gaming Adolescents: Survey-Based Multivariable, Multilevel Logistic Regression Analyses

    Science.gov (United States)

    de Vet, Emely; Chinapaw, Mai JM; de Boer, Michiel; Seidell, Jacob C; Brug, Johannes

    2014-01-01

    Background Playing video games contributes substantially to sedentary behavior in youth. A new generation of video games—active games—seems to be a promising alternative to sedentary games to promote physical activity and reduce sedentary behavior. At this time, little is known about correlates of active and non-active gaming among adolescents. Objective The objective of this study was to examine potential personal, social, and game-related correlates of both active and non-active gaming in adolescents. Methods A survey assessing game behavior and potential personal, social, and game-related correlates was conducted among adolescents (12-16 years, N=353) recruited via schools. Multivariable, multilevel logistic regression analyses, adjusted for demographics (age, sex and educational level of adolescents), were conducted to examine personal, social, and game-related correlates of active gaming ≥1 hour per week (h/wk) and non-active gaming >7 h/wk. Results Active gaming ≥1 h/wk was significantly associated with a more positive attitude toward active gaming (OR 5.3, CI 2.4-11.8; Pgames (OR 0.30, CI 0.1-0.6; P=.002), a higher score on habit strength regarding gaming (OR 1.9, CI 1.2-3.2; P=.008) and having brothers/sisters (OR 6.7, CI 2.6-17.1; Pgame engagement (OR 0.95, CI 0.91-0.997; P=.04). Non-active gaming >7 h/wk was significantly associated with a more positive attitude toward non-active gaming (OR 2.6, CI 1.1-6.3; P=.035), a stronger habit regarding gaming (OR 3.0, CI 1.7-5.3; P7 h/wk. Active gaming is most strongly (negatively) associated with attitude with respect to non-active games, followed by observed active game behavior of brothers and sisters and attitude with respect to active gaming (positive associations). On the other hand, non-active gaming is most strongly associated with observed non-active game behavior of friends, habit strength regarding gaming and attitude toward non-active gaming (positive associations). Habit strength was a

  13. Increasing hookah use among adolescent females in the US: analyses from the 2011-2014 National Youth Tobacco Survey (NYTS

    Directory of Open Access Journals (Sweden)

    Jenni A. Shearston

    2016-09-01

    These data demonstrate the magnitude of adolescent hookah use, particularly among adolescents who use electronic or traditional cigarettes. Most strikingly, rates of female adolescent use have increased much more rapidly than has male use, and adolescent females are for the first time more likely to smoke hookahs than adolescent males in the US nationwide. These findings urgently call for better understanding of the changing correlates of hookah use, including polytobacco use.

  14. Consequences of kriging and land use regression for PM2.5 predictions in epidemiologic analyses: insights into spatial variability using high-resolution satellite data.

    Science.gov (United States)

    Alexeeff, Stacey E; Schwartz, Joel; Kloog, Itai; Chudnovsky, Alexandra; Koutrakis, Petros; Coull, Brent A

    2015-01-01

    Many epidemiological studies use predicted air pollution exposures as surrogates for true air pollution levels. These predicted exposures contain exposure measurement error, yet simulation studies have typically found negligible bias in resulting health effect estimates. However, previous studies typically assumed a statistical spatial model for air pollution exposure, which may be oversimplified. We address this shortcoming by assuming a realistic, complex exposure surface derived from fine-scale (1 km × 1 km) remote-sensing satellite data. Using simulation, we evaluate the accuracy of epidemiological health effect estimates in linear and logistic regression when using spatial air pollution predictions from kriging and land use regression models. We examined chronic (long-term) and acute (short-term) exposure to air pollution. Results varied substantially across different scenarios. Exposure models with low out-of-sample R(2) yielded severe biases in the health effect estimates of some models, ranging from 60% upward bias to 70% downward bias. One land use regression exposure model with >0.9 out-of-sample R(2) yielded upward biases up to 13% for acute health effect estimates. Almost all models drastically underestimated the SEs. Land use regression models performed better in chronic effect simulations. These results can help researchers when interpreting health effect estimates in these types of studies.

  15. Insight into the Female Longevity Puzzle: Using Register Data to Analyse Mortality and Cause of Death Behaviour Across Socio-economic Groups

    DEFF Research Database (Denmark)

    Kallestrup-Lamb, Malene; Rosenskjold, Carsten Paysen T.

    This paper analyses the complexity of female longevity improvements. As socio-economic status influence health and mortality, we partition all individuals, at each age and year, into ten socio-economic groups based on an affluence measure. We identify the particular socio-economic groups that have...... for all subgroups, however with particular large decreases for the low-middle and middle affluence groups. We find that causes of deaths related to smoking partly contribute to the slowdown in female longevity. However the lack of improvements in deaths relating to ischemic heart diseases is dominant...

  16. Human Immunodeficiency Viruses Appear Compartmentalized to the Female Genital Tract in Cross-Sectional Analyses but Genital Lineages Do Not Persist Over Time

    OpenAIRE

    Bull, Marta E.; Heath, Laura M.; McKernan-Mullin, Jennifer L.; Kraft, Kelli M.; Acevedo, Luis; Hitti, Jane E.; Cohn, Susan E.; Tapia, Kenneth A.; Holte, Sarah E.; Dragavon, Joan A.; Coombs, Robert W.; Mullins, James I.; Frenkel, Lisa M.

    2013-01-01

    Background. Whether unique human immunodeficiency type 1 (HIV) genotypes occur in the genital tract is important for vaccine development and management of drug resistant viruses. Multiple cross-sectional studies suggest HIV is compartmentalized within the female genital tract. We hypothesize that bursts of HIV replication and/or proliferation of infected cells captured in cross-sectional analyses drive compartmentalization but over time genital-specific viral lineages do not form; rather viru...

  17. 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...

  18. Univariate and multiple linear regression analyses for 23 single nucleotide polymorphisms in 14 genes predisposing to chronic glomerular diseases and IgA nephropathy in Han Chinese.

    Science.gov (United States)

    Wang, Hui; Sui, Weiguo; Xue, Wen; Wu, Junyong; Chen, Jiejing; Dai, Yong

    2014-09-01

    Immunoglobulin A nephropathy (IgAN) is a complex trait regulated by the interaction among multiple physiologic regulatory systems and probably involving numerous genes, which leads to inconsistent findings in genetic studies. One possibility of failure to replicate some single-locus results is that the underlying genetics of IgAN nephropathy is based on multiple genes with minor effects. To learn the association between 23 single nucleotide polymorphisms (SNPs) in 14 genes predisposing to chronic glomerular diseases and IgAN in Han males, the 23 SNPs genotypes of 21 Han males were detected and analyzed with a BaiO gene chip, and their associations were analyzed with univariate analysis and multiple linear regression analysis. Analysis showed that CTLA4 rs231726 and CR2 rs1048971 revealed a significant association with IgAN. These findings support the multi-gene nature of the etiology of IgAN and propose a potential gene-gene interactive model for future studies.

  19. Meta-regression analyses to explain statistical heterogeneity in a systematic review of strategies for guideline implementation in primary health care.

    Directory of Open Access Journals (Sweden)

    Susanne Unverzagt

    Full Text Available This study is an in-depth-analysis to explain statistical heterogeneity in a systematic review of implementation strategies to improve guideline adherence of primary care physicians in the treatment of patients with cardiovascular diseases. The systematic review included randomized controlled trials from a systematic search in MEDLINE, EMBASE, CENTRAL, conference proceedings and registers of ongoing studies. Implementation strategies were shown to be effective with substantial heterogeneity of treatment effects across all investigated strategies. Primary aim of this study was to explain different effects of eligible trials and to identify methodological and clinical effect modifiers. Random effects meta-regression models were used to simultaneously assess the influence of multimodal implementation strategies and effect modifiers on physician adherence. Effect modifiers included the staff responsible for implementation, level of prevention and definition pf the primary outcome, unit of randomization, duration of follow-up and risk of bias. Six clinical and methodological factors were investigated as potential effect modifiers of the efficacy of different implementation strategies on guideline adherence in primary care practices on the basis of information from 75 eligible trials. Five effect modifiers were able to explain a substantial amount of statistical heterogeneity. Physician adherence was improved by 62% (95% confidence interval (95% CI 29 to 104% or 29% (95% CI 5 to 60% in trials where other non-medical professionals or nurses were included in the implementation process. Improvement of physician adherence was more successful in primary and secondary prevention of cardiovascular diseases by around 30% (30%; 95% CI -2 to 71% and 31%; 95% CI 9 to 57%, respectively compared to tertiary prevention. This study aimed to identify effect modifiers of implementation strategies on physician adherence. Especially the cooperation of different health

  20. Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part II: Evaluation of Sample Models

    Science.gov (United States)

    Duda, David P.; Minnis, Patrick

    2009-01-01

    Previous studies have shown that probabilistic forecasting may be a useful method for predicting persistent contrail formation. A probabilistic forecast to accurately predict contrail formation over the contiguous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and from the Rapid Update Cycle (RUC) as well as GOES water vapor channel measurements, combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The mean accuracies for both the SURFACE and OUTBREAK models typically exceeded 75 percent when based on the RUC or ARPS analysis data, but decreased when the logistic models were derived from ARPS forecast data.

  1. Human immunodeficiency viruses appear compartmentalized to the female genital tract in cross-sectional analyses but genital lineages do not persist over time.

    Science.gov (United States)

    Bull, Marta E; Heath, Laura M; McKernan-Mullin, Jennifer L; Kraft, Kelli M; Acevedo, Luis; Hitti, Jane E; Cohn, Susan E; Tapia, Kenneth A; Holte, Sarah E; Dragavon, Joan A; Coombs, Robert W; Mullins, James I; Frenkel, Lisa M

    2013-04-15

    Whether unique human immunodeficiency type 1 (HIV) genotypes occur in the genital tract is important for vaccine development and management of drug resistant viruses. Multiple cross-sectional studies suggest HIV is compartmentalized within the female genital tract. We hypothesize that bursts of HIV replication and/or proliferation of infected cells captured in cross-sectional analyses drive compartmentalization but over time genital-specific viral lineages do not form; rather viruses mix between genital tract and blood. Eight women with ongoing HIV replication were studied during a period of 1.5 to 4.5 years. Multiple viral sequences were derived by single-genome amplification of the HIV C2-V5 region of env from genital secretions and blood plasma. Maximum likelihood phylogenies were evaluated for compartmentalization using 4 statistical tests. In cross-sectional analyses compartmentalization of genital from blood viruses was detected in three of eight women by all tests; this was associated with tissue specific clades containing multiple monotypic sequences. In longitudinal analysis, the tissues-specific clades did not persist to form viral lineages. Rather, across women, HIV lineages were comprised of both genital tract and blood sequences. The observation of genital-specific HIV clades only in cross-sectional analysis and an absence of genital-specific lineages in longitudinal analyses suggest a dynamic interchange of HIV variants between the female genital tract and blood.

  2. Human Immunodeficiency Viruses Appear Compartmentalized to the Female Genital Tract in Cross-Sectional Analyses but Genital Lineages Do Not Persist Over Time

    Science.gov (United States)

    Bull, Marta E.; Heath, Laura M.; McKernan-Mullin, Jennifer L.; Kraft, Kelli M.; Acevedo, Luis; Hitti, Jane E.; Cohn, Susan E.; Tapia, Kenneth A.; Holte, Sarah E.; Dragavon, Joan A.; Coombs, Robert W.; Mullins, James I.; Frenkel, Lisa M.

    2013-01-01

    Background. Whether unique human immunodeficiency type 1 (HIV) genotypes occur in the genital tract is important for vaccine development and management of drug resistant viruses. Multiple cross-sectional studies suggest HIV is compartmentalized within the female genital tract. We hypothesize that bursts of HIV replication and/or proliferation of infected cells captured in cross-sectional analyses drive compartmentalization but over time genital-specific viral lineages do not form; rather viruses mix between genital tract and blood. Methods. Eight women with ongoing HIV replication were studied during a period of 1.5 to 4.5 years. Multiple viral sequences were derived by single-genome amplification of the HIV C2-V5 region of env from genital secretions and blood plasma. Maximum likelihood phylogenies were evaluated for compartmentalization using 4 statistical tests. Results. In cross-sectional analyses compartmentalization of genital from blood viruses was detected in three of eight women by all tests; this was associated with tissue specific clades containing multiple monotypic sequences. In longitudinal analysis, the tissues-specific clades did not persist to form viral lineages. Rather, across women, HIV lineages were comprised of both genital tract and blood sequences. Conclusions. The observation of genital-specific HIV clades only in cross-sectional analysis and an absence of genital-specific lineages in longitudinal analyses suggest a dynamic interchange of HIV variants between the female genital tract and blood. PMID:23315326

  3. Propensity-score matching in economic analyses: comparison with regression models, instrumental variables, residual inclusion, differences-in-differences, and decomposition methods.

    Science.gov (United States)

    Crown, William H

    2014-02-01

    This paper examines the use of propensity score matching in economic analyses of observational data. Several excellent papers have previously reviewed practical aspects of propensity score estimation and other aspects of the propensity score literature. The purpose of this paper is to compare the conceptual foundation of propensity score models with alternative estimators of treatment effects. References are provided to empirical comparisons among methods that have appeared in the literature. These comparisons are available for a subset of the methods considered in this paper. However, in some cases, no pairwise comparisons of particular methods are yet available, and there are no examples of comparisons across all of the methods surveyed here. Irrespective of the availability of empirical comparisons, the goal of this paper is to provide some intuition about the relative merits of alternative estimators in health economic evaluations where nonlinearity, sample size, availability of pre/post data, heterogeneity, and missing variables can have important implications for choice of methodology. Also considered is the potential combination of propensity score matching with alternative methods such as differences-in-differences and decomposition methods that have not yet appeared in the empirical literature.

  4. Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part I: Effects of Random Error

    Science.gov (United States)

    Duda, David P.; Minnis, Patrick

    2009-01-01

    Straightforward application of the Schmidt-Appleman contrail formation criteria to diagnose persistent contrail occurrence from numerical weather prediction data is hindered by significant bias errors in the upper tropospheric humidity. Logistic models of contrail occurrence have been proposed to overcome this problem, but basic questions remain about how random measurement error may affect their accuracy. A set of 5000 synthetic contrail observations is created to study the effects of random error in these probabilistic models. The simulated observations are based on distributions of temperature, humidity, and vertical velocity derived from Advanced Regional Prediction System (ARPS) weather analyses. The logistic models created from the simulated observations were evaluated using two common statistical measures of model accuracy, the percent correct (PC) and the Hanssen-Kuipers discriminant (HKD). To convert the probabilistic results of the logistic models into a dichotomous yes/no choice suitable for the statistical measures, two critical probability thresholds are considered. The HKD scores are higher when the climatological frequency of contrail occurrence is used as the critical threshold, while the PC scores are higher when the critical probability threshold is 0.5. For both thresholds, typical random errors in temperature, relative humidity, and vertical velocity are found to be small enough to allow for accurate logistic models of contrail occurrence. The accuracy of the models developed from synthetic data is over 85 percent for both the prediction of contrail occurrence and non-occurrence, although in practice, larger errors would be anticipated.

  5. Autistic Regression

    Science.gov (United States)

    Matson, Johnny L.; Kozlowski, Alison M.

    2010-01-01

    Autistic regression is one of the many mysteries in the developmental course of autism and pervasive developmental disorders not otherwise specified (PDD-NOS). Various definitions of this phenomenon have been used, further clouding the study of the topic. Despite this problem, some efforts at establishing prevalence have been made. The purpose of…

  6. Regression Analysis

    CERN Document Server

    Freund, Rudolf J; Sa, Ping

    2006-01-01

    The book provides complete coverage of the classical methods of statistical analysis. It is designed to give students an understanding of the purpose of statistical analyses, to allow the student to determine, at least to some degree, the correct type of statistical analyses to be performed in a given situation, and have some appreciation of what constitutes good experimental design

  7. Linear regression

    CERN Document Server

    Olive, David J

    2017-01-01

    This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...

  8. Area under the curve predictions of dalbavancin, a new lipoglycopeptide agent, using the end of intravenous infusion concentration data point by regression analyses such as linear, log-linear and power models.

    Science.gov (United States)

    Bhamidipati, Ravi Kanth; Syed, Muzeeb; Mullangi, Ramesh; Srinivas, Nuggehally

    2018-02-01

    1. Dalbavancin, a lipoglycopeptide, is approved for treating gram-positive bacterial infections. Area under plasma concentration versus time curve (AUC inf ) of dalbavancin is a key parameter and AUC inf /MIC ratio is a critical pharmacodynamic marker. 2. Using end of intravenous infusion concentration (i.e. C max ) C max versus AUC inf relationship for dalbavancin was established by regression analyses (i.e. linear, log-log, log-linear and power models) using 21 pairs of subject data. 3. The predictions of the AUC inf were performed using published C max data by application of regression equations. The quotient of observed/predicted values rendered fold difference. The mean absolute error (MAE)/root mean square error (RMSE) and correlation coefficient (r) were used in the assessment. 4. MAE and RMSE values for the various models were comparable. The C max versus AUC inf exhibited excellent correlation (r > 0.9488). The internal data evaluation showed narrow confinement (0.84-1.14-fold difference) with a RMSE models predicted AUC inf with a RMSE of 3.02-27.46% with fold difference largely contained within 0.64-1.48. 5. Regardless of the regression models, a single time point strategy of using C max (i.e. end of 30-min infusion) is amenable as a prospective tool for predicting AUC inf of dalbavancin in patients.

  9. Secondary mediation and regression analyses of the PTClinResNet database: determining causal relationships among the International Classification of Functioning, Disability and Health levels for four physical therapy intervention trials.

    Science.gov (United States)

    Mulroy, Sara J; Winstein, Carolee J; Kulig, Kornelia; Beneck, George J; Fowler, Eileen G; DeMuth, Sharon K; Sullivan, Katherine J; Brown, David A; Lane, Christianne J

    2011-12-01

    Each of the 4 randomized clinical trials (RCTs) hosted by the Physical Therapy Clinical Research Network (PTClinResNet) targeted a different disability group (low back disorder in the Muscle-Specific Strength Training Effectiveness After Lumbar Microdiskectomy [MUSSEL] trial, chronic spinal cord injury in the Strengthening and Optimal Movements for Painful Shoulders in Chronic Spinal Cord Injury [STOMPS] trial, adult stroke in the Strength Training Effectiveness Post-Stroke [STEPS] trial, and pediatric cerebral palsy in the Pediatric Endurance and Limb Strengthening [PEDALS] trial for children with spastic diplegic cerebral palsy) and tested the effectiveness of a muscle-specific or functional activity-based intervention on primary outcomes that captured pain (STOMPS, MUSSEL) or locomotor function (STEPS, PEDALS). The focus of these secondary analyses was to determine causal relationships among outcomes across levels of the International Classification of Functioning, Disability and Health (ICF) framework for the 4 RCTs. With the database from PTClinResNet, we used 2 separate secondary statistical approaches-mediation analysis for the MUSSEL and STOMPS trials and regression analysis for the STEPS and PEDALS trials-to test relationships among muscle performance, primary outcomes (pain related and locomotor related), activity and participation measures, and overall quality of life. Predictive models were stronger for the 2 studies with pain-related primary outcomes. Change in muscle performance mediated or predicted reductions in pain for the MUSSEL and STOMPS trials and, to some extent, walking speed for the STEPS trial. Changes in primary outcome variables were significantly related to changes in activity and participation variables for all 4 trials. Improvement in activity and participation outcomes mediated or predicted increases in overall quality of life for the 3 trials with adult populations. Variables included in the statistical models were limited to those

  10. Logistic regression analysis of trichomonas vaginalis infection in female adults and its influencing factors%成年女性阴道毛滴虫感染情况及其影响因素的Logistic回归分析

    Institute of Scientific and Technical Information of China (English)

    潘继升; 陈军

    2017-01-01

    目的:分析成年女性阴道毛滴虫感染情况及其影响因素,为成年女性阴道毛滴虫感染的防治提供依据.方法:选择2016年1月至2016年7月于我院确诊的阴道毛滴虫感染患者104例作为感染组.另取同期健康体检者104例作为对照组.分别统计并记录两组患者基本资料,包括年龄、职业、卫生意识等指标,引用多因素Logistic回归分析,分析成年女性阴道毛滴虫感染情况的影响因素.结果:感染组年龄在30 ~ 39岁的人数占比为45.19%,显著高于对照组的30.77%,差异有统计学意义(P<0.05).感染组农民人数占比显著高于对照组;对照组有专用洁阴用巾/盆、了解性传播疾病知识、每天清洗外阴人数占比均显著高于感染组,差异均有统计学意义(P<0.05).经多因素Logistic回归分析可得,年龄30~ 39岁、农民职业、卫生意识差均为影响成年女性阴道毛滴虫感染的危险因素.结论:年龄30~39岁、农民职业、卫生意识差均是成年女性阴道毛滴虫感染的危险因素,临床工作中应加强地区妇女的卫生保健工作,帮助其增强自我保护意识,以降低阴道毛滴虫感染率.%Objectives:To study female trichomonas vaginalis infection in female adults and its influencing factors so as to provide reference to the prevention and treatment of trichomonas vaginalis infection.Methods:104 patients with trichomonas vaginalis infection from January 2016 to July 2016 in our hospital were selected as infection group.Another 104 healthy people were selected as control group.Basic information,including age,occupation,health awareness and other factors,was recorded.Multiple logistic regression analysis on two groups was conducted.Results:The infection group,the number of people aged 30 ~ 39 accounted for 45.19% (47/104),which was significantly higher than that of control group (30.77%,32/104),with statistically significant differences (P < 0.05).The number of

  11. Differentiating regressed melanoma from regressed lichenoid keratosis.

    Science.gov (United States)

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

    2017-04-01

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

  12. Omics Analyses of Trichoderma reesei CBS999.97 and QM6a Indicate the Relevance of Female Fertility to Carbohydrate-Active Enzyme and Transporter Levels.

    Science.gov (United States)

    Tisch, Doris; Pomraning, Kyle R; Collett, James R; Freitag, Michael; Baker, Scott E; Chen, Chia-Ling; Hsu, Paul Wei-Che; Chuang, Yu Chien; Schuster, Andre; Dattenböck, Christoph; Stappler, Eva; Sulyok, Michael; Böhmdorfer, Stefan; Oberlerchner, Josua; Wang, Ting-Fang; Schmoll, Monika

    2017-11-15

    The filamentous fungus Trichoderma reesei is found predominantly in the tropics but also in more temperate regions, such as Europe, and is widely known as a producer of large amounts of plant cell wall-degrading enzymes. We sequenced the genome of the sexually competent isolate CBS999.97, which is phenotypically different from the female sterile strain QM6a but can cross sexually with QM6a. Transcriptome data for growth on cellulose showed that entire carbohydrate-active enzyme (CAZyme) families are consistently differentially regulated between these strains. We evaluated backcrossed strains of both mating types, which acquired female fertility from CBS999.97 but maintained a mostly QM6a genetic background, and we could thereby distinguish between the effects of strain background and female fertility or mating type. We found clear regulatory differences associated with female fertility and female sterility, including regulation of CAZyme and transporter genes. Analysis of carbon source utilization, transcriptomes, and secondary metabolites in these strains revealed that only a few changes in gene regulation are consistently correlated with different mating types. Different strain backgrounds (QM6a versus CBS999.97) resulted in the most significant alterations in the transcriptomes and in carbon source utilization, with decreased growth of CBS999.97 on several amino acids (for example proline or alanine), which further correlated with the downregulation of genes involved in the respective pathways. In combination, our findings support a role of fertility-associated processes in physiology and gene regulation and are of high relevance for the use of sexual crossing in combining the characteristics of two compatible strains or quantitative trait locus (QTL) analysis. IMPORTANCE Trichoderma reesei is a filamentous fungus with a high potential for secretion of plant cell wall-degrading enzymes. We sequenced the genome of the fully fertile field isolate CBS999.97 and

  13. 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.…

  14. Better Autologistic Regression

    Directory of Open Access Journals (Sweden)

    Mark A. Wolters

    2017-11-01

    Full Text Available Autologistic regression is an important probability model for dichotomous random variables observed along with covariate information. It has been used in various fields for analyzing binary data possessing spatial or network structure. The model can be viewed as an extension of the autologistic model (also known as the Ising model, quadratic exponential binary distribution, or Boltzmann machine to include covariates. It can also be viewed as an extension of logistic regression to handle responses that are not independent. Not all authors use exactly the same form of the autologistic regression model. Variations of the model differ in two respects. First, the variable coding—the two numbers used to represent the two possible states of the variables—might differ. Common coding choices are (zero, one and (minus one, plus one. Second, the model might appear in either of two algebraic forms: a standard form, or a recently proposed centered form. Little attention has been paid to the effect of these differences, and the literature shows ambiguity about their importance. It is shown here that changes to either coding or centering in fact produce distinct, non-nested probability models. Theoretical results, numerical studies, and analysis of an ecological data set all show that the differences among the models can be large and practically significant. Understanding the nature of the differences and making appropriate modeling choices can lead to significantly improved autologistic regression analyses. The results strongly suggest that the standard model with plus/minus coding, which we call the symmetric autologistic model, is the most natural choice among the autologistic variants.

  15. Functional analyses of the skin surface of the areola mammae: comparison between healthy adult male and female subjects and between healthy individuals and patients with atopic dermatitis.

    Science.gov (United States)

    Kikuchi, K; Tagami, H; Akaraphanth, R; Aiba, S

    2011-01-01

    Although the nipple and areola of the breast constitute a unique and prominent area on the chest, so far no study has been done on the functional properties of their skin surfaces. To study the stratum corneum (SC) covering the areola using noninvasive methods. Eighteen adult healthy subjects comprising nine men and nine women and 18 age- and sex-matched patients with atopic dermatitis (AD), none of whom had visible skin lesions, participated in the study. Transepidermal water loss (TEWL), skin surface hydration and skin surface lipid levels were measured on the areola and adjacent breast skin. The size of the skin surface corneocytes of these skin regions was assessed. All the healthy subjects showed significantly higher TEWL accompanied by smaller sized corneocytes on the areola than on the adjacent breast skin. Only female subjects revealed a significantly higher skin surface hydration state together with significantly increased skin surface lipid levels on the areola than on the adjacent breast skin. These sex differences were observed even in patients with AD. Comparison between healthy individuals and the patients with AD demonstrated higher TEWL, decreased skin surface hydration state and lower skin surface lipid levels associated with smaller sized corneocytes in the areola in the patients with AD, especially in male patients. In adults, the SC barrier function and SC water-binding capacity of the areola were functionally poorer than in the adjacent skin, being covered by smaller sized corneocytes and lower amounts of skin surface lipids, especially in men and in patients with AD. © 2011 The Authors. BJD © 2011 British Association of Dermatologists 2011.

  16. Reduced Rank Regression

    DEFF Research Database (Denmark)

    Johansen, Søren

    2008-01-01

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

  17. 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

  18. Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures

    Science.gov (United States)

    Hegazy, Maha A.; Lotfy, Hayam M.; Mowaka, Shereen; Mohamed, Ekram Hany

    2016-07-01

    Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.

  19. Female Directors and Firm Performance: Evidence from UK Listed Firms

    OpenAIRE

    Pasaribu, Pananda

    2017-01-01

    The impact of female directors on firm performance has lacked consistency in the previously conducted empirical studies, which may be due to the endogeneity problem, or certain characteristics (i.e. governance, industry, competition). This study examines the relationship between female directors and firm performance by addressing those problems. This study analyses all non-financial UK listed firms during the period 2004-2012 and employs several econometric models. The regression results indi...

  20. Vanadium NMR Chemical Shifts of (Imido)vanadium(V) Dichloride Complexes with Imidazolin-2-iminato and Imidazolidin-2-iminato Ligands: Cooperation with Quantum-Chemical Calculations and Multiple Linear Regression Analyses.

    Science.gov (United States)

    Yi, Jun; Yang, Wenhong; Sun, Wen-Hua; Nomura, Kotohiro; Hada, Masahiko

    2017-11-30

    The NMR chemical shifts of vanadium ( 51 V) in (imido)vanadium(V) dichloride complexes with imidazolin-2-iminato and imidazolidin-2-iminato ligands were calculated by the density functional theory (DFT) method with GIAO. The calculated 51 V NMR chemical shifts were analyzed by the multiple linear regression (MLR) analysis (MLRA) method with a series of calculated molecular properties. Some of calculated NMR chemical shifts were incorrect using the optimized molecular geometries of the X-ray structures. After the global minimum geometries of all of the molecules were determined, the trend of the observed chemical shifts was well reproduced by the present DFT method. The MLRA method was performed to investigate the correlation between the 51 V NMR chemical shift and the natural charge, band energy gap, and Wiberg bond index of the V═N bond. The 51 V NMR chemical shifts obtained with the present MLR model were well reproduced with a correlation coefficient of 0.97.

  1. 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

  2. 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...

  3. 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...

  4. 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

  5. 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

  6. Equações de regressão para estimar valores energéticos do grão de trigo e seus subprodutos para frangos de corte, a partir de análises químicas Regression equations to evaluate the energy values of wheat grain and its by-products for broiler chickens from chemical analyses

    Directory of Open Access Journals (Sweden)

    F.M.O. Borges

    2003-12-01

    que significou pouca influência da metodologia sobre essa medida. A FDN não mostrou ser melhor preditor de EM do que a FB.One experiment was run with broiler chickens, to obtain prediction equations for metabolizable energy (ME based on feedstuffs chemical analyses, and determined ME of wheat grain and its by-products, using four different methodologies. Seven wheat grain by-products were used in five treatments: wheat grain, wheat germ, white wheat flour, dark wheat flour, wheat bran for human use, wheat bran for animal use and rough wheat bran. Based on chemical analyses of crude fiber (CF, ether extract (EE, crude protein (CP, ash (AS and starch (ST of the feeds and the determined values of apparent energy (MEA, true energy (MEV, apparent corrected energy (MEAn and true energy corrected by nitrogen balance (MEVn in five treatments, prediction equations were obtained using the stepwise procedure. CF showed the best relationship with metabolizable energy values, however, this variable alone was not enough for a good estimate of the energy values (R² below 0.80. When EE and CP were included in the equations, R² increased to 0.90 or higher in most estimates. When the equations were calculated with all treatments, the equation for MEA were less precise and R² decreased. When ME data of the traditional or force-feeding methods were used separately, the precision of the equations increases (R² higher than 0.85. For MEV and MEVn values, the best multiple linear equations included CF, EE and CP (R²>0.90, independently of using all experimental data or separating by methodology. The estimates of MEVn values showed high precision and the linear coefficients (a of the equations were similar for all treatments or methodologies. Therefore, it explains the small influence of the different methodologies on this parameter. NDF was not a better predictor of ME than CF.

  7. A Simulation Investigation of Principal Component Regression.

    Science.gov (United States)

    Allen, David E.

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

  8. Boosted beta regression.

    Directory of Open Access Journals (Sweden)

    Matthias Schmid

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

  9. Understanding logistic regression analysis.

    Science.gov (United States)

    Sperandei, Sandro

    2014-01-01

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

  10. 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

  11. 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-

  12. Multilingual speaker age recognition: regression analyses on the Lwazi corpus

    CSIR Research Space (South Africa)

    Feld, M

    2009-12-01

    Full Text Available Multilinguality represents an area of significant opportunities for automatic speech-processing systems: whereas multilingual societies are commonplace, the majority of speechprocessing systems are developed with a single language in mind. As a step...

  13. 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.

  14. Female terrorism : a review

    NARCIS (Netherlands)

    Jacques, Karen; Taylor, Paul J.

    2009-01-01

    The sharp growth in the number of publications examining female involvement in terrorism has produced a valuable but un-integrated body of knowledge spread across many disciplines. In this paper, we bring together 54 publications on female terrorism and use qualitative and quantitative analyses to

  15. Vector regression introduced

    Directory of Open Access Journals (Sweden)

    Mok Tik

    2014-06-01

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

  16. 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.

  17. Minimax Regression Quantiles

    DEFF Research Database (Denmark)

    Bache, Stefan Holst

    A new and alternative quantile regression estimator is developed and it is shown that the estimator is root n-consistent and asymptotically normal. The estimator is based on a minimax ‘deviance function’ and has asymptotically equivalent properties to the usual quantile regression estimator. It is......, however, a different and therefore new estimator. It allows for both linear- and nonlinear model specifications. A simple algorithm for computing the estimates is proposed. It seems to work quite well in practice but whether it has theoretical justification is still an open question....

  18. 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....

  19. 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...

  20. Multiple linear regression analysis

    Science.gov (United States)

    Edwards, T. R.

    1980-01-01

    Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.

  1. Bayesian logistic regression analysis

    NARCIS (Netherlands)

    Van Erp, H.R.N.; Van Gelder, P.H.A.J.M.

    2012-01-01

    In this paper we present a Bayesian logistic regression analysis. It is found that if one wishes to derive the posterior distribution of the probability of some event, then, together with the traditional Bayes Theorem and the integrating out of nuissance parameters, the Jacobian transformation is an

  2. Linear Regression Analysis

    CERN Document Server

    Seber, George A F

    2012-01-01

    Concise, mathematically clear, and comprehensive treatment of the subject.* Expanded coverage of diagnostics and methods of model fitting.* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models.* More than 200 problems throughout the book plus outline solutions for the exercises.* This revision has been extensively class-tested.

  3. Nonlinear Regression with R

    CERN Document Server

    Ritz, Christian; Parmigiani, Giovanni

    2009-01-01

    R is a rapidly evolving lingua franca of graphical display and statistical analysis of experiments from the applied sciences. This book provides a coherent treatment of nonlinear regression with R by means of examples from a diversity of applied sciences such as biology, chemistry, engineering, medicine and toxicology.

  4. Bayesian ARTMAP for regression.

    Science.gov (United States)

    Sasu, L M; Andonie, R

    2013-10-01

    Bayesian ARTMAP (BA) is a recently introduced neural architecture which uses a combination of Fuzzy ARTMAP competitive learning and Bayesian learning. Training is generally performed online, in a single-epoch. During training, BA creates input data clusters as Gaussian categories, and also infers the conditional probabilities between input patterns and categories, and between categories and classes. During prediction, BA uses Bayesian posterior probability estimation. So far, BA was used only for classification. The goal of this paper is to analyze the efficiency of BA for regression problems. Our contributions are: (i) we generalize the BA algorithm using the clustering functionality of both ART modules, and name it BA for Regression (BAR); (ii) we prove that BAR is a universal approximator with the best approximation property. In other words, BAR approximates arbitrarily well any continuous function (universal approximation) and, for every given continuous function, there is one in the set of BAR approximators situated at minimum distance (best approximation); (iii) we experimentally compare the online trained BAR with several neural models, on the following standard regression benchmarks: CPU Computer Hardware, Boston Housing, Wisconsin Breast Cancer, and Communities and Crime. Our results show that BAR is an appropriate tool for regression tasks, both for theoretical and practical reasons. Copyright © 2013 Elsevier Ltd. All rights reserved.

  5. Bounded Gaussian process regression

    DEFF Research Database (Denmark)

    Jensen, Bjørn Sand; Nielsen, Jens Brehm; Larsen, Jan

    2013-01-01

    We extend the Gaussian process (GP) framework for bounded regression by introducing two bounded likelihood functions that model the noise on the dependent variable explicitly. This is fundamentally different from the implicit noise assumption in the previously suggested warped GP framework. We...... with the proposed explicit noise-model extension....

  6. and Multinomial Logistic Regression

    African Journals Online (AJOL)

    This work presented the results of an experimental comparison of two models: Multinomial Logistic Regression (MLR) and Artificial Neural Network (ANN) for classifying students based on their academic performance. The predictive accuracy for each model was measured by their average Classification Correct Rate (CCR).

  7. Mechanisms of neuroblastoma regression

    Science.gov (United States)

    Brodeur, Garrett M.; Bagatell, Rochelle

    2014-01-01

    Recent genomic and biological studies of neuroblastoma have shed light on the dramatic heterogeneity in the clinical behaviour of this disease, which spans from spontaneous regression or differentiation in some patients, to relentless disease progression in others, despite intensive multimodality therapy. This evidence also suggests several possible mechanisms to explain the phenomena of spontaneous regression in neuroblastomas, including neurotrophin deprivation, humoral or cellular immunity, loss of telomerase activity and alterations in epigenetic regulation. A better understanding of the mechanisms of spontaneous regression might help to identify optimal therapeutic approaches for patients with these tumours. Currently, the most druggable mechanism is the delayed activation of developmentally programmed cell death regulated by the tropomyosin receptor kinase A pathway. Indeed, targeted therapy aimed at inhibiting neurotrophin receptors might be used in lieu of conventional chemotherapy or radiation in infants with biologically favourable tumours that require treatment. Alternative approaches consist of breaking immune tolerance to tumour antigens or activating neurotrophin receptor pathways to induce neuronal differentiation. These approaches are likely to be most effective against biologically favourable tumours, but they might also provide insights into treatment of biologically unfavourable tumours. We describe the different mechanisms of spontaneous neuroblastoma regression and the consequent therapeutic approaches. PMID:25331179

  8. 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.

  9. Subset selection in regression

    CERN Document Server

    Miller, Alan

    2002-01-01

    Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade. Thoroughly revised to reflect progress in theory, methods, and computing power, the second edition promises to continue that tradition. The author has thoroughly updated each chapter, incorporated new material on recent developments, and included more examples and references. New in the Second Edition:A separate chapter on Bayesian methodsComplete revision of the chapter on estimationA major example from the field of near infrared spectroscopyMore emphasis on cross-validationGreater focus on bootstrappingStochastic algorithms for finding good subsets from large numbers of predictors when an exhaustive search is not feasible Software available on the Internet for implementing many of the algorithms presentedMore examplesSubset Selection in Regression, Second Edition remains dedicated to the techniques for fitting...

  10. Regression in organizational leadership.

    Science.gov (United States)

    Kernberg, O F

    1979-02-01

    The choice of good leaders is a major task for all organizations. Inforamtion regarding the prospective administrator's personality should complement questions regarding his previous experience, his general conceptual skills, his technical knowledge, and the specific skills in the area for which he is being selected. The growing psychoanalytic knowledge about the crucial importance of internal, in contrast to external, object relations, and about the mutual relationships of regression in individuals and in groups, constitutes an important practical tool for the selection of leaders.

  11. Classification and regression trees

    CERN Document Server

    Breiman, Leo; Olshen, Richard A; Stone, Charles J

    1984-01-01

    The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

  12. Comparison of Classical Linear Regression and Orthogonal Regression According to the Sum of Squares Perpendicular Distances

    OpenAIRE

    KELEŞ, Taliha; ALTUN, Murat

    2016-01-01

    Regression analysis is a statistical technique for investigating and modeling the relationship between variables. The purpose of this study was the trivial presentation of the equation for orthogonal regression (OR) and the comparison of classical linear regression (CLR) and OR techniques with respect to the sum of squared perpendicular distances. For that purpose, the analyses were shown by an example. It was found that the sum of squared perpendicular distances of OR is smaller. Thus, it wa...

  13. Logistic regression models

    CERN Document Server

    Hilbe, Joseph M

    2009-01-01

    This book really does cover everything you ever wanted to know about logistic regression … with updates available on the author's website. Hilbe, a former national athletics champion, philosopher, and expert in astronomy, is a master at explaining statistical concepts and methods. Readers familiar with his other expository work will know what to expect-great clarity.The book provides considerable detail about all facets of logistic regression. No step of an argument is omitted so that the book will meet the needs of the reader who likes to see everything spelt out, while a person familiar with some of the topics has the option to skip "obvious" sections. The material has been thoroughly road-tested through classroom and web-based teaching. … The focus is on helping the reader to learn and understand logistic regression. The audience is not just students meeting the topic for the first time, but also experienced users. I believe the book really does meet the author's goal … .-Annette J. Dobson, Biometric...

  14. Reproductive efficiency of captive Chinese- and Indian-origin rhesus macaque (Macaca mulatta) females

    Science.gov (United States)

    Kubisch, H. Michael; Falkenstein, Kathrine P.; Deroche, Chelsea B.; Franke, Donald E.

    2011-01-01

    Reproductive and survival records (n = 2,913) from 313 Chinese-origin and 365 Indian-derived rhesus macaques at the Tulane National Primate Research Center spanning 3 generations were studied. Least-squares analysis of variance procedures were used to compare reproductive and infant survival traits while proportional hazards regression procedures were used to study female age at death, number of infants born per female and time from last birth to death. Chinese females were older at first parturition than Indian-females because they were older when placed with males, but the two subspecies had similar first and lifetime post-partum birth intervals. Females that gave birth to stillborn infants had shorter first post-partum birth intervals than females giving birth to live infants. Post-partum birth intervals decreased in females from 3 to 12 years of age but then increased again with advancing age. Chinese infants had a greater survival rate than Indian infants at 30 d, 6 mo and 1yr of age. Five hundred and forty-three females (80.01 %) had uncensored, or true records for age at death, number of infants born per female, and time from the birth until death whereas 135 females (19.91 %) had censored records for these traits. Low and high uncensored observations for age at death were 3 and 26 years of age for Chinese and 3 and 23 years of age for Indian females. Uncensored number of infants born per female ranged from 1 to 15 for Chinese females and 1 to 18 for Indian females. Each of these traits was significantly influenced by the origin × generation interaction in the proportional hazards regression analyses, indicating that probabilities associated with age at death, number of infants born per female and time from last birth to death for Chinese and Indian females did not rank the same across generations. PMID:22512021

  15. Steganalysis using logistic regression

    Science.gov (United States)

    Lubenko, Ivans; Ker, Andrew D.

    2011-02-01

    We advocate Logistic Regression (LR) as an alternative to the Support Vector Machine (SVM) classifiers commonly used in steganalysis. LR offers more information than traditional SVM methods - it estimates class probabilities as well as providing a simple classification - and can be adapted more easily and efficiently for multiclass problems. Like SVM, LR can be kernelised for nonlinear classification, and it shows comparable classification accuracy to SVM methods. This work is a case study, comparing accuracy and speed of SVM and LR classifiers in detection of LSB Matching and other related spatial-domain image steganography, through the state-of-art 686-dimensional SPAM feature set, in three image sets.

  16. SEPARATION PHENOMENA LOGISTIC REGRESSION

    Directory of Open Access Journals (Sweden)

    Ikaro Daniel de Carvalho Barreto

    2014-03-01

    Full Text Available This paper proposes an application of concepts about the maximum likelihood estimation of the binomial logistic regression model to the separation phenomena. It generates bias in the estimation and provides different interpretations of the estimates on the different statistical tests (Wald, Likelihood Ratio and Score and provides different estimates on the different iterative methods (Newton-Raphson and Fisher Score. It also presents an example that demonstrates the direct implications for the validation of the model and validation of variables, the implications for estimates of odds ratios and confidence intervals, generated from the Wald statistics. Furthermore, we present, briefly, the Firth correction to circumvent the phenomena of separation.

  17. 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......-product we obtain fast access to the baseline hazards (compared to survival::basehaz()) and predictions of survival probabilities, their confidence intervals and confidence bands. Confidence intervals and confidence bands are based on point-wise asymptotic expansions of the corresponding statistical...

  18. Adaptive metric kernel regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    2000-01-01

    Kernel smoothing is a widely used non-parametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this contribution, we propose an algorithm that adapts the input metric used in multivariate...... regression by minimising a cross-validation estimate of the generalisation error. This allows to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms...

  19. Adaptive Metric Kernel Regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    1998-01-01

    Kernel smoothing is a widely used nonparametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this paper, we propose an algorithm that adapts the input metric used in multivariate regression...... by minimising a cross-validation estimate of the generalisation error. This allows one to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the standard...

  20. Aid and growth regressions

    DEFF Research Database (Denmark)

    Hansen, Henrik; Tarp, Finn

    2001-01-01

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

  1. 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).

  2. Cancer burden trends in Umbria region using a joinpoint regression

    Directory of Open Access Journals (Sweden)

    Giuseppe Michele Masanotti

    2015-09-01

    Full Text Available INTRODUCTION. The analysis of the epidemiological data on cancer is an important tool to control and evaluate the outcomes of primary and secondary prevention, the effectiveness of health care and, in general, all cancer control activities. MATERIALS AND METHODS. The aim of the this paper is to analyze the cancer mortality in the Umbria region from 1978 to 2009 and incidence from 1994-2008. Sex and site-specific trends for standardized rates were analyzed by "joinpoint regression", using the surveillance epidemiology and end results (SEER software. RESULTS. Applying the jointpoint analyses by sex and cancer site, to incidence spanning from 1994 to 2008 and mortality from 1978 to 2009 for all sites, both in males and females, a significant joinpoint for mortality was found; moreover the trend shape was similar and the joinpoint years were very close. In males standardized rate significantly increased up to 1989 by 1.23% per year and significantly decreased thereafter by -1.31%; among females the mortality rate increased in average of 0.78% (not significant per year till 1988 and afterward significantly decreased by -0.92% per year. Incidence rate showed different trends among sexes. In males was practically constant over the period studied (not significant increase 0.14% per year, in females significantly increased by 1.49% per year up to 2001 and afterward slowly decreased (-0.71% n.s. estimated annual percent change − EAPC. CONCLUSIONS. For all sites combined trends for mortality decreased since late '80s, both in males and females; such behaviour is in line with national and European Union data. This work shows that, even compared to health systems that invest more resources, the Umbria public health system achieved good health outcomes.

  3. Measurement Error in Education and Growth Regressions

    NARCIS (Netherlands)

    Portela, M.; Teulings, C.N.; Alessie, R.

    The perpetual inventory method used for the construction of education data per country leads to systematic measurement error. This paper analyses the effect of this measurement error on GDP regressions. There is a systematic difference in the education level between census data and observations

  4. Measurement error in education and growth regressions

    NARCIS (Netherlands)

    Portela, Miguel; Teulings, Coen; Alessie, R.

    2004-01-01

    The perpetual inventory method used for the construction of education data per country leads to systematic measurement error. This paper analyses the effect of this measurement error on GDP regressions. There is a systematic difference in the education level between census data and observations

  5. Panel data specifications in nonparametric kernel regression

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    parametric panel data estimators to analyse the production technology of Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we...

  6. Grades, Gender, and Encouragement: A Regression Discontinuity Analysis

    Science.gov (United States)

    Owen, Ann L.

    2010-01-01

    The author employs a regression discontinuity design to provide direct evidence on the effects of grades earned in economics principles classes on the decision to major in economics and finds a differential effect for male and female students. Specifically, for female students, receiving an A for a final grade in the first economics class is…

  7. Canonical variate regression.

    Science.gov (United States)

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

    2016-07-01

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

  8. Eating Disorders Among a Community-based Sample of Chilean Female Adolescents

    Science.gov (United States)

    Granillo, M. Teresa; Grogan-Kaylor, Andrew; Delva, Jorge; Castillo, Marcela

    2010-01-01

    The purpose of this study was to explore the prevalence and correlates of eating disorders among a community-based sample of female Chilean adolescents. Data were collected through structured interviews with 420 female adolescents residing in Santiago, Chile. Approximately 4% of the sample reported ever being diagnosed with an eating disorder. Multivariate logistic regression analyses revealed that those with higher symptoms of anxiety and who had tried cigarettes were significantly more likely to have been diagnosed with an eating disorder. Findings indicate that Chilean female adolescents are at risk of eating disorders and that eating disorders, albeit maladaptive, may be a means to cope with negative affect, specifically anxiety. PMID:22121329

  9. 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)

  10. Recursive Algorithm For Linear Regression

    Science.gov (United States)

    Varanasi, S. V.

    1988-01-01

    Order of model determined easily. Linear-regression algorithhm includes recursive equations for coefficients of model of increased order. Algorithm eliminates duplicative calculations, facilitates search for minimum order of linear-regression model fitting set of data satisfactory.

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

    Science.gov (United States)

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

    2011-01-01

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

  12. Female Directors and Firm Performance: Evidence from UK Listed Firms

    Directory of Open Access Journals (Sweden)

    Pananda Pasaribu

    2017-08-01

    Full Text Available The impact of female directors on firm performance has lacked consistency in the previously conducted empirical studies, which may be due to the endogeneity problem, or certain characteristics (i.e. governance, industry, competition. This study examines the relationship between female directors and firm performance by addressing those problems. This study analyses all non-financial UK listed firms during the period 2004-2012 and employs several econometric models. The regression results indicate that there is little evidence that female directors have a positive and strong relationship with firm performance. But, further analysis reports that the UK’s small listed firms experience a positive significant effect, because small firms do not suffer from the problem of over-monitoring and they have more flexibility in composing their boards of directors.

  13. Combining Alphas via Bounded Regression

    Directory of Open Access Journals (Sweden)

    Zura Kakushadze

    2015-11-01

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

  14. Regression in autistic spectrum disorders.

    Science.gov (United States)

    Stefanatos, Gerry A

    2008-12-01

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

  15. 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.

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

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

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

  17. Online Female Escort Advertisements

    Directory of Open Access Journals (Sweden)

    James D. Griffith

    2016-05-01

    Full Text Available Female escorts represent an occupational group that charges a fee for sex, which can be regarded as an extreme form of short-term mating. The present study examined if the fees charged by escorts are related to traits typically associated with female short-term mate value. A total of 2,925 advertisements for female escorts offering sexual services in the United States were examined, as a customized software program was used to download all the advertisements from an online escort directory. The advertisement content was coded, and relationships between advertised physical characteristics and the hourly rate charged by female escorts were examined. The analyses showed that higher fees were associated with female escorts who advertised a waist-to-hip ratio near 0.7, lower weight and body mass index, younger age, and photographic displays of breast and buttocks nudity. The findings provide evidence that evolutionarily relevant traits associated with female short-term mate value are systematically related to fees charged for sexual services.

  18. Female offenders

    NARCIS (Netherlands)

    Vivienne de Vogel; Marijke Louppen

    2017-01-01

    Although girls and women represent only a minority of the forensic mental health and prison populations, studies worldwide suggest that there has been a steady increase in the number of females being convicted for committing offenses, especially violent offenses. In this chapter, an overview will

  19. Linear regression in astronomy. II

    Science.gov (United States)

    Feigelson, Eric D.; Babu, Gutti J.

    1992-01-01

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

  20. 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....

  1. 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.

  2. Quantile regression theory and applications

    CERN Document Server

    Davino, Cristina; Vistocco, Domenico

    2013-01-01

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

  3. Female infertility

    International Nuclear Information System (INIS)

    Hall, D.A.; Yoder, I.

    1984-01-01

    Infertility, defined as 1 year of unprotected intercourse without conception, is becoming of increasingly important medical concern. Fertility in both the male and the female is at its peak in the twenties. Many couples today have postponed marriage and/or childbearing into their 30s until careers are established, but at that point fertility may be diminished. The current epidemic of venereal disease has been associated with an increasing incidence of tubal scarring. In addition, the use of intrauterine devices (IUDs) and birth control pills for contraception have let to later problems with pelvic inflammatory disease (PID) and ovulation disturbances. The problem of infertility intensifies as the number of babies available for adoption decreases. Therefore, it is estimated that approximately 10-20% of couples will eventually seek medical attention for an infertility-related problem. Fortunately, marked improvements in the results of tubal surgery are concurrently occurring secondary to refinements in microsurgical techniques, and many medical alternatives to induce ovulation are being developed. The male factor causes infertility in 30-40 % of couples, and the female factor is responsible in approximately 50% of couples. No cause is found in 10-20% of couples. This chapter discusses the role of coordinated imaging in the diagnosis and therapy of infertility in the female

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

    Directory of Open Access Journals (Sweden)

    M. Guns

    2012-06-01

    Full Text Available Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

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

    Science.gov (United States)

    Guns, M.; Vanacker, V.

    2012-06-01

    Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

  6. Intense-personal celebrity worship and body image: evidence of a link among female adolescents.

    Science.gov (United States)

    Maltby, John; Giles, David C; Barber, Louise; McCutcheon, Lynn E

    2005-02-01

    The aim of the present study was to examine the relationship between celebrity worship and body image within the theoretical perspective of intense para-social relationships with celebrities. Correlation and multiple regression analyses were used to examine the relationships between celebrity worship and body image. Three samples, 229 (102 males and 127 females) adolescents, 183 (88 males and 95 females) full-time university undergraduate students, and 289 (126 males and 163 females) adults were administered an amended version of the Celebrity Attitude Scale, the Attention to Body Shape Scale, and the Body Shape Questionnaire-Revised. Significant relationships were found between attitudes toward celebrities and body image only among female adolescents. Multiple regression analyses suggested that Intense-personal celebrity worship accounted for unique variance in scores in body image. Findings suggest that in female adolescents, there is an interaction between Intense-personal celebrity worship and body image between the ages of 14 and 16 years, and some tentative evidence has been found to suggest that this relationship disappears at the onset of adulthood, 17 to 20 years. Results are consistent with those authors who stress the importance of the formation of para-social relationships with media figures, and suggest that para-social relationships with celebrities perceived as having a good body shape may lead to a poor body image in female adolescents.

  7. Panel Smooth Transition Regression Models

    DEFF Research Database (Denmark)

    González, Andrés; Terasvirta, Timo; Dijk, Dick van

    We introduce the panel smooth transition regression model. This new model is intended for characterizing heterogeneous panels, allowing the regression coefficients to vary both across individuals and over time. Specifically, heterogeneity is allowed for by assuming that these coefficients are bou...

  8. Testing discontinuities in nonparametric regression

    KAUST Repository

    Dai, Wenlin

    2017-01-19

    In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

  9. Testing discontinuities in nonparametric regression

    KAUST Repository

    Dai, Wenlin; Zhou, Yuejin; Tong, Tiejun

    2017-01-01

    In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

  10. Logistic Regression: Concept and Application

    Science.gov (United States)

    Cokluk, Omay

    2010-01-01

    The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…

  11. Fungible weights in logistic regression.

    Science.gov (United States)

    Jones, Jeff A; Waller, Niels G

    2016-06-01

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

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

    International Nuclear Information System (INIS)

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

    2007-01-01

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

  13. 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)

  14. 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...

  15. Augmenting Data with Published Results in Bayesian Linear Regression

    Science.gov (United States)

    de Leeuw, Christiaan; Klugkist, Irene

    2012-01-01

    In most research, linear regression analyses are performed without taking into account published results (i.e., reported summary statistics) of similar previous studies. Although the prior density in Bayesian linear regression could accommodate such prior knowledge, formal models for doing so are absent from the literature. The goal of this…

  16. Predicting Word Reading Ability: A Quantile Regression Study

    Science.gov (United States)

    McIlraith, Autumn L.

    2018-01-01

    Predictors of early word reading are well established. However, it is unclear if these predictors hold for readers across a range of word reading abilities. This study used quantile regression to investigate predictive relationships at different points in the distribution of word reading. Quantile regression analyses used preschool and…

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

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

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

  18. 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.

  19. Breast cancer risk in female survivors of Hodgkin's lymphoma

    DEFF Research Database (Denmark)

    De Bruin, Marie L; Sparidans, Judith; van't Veer, Mars B

    2009-01-01

    PURPOSE: We assessed the long-term risk of breast cancer (BC) after treatment for Hodgkin's lymphoma (HL). We focused on the volume of breast tissue exposed to radiation and the influence of gonadotoxic chemotherapy (CT). PATIENTS AND METHODS: We performed a cohort study among 1,122 female 5-year...... survivors treated for HL before the age of 51 years between 1965 and 1995. We compared the incidence of BC with that in the general population. To assess the risk according to radiation volume and hormone factors, we performed multivariate Cox regression analyses. RESULTS: After a median follow-up of 17...

  20. Female condoms.

    Science.gov (United States)

    Bounds, W

    1997-06-01

    Early versions of a female condom were available in the 1920s and 1960s, but they were little used and soon forgotten. It took the arrival of AIDS, and the urgent need for a wider range of female-controlled barrier techniques, to rekindle scientific interest in this method. In the 1980s, three groups in Europe and the USA began development of new female condom designs, comprising 'Femidom (Reality)', the 'Bikini Condom', and 'Women's Choice'. Apart from differences in their physical design, Femidom differs from the others in that it is made of a polyurethane membrane, which has several advantages over latex. Of the three, Femidom is the most advanced in terms of development and clinical testing, and it is the only one to have reached the marketing stage. Laboratory studies and clinical trials suggest that its contraceptive efficacy is similar to that documented for the male condom, though a direct comparison is not possible because no comparative clinical trials have, as yet, been undertaken. Reported 'typical-use' pregnancy rates range from 12.4 to 22.2% at 6 months of use in the USA and Latin America, respectively, while a study in the UK observed a rate of 15% at 12 months. As with all barrier methods, most failures appear to be associated with poor compliance or incorrect use. 'Perfect-use' pregnancy rates were substantially lower, indicating that Femidom can be very effective, if used consistently and correctly. Evidence for Femidom's effectiveness to protect against transmission of sexual disease-causing organisms, including HIV, is still very limited and based largely on laboratory studies. Whilst, in theory, the condom should confer reliable protection, its efficacy in clinical use will depend upon correct and consistent use and upon the product's ability to maintain an effective physical barrier throughout penetrative intercourse. In this respect, the results of recent and ongoing clinical studies are expected with much interest. How valuable Femidom will

  1. Female children with incarcerated adult family members at risk for life-long neurological decline

    OpenAIRE

    Brewer-Smyth, Kathleen; Pohlig, Ryan T.; Bucurescu, Gabriel

    2016-01-01

    A secondary analysis of data from adult female prison inmates in the mid-Atlantic United States defined relationships between having incarcerated adult family members during childhood and neurological outcomes. Of 135 inmates, 99(73%) had one or more incarcerated adult family members during childhood. Regression analyses revealed that having incarcerated adult family members was related to greater frequency and severity of childhood abuse and higher incidence of neurological deficits in adult...

  2. Abstract Expression Grammar Symbolic Regression

    Science.gov (United States)

    Korns, Michael F.

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

  3. Quantile Regression With Measurement Error

    KAUST Repository

    Wei, Ying; Carroll, Raymond J.

    2009-01-01

    . The finite sample performance of the proposed method is investigated in a simulation study, and compared to the standard regression calibration approach. Finally, we apply our methodology to part of the National Collaborative Perinatal Project growth data, a

  4. From Rasch scores to regression

    DEFF Research Database (Denmark)

    Christensen, Karl Bang

    2006-01-01

    Rasch models provide a framework for measurement and modelling latent variables. Having measured a latent variable in a population a comparison of groups will often be of interest. For this purpose the use of observed raw scores will often be inadequate because these lack interval scale propertie....... This paper compares two approaches to group comparison: linear regression models using estimated person locations as outcome variables and latent regression models based on the distribution of the score....

  5. Testing Heteroscedasticity in Robust Regression

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2011-01-01

    Roč. 1, č. 4 (2011), s. 25-28 ISSN 2045-3345 Grant - others:GA ČR(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust regression * heteroscedasticity * regression quantiles * diagnostics Subject RIV: BB - Applied Statistics , Operational Research http://www.researchjournals.co.uk/documents/Vol4/06%20Kalina.pdf

  6. Regression methods for medical research

    CERN Document Server

    Tai, Bee Choo

    2013-01-01

    Regression Methods for Medical Research provides medical researchers with the skills they need to critically read and interpret research using more advanced statistical methods. The statistical requirements of interpreting and publishing in medical journals, together with rapid changes in science and technology, increasingly demands an understanding of more complex and sophisticated analytic procedures.The text explains the application of statistical models to a wide variety of practical medical investigative studies and clinical trials. Regression methods are used to appropriately answer the

  7. Forecasting with Dynamic Regression Models

    CERN Document Server

    Pankratz, Alan

    2012-01-01

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

  8. [Gender differences in career motivation: female doctors' ambitions benefit from family friendly work environment].

    Science.gov (United States)

    Pas, B R; Lagro-Janssen, A L M; Doorewaard, J A C M; Eisinga, R N; Peters, C P

    2008-10-04

    To determine gender differences in career motivation and the effect of a family friendly work environment. Cross-sectional pilot investigation. A web survey among male and female doctors (n = 107; 72 women and 35 men) in different specialties, including surgical, internal medicine and general practitioners, was used to gather information on different dimensions of career motivation and perceptions of the family friendliness of the work environment. Differences were analysed by means of t-tests and regression analyses. Male doctors had higher scores on career identity and on career planning than female doctors. However, male and female doctors did not differ in their willingness to achieve top positions. Female doctors were more determined concerning their career goals than their male counterparts. The family friendliness of the work environment had an overall positive effect on career motivation for both male and female doctors. However, a family friendly work environment had a negative effect on the career identity of male doctors. For male and female doctors alike, support to achieve career goals and elimination of career barriers lead to increased career identity. Male and female doctors differed in certain dimensions of career motivation. Offering support for career goals and taking away career barriers leads to a higher career motivation than offering a family friendly work environment.

  9. 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.

  10. Male depression in females?

    Science.gov (United States)

    Möller-Leimkühler, Anne Maria; Yücel, Mete

    2010-02-01

    Scientific evidence for a male-typed depression ("male depression") is still limited, but mainly supports this concept with respect to single externalizing symptoms or symptom clusters. In particular, studies on non-clinical populations including males and females are lacking. The present study aims at assessing general well-being, the risk and the symptoms of male depression dependent on biological sex and gender-role orientation on instrumental (masculine) and expressive (feminine) personality traits in an unselected community sample of males and females. Students (518 males, 500 females) of the Ludwig-Maximilians-University of Munich, Germany, were asked to participate in a "stress study" and complete the following self-report questionnaires: the WHO-5 Well-being Index [Bech, P., 1998. Quality of Life in the Psychiatric Patient. Mosby-Wolfe, London], the Gotland Scale for Male Depression [Walinder, J., Rutz, W., 2001. Male depression and suicide. International Clinical Psychopharmacology 16 (suppl 2), 21-24] and the German Extended Personal Attribute Questionnaire [Runge, T.E., Frey, D., Gollwitzer, P.M., et al., 1981. Masculine (instrumental) and feminine (expressive) traits. A comparison between students in the United States and West Germany. Journal of Cross-Cultural Psychology 12, 142-162]. General well-being of the students was significantly lower compared to population norms. Contrary to expectations, female students had a greater risk of male depression than male students (28.9% vs. 22.4%; p<0.05). Overall, prototypic depressive symptoms as well as externalizing symptoms were more pronounced in females. In the subgroup of those at risk for male depression, biological sex and kind of symptoms were unrelated. Principal component analyses revealed a similar symptom structure for males and females. Low scores on masculinity/instrumentality significantly predicted higher risk of male depression, independent of biological sex. The study sample is not

  11. Producing The New Regressive Left

    DEFF Research Database (Denmark)

    Crone, Christine

    members, this thesis investigates a growing political trend and ideological discourse in the Arab world that I have called The New Regressive Left. On the premise that a media outlet can function as a forum for ideology production, the thesis argues that an analysis of this material can help to trace...... the contexture of The New Regressive Left. If the first part of the thesis lays out the theoretical approach and draws the contextual framework, through an exploration of the surrounding Arab media-and ideoscapes, the second part is an analytical investigation of the discourse that permeates the programmes aired...... becomes clear from the analytical chapters is the emergence of the new cross-ideological alliance of The New Regressive Left. This emerging coalition between Shia Muslims, religious minorities, parts of the Arab Left, secular cultural producers, and the remnants of the political,strategic resistance...

  12. A Matlab program for stepwise regression

    Directory of Open Access Journals (Sweden)

    Yanhong Qi

    2016-03-01

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

  13. Correlation and simple linear regression.

    Science.gov (United States)

    Zou, Kelly H; Tuncali, Kemal; Silverman, Stuart G

    2003-06-01

    In this tutorial article, the concepts of correlation and regression are reviewed and demonstrated. The authors review and compare two correlation coefficients, the Pearson correlation coefficient and the Spearman rho, for measuring linear and nonlinear relationships between two continuous variables. In the case of measuring the linear relationship between a predictor and an outcome variable, simple linear regression analysis is conducted. These statistical concepts are illustrated by using a data set from published literature to assess a computed tomography-guided interventional technique. These statistical methods are important for exploring the relationships between variables and can be applied to many radiologic studies.

  14. Regression filter for signal resolution

    International Nuclear Information System (INIS)

    Matthes, W.

    1975-01-01

    The problem considered is that of resolving a measured pulse height spectrum of a material mixture, e.g. gamma ray spectrum, Raman spectrum, into a weighed sum of the spectra of the individual constituents. The model on which the analytical formulation is based is described. The problem reduces to that of a multiple linear regression. A stepwise linear regression procedure was constructed. The efficiency of this method was then tested by transforming the procedure in a computer programme which was used to unfold test spectra obtained by mixing some spectra, from a library of arbitrary chosen spectra, and adding a noise component. (U.K.)

  15. Nonparametric Mixture of Regression Models.

    Science.gov (United States)

    Huang, Mian; Li, Runze; Wang, Shaoli

    2013-07-01

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

  16. Cactus: An Introduction to Regression

    Science.gov (United States)

    Hyde, Hartley

    2008-01-01

    When the author first used "VisiCalc," the author thought it a very useful tool when he had the formulas. But how could he design a spreadsheet if there was no known formula for the quantities he was trying to predict? A few months later, the author relates he learned to use multiple linear regression software and suddenly it all clicked into…

  17. 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

  18. Survival analysis II: Cox regression

    NARCIS (Netherlands)

    Stel, Vianda S.; Dekker, Friedo W.; Tripepi, Giovanni; Zoccali, Carmine; Jager, Kitty J.

    2011-01-01

    In contrast to the Kaplan-Meier method, Cox proportional hazards regression can provide an effect estimate by quantifying the difference in survival between patient groups and can adjust for confounding effects of other variables. The purpose of this article is to explain the basic concepts of the

  19. Kernel regression with functional response

    OpenAIRE

    Ferraty, Frédéric; Laksaci, Ali; Tadj, Amel; Vieu, Philippe

    2011-01-01

    We consider kernel regression estimate when both the response variable and the explanatory one are functional. The rates of uniform almost complete convergence are stated as function of the small ball probability of the predictor and as function of the entropy of the set on which uniformity is obtained.

  20. [Nickel levels in female dermatological patients].

    Science.gov (United States)

    Schwegler, U; Twardella, D; Fedorov, M; Darsow, U; Schaller, K-H; Habernegg, R; Behrendt, H; Fromme, H

    2009-07-01

    Nickel levels in urine were determined among 163 female dermatological patients aged 18 to 46 years. Data on life-style factors were collected in parallel via a questionnaire. Urinary nickel excretion was in the normal range of the German female population (0.2-46.1 microg Ni/g creatinine). The 95th percentile (3.9 microg Ni/l urine) exceeded the German reference value (3.0 microg Ni/l urine). In the multivariate regression analyses we found a statistically significant increase of ln-transformed nickel levels with increase in age and in women using dietary supplements. The following variables were not associated with Nickel urine levels: suffering from nickel eczema, smoking, drinking stagnated water, eating foods with high nickel contents and using nickel-containing kitchen utensils as, for example, an electric kettle with an open heater coil. We conclude that personal urinary levels should be assessed with simultaneous consideration of habits and life-style factors. A German national survery would be useful. Those patients who experience the exacerbation of their eczema in cases of oral provocation, for example, by a high nickel diet should be aware of potential sources of nickel, such as supplements.

  1. Linear regression and the normality assumption.

    Science.gov (United States)

    Schmidt, Amand F; Finan, Chris

    2017-12-16

    Researchers often perform arbitrary outcome transformations to fulfill the normality assumption of a linear regression model. This commentary explains and illustrates that in large data settings, such transformations are often unnecessary, and worse may bias model estimates. Linear regression assumptions are illustrated using simulated data and an empirical example on the relation between time since type 2 diabetes diagnosis and glycated hemoglobin levels. Simulation results were evaluated on coverage; i.e., the number of times the 95% confidence interval included the true slope coefficient. Although outcome transformations bias point estimates, violations of the normality assumption in linear regression analyses do not. The normality assumption is necessary to unbiasedly estimate standard errors, and hence confidence intervals and P-values. However, in large sample sizes (e.g., where the number of observations per variable is >10) violations of this normality assumption often do not noticeably impact results. Contrary to this, assumptions on, the parametric model, absence of extreme observations, homoscedasticity, and independency of the errors, remain influential even in large sample size settings. Given that modern healthcare research typically includes thousands of subjects focusing on the normality assumption is often unnecessary, does not guarantee valid results, and worse may bias estimates due to the practice of outcome transformations. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Spontaneous regression of intracranial malignant lymphoma

    International Nuclear Information System (INIS)

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

    1988-01-01

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

  3. Floral function: effects of traits on pollinators, male and female pollination success, and female fitness across three species of milkweeds (Asclepias).

    Science.gov (United States)

    La Rosa, Raffica J; Conner, Jeffrey K

    2017-01-01

    Central questions in plant reproductive ecology are whether the functions of floral traits in hermaphrodites create conflict between sexes that could slow evolution, and whether individual floral traits function in pollinator attraction, efficiency, or both. We studied how floral traits affect pollinator visitation and efficiency, and how they affect male and female function and female fitness within and across three Asclepias species that differ in floral morphology. Using separate multiple regressions, we regressed pollen removal, deposition, and fruit number onto six floral traits. We also used path analyses integrating these variables with pollinator visitation data for two of the species to further explore floral function and its effects on fruit production. Most traits affected male pollination success only, and these effects often differed between species. The exception was increased slit length, which increased pollinia insertion in two of the species. There were no interspecific differences in the effects of the traits on female pollination success. All traits except horn reach affected pollination efficiency in at least one species, and horn reach and two hood dimensions were the only traits to affect pollinator attraction, but in just one species. Traits tended to function in only one sex, and more traits affected function through pollinator efficiency than through attraction. There was no significant link between female pollination success and female fitness in any of the three species; this pattern is consistent with fruit production not being limited by pollen deposition. © 2017 Botanical Society of America.

  4. Adverse reproductive outcomes among female veterinarians

    International Nuclear Information System (INIS)

    Schenker, M.B.; Samuels, S.J.; Green, R.S.; Wiggins, P.

    1990-01-01

    Because female veterinarians are exposed to several known reproductive hazards, the authors conducted a reproductive survey of all female graduates of a US veterinary school (n = 537) and law school (comparison group, n = 794). Analysis was confined to pregnancies completed after the second year of professional school and from 1966 to 1986. Based on one randomly chosen eligible pregnancy per woman (veterinarians, n = 176; lawyers, n = 229), spontaneous abortion rates, adjusted for elective abortions, were 13.3% for the veterinarians and 15.1% for the lawyers; these did not differ significantly. A Cox life table regression model controlling for age, smoking, alcohol use, and prior spontaneous abortion also showed no significant difference in spontaneous abortion rates between the two populations. Using all pregnancies, veterinarians who reported performing five or more radiographic examinations per week had a marginally elevated risk of spontaneous abortion, but the statistical significance disappeared when analysis was limited to one random pregnancy per woman. For one random eligible birth per woman, the mean birth weight did not differ significantly between the veterinarians and lawyers, even after controlling for possible confounders in regression analyses. A higher rate of reportable birth defects was observed among the veterinarians than among the lawyers (relative risk = 4.2, 95% confidence interval 1.2-15.1), but this unexpected result must be considered hypothesis-generating. The authors did not find an overall increased risk for spontaneous abortion or low birth weight infants among veterinarians compared with lawyers, but veterinarians who reported performing five or more radiographic examinations per week may have been at increased risk for spontaneous abortion

  5. Pregnancy outcomes in female hairdressers.

    Science.gov (United States)

    Ronda, Elena; Moen, Bente E; García, Ana M; Sánchez-Paya, José; Baste, Valborg

    2010-12-01

    The hairdressing occupation may entail exposure to a wide range of chemical products, psychosocial and physical stress. All these factors may affect the health of a pregnant hairdresser and her offspring. Our aim was to analyse whether employment in this profession is associated with adverse reproductive effects. Female hairdressers working in the 248 hairdressing salons in Alicante (Spain), who became pregnant for the first time after 1990 were included (n = 94). The incidence of spontaneous abortions, number of children born and their birth weight and preterm delivery among hairdressers was compared with a control group of shop assistants and office workers (n = 138). Information was collected through personal interviews at their work place. A structured questionnaire was used gathering information concerning exposure variables including the use of chemical products, ventilation at the salons, work-related stress and hours of standing work. In addition, socio-demographic factors and smoking information were obtained. Crude and adjusted relative risks (RR) and 95% confidence intervals (95%CI) were calculated using logbinomial regression. Hairdressers showed a non-significant increased risk of spontaneous abortions (RR = 1.6, 95%CI 0.9-2.7). There were no differences in preterm delivery and birth weight of the children born of mothers in the two groups. Among hairdressers, the RR of spontaneous abortion among those with high perceived work-related stress was 2.4 (95%CI: 0.2-28.3) relative to those with low or normal perceived stress. A slightly increased risk of spontaneous abortion among hairdressers was found, mainly associated with perceived work-related stress. Observed results deserve further research.

  6. Quantile Regression With Measurement Error

    KAUST Repository

    Wei, Ying

    2009-08-27

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

  7. Multivariate and semiparametric kernel regression

    OpenAIRE

    Härdle, Wolfgang; Müller, Marlene

    1997-01-01

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

  8. Regression algorithm for emotion detection

    OpenAIRE

    Berthelon , Franck; Sander , Peter

    2013-01-01

    International audience; We present here two components of a computational system for emotion detection. PEMs (Personalized Emotion Maps) store links between bodily expressions and emotion values, and are individually calibrated to capture each person's emotion profile. They are an implementation based on aspects of Scherer's theoretical complex system model of emotion~\\cite{scherer00, scherer09}. We also present a regression algorithm that determines a person's emotional feeling from sensor m...

  9. 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

  10. Polylinear regression analysis in radiochemistry

    International Nuclear Information System (INIS)

    Kopyrin, A.A.; Terent'eva, T.N.; Khramov, N.N.

    1995-01-01

    A number of radiochemical problems have been formulated in the framework of polylinear regression analysis, which permits the use of conventional mathematical methods for their solution. The authors have considered features of the use of polylinear regression analysis for estimating the contributions of various sources to the atmospheric pollution, for studying irradiated nuclear fuel, for estimating concentrations from spectral data, for measuring neutron fields of a nuclear reactor, for estimating crystal lattice parameters from X-ray diffraction patterns, for interpreting data of X-ray fluorescence analysis, for estimating complex formation constants, and for analyzing results of radiometric measurements. The problem of estimating the target parameters can be incorrect at certain properties of the system under study. The authors showed the possibility of regularization by adding a fictitious set of data open-quotes obtainedclose quotes from the orthogonal design. To estimate only a part of the parameters under consideration, the authors used incomplete rank models. In this case, it is necessary to take into account the possibility of confounding estimates. An algorithm for evaluating the degree of confounding is presented which is realized using standard software or regression analysis

  11. Gaussian Process Regression Model in Spatial Logistic Regression

    Science.gov (United States)

    Sofro, A.; Oktaviarina, A.

    2018-01-01

    Spatial analysis has developed very quickly in the last decade. One of the favorite approaches is based on the neighbourhood of the region. Unfortunately, there are some limitations such as difficulty in prediction. Therefore, we offer Gaussian process regression (GPR) to accommodate the issue. In this paper, we will focus on spatial modeling with GPR for binomial data with logit link function. The performance of the model will be investigated. We will discuss the inference of how to estimate the parameters and hyper-parameters and to predict as well. Furthermore, simulation studies will be explained in the last section.

  12. Tutorial on Using Regression Models with Count Outcomes Using R

    Directory of Open Access Journals (Sweden)

    A. Alexander Beaujean

    2016-02-01

    Full Text Available Education researchers often study count variables, such as times a student reached a goal, discipline referrals, and absences. Most researchers that study these variables use typical regression methods (i.e., ordinary least-squares either with or without transforming the count variables. In either case, using typical regression for count data can produce parameter estimates that are biased, thus diminishing any inferences made from such data. As count-variable regression models are seldom taught in training programs, we present a tutorial to help educational researchers use such methods in their own research. We demonstrate analyzing and interpreting count data using Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial regression models. The count regression methods are introduced through an example using the number of times students skipped class. The data for this example are freely available and the R syntax used run the example analyses are included in the Appendix.

  13. Spontaneous regression of pulmonary bullae

    International Nuclear Information System (INIS)

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

    2002-01-01

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

  14. Quantum algorithm for linear regression

    Science.gov (United States)

    Wang, Guoming

    2017-07-01

    We present a quantum algorithm for fitting a linear regression model to a given data set using the least-squares approach. Differently from previous algorithms which yield a quantum state encoding the optimal parameters, our algorithm outputs these numbers in the classical form. So by running it once, one completely determines the fitted model and then can use it to make predictions on new data at little cost. Moreover, our algorithm works in the standard oracle model, and can handle data sets with nonsparse design matrices. It runs in time poly( log2(N ) ,d ,κ ,1 /ɛ ) , where N is the size of the data set, d is the number of adjustable parameters, κ is the condition number of the design matrix, and ɛ is the desired precision in the output. We also show that the polynomial dependence on d and κ is necessary. Thus, our algorithm cannot be significantly improved. Furthermore, we also give a quantum algorithm that estimates the quality of the least-squares fit (without computing its parameters explicitly). This algorithm runs faster than the one for finding this fit, and can be used to check whether the given data set qualifies for linear regression in the first place.

  15. Interpretation of commonly used statistical regression models.

    Science.gov (United States)

    Kasza, Jessica; Wolfe, Rory

    2014-01-01

    A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

  16. 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/.

  17. Weight-related concerns and diet behaviors among urban young females: A cross-sectional study

    Directory of Open Access Journals (Sweden)

    Shabnam Omidvar

    2016-01-01

    Full Text Available Background: Females are more likely than males to perceive themselves as too heavy, this has been explained in terms of the equation of “female beauty with extreme thinness.” Therefore, females are in general prone to develop unhealthy behaviors for weight management. Wrong weight control behaviors have significant health consequences. Objectives: To investigate the body weight concerns, body satisfaction, and weight control behaviors among young females and their association with age and socioeconomic status (SES. Materials and Methods: A cross-sectional study conducted in urban areas from a major city in South India. About 650 healthy unmarried females aged 15–25 years formed the study population. Self-reporting questionnaires were used to obtain relevant data. The categorical data were analyzed using Chi-square, correlation, and regression analyses by SPSS version 16. Results: Most overweight and obese subjects perceived themselves as overweight. Adolescents were more likely to report themselves as overweight. The perceived weight, body satisfaction, and weight control behaviors are influenced by weight status and age of the subjects. However, SES of the participants did not exhibit effect of others' opinion about their weight and body satisfaction as well as weight management behaviors. Conclusion: The high prevalence of weight-related concerns suggests that all females should be reached with appropriate information and interventions. Healthy weight control practices need to be explicitly promoted and unhealthy practices discouraged. Young females need special attention toward weight management.

  18. [Female erotic dreams and female seed in ancient Greek medicine].

    Science.gov (United States)

    Andò, Valeria

    2009-01-01

    This paper analyses passages of the Hippocratic Corpus, of Aristotle and Galen about oneirogmòs, spermatic emission during sleep, referring specifically to women. Into the Hippocratic texts there is only one gynaecological case among many cases about males: for them this nocturnal emission is symptom of dangerous illness and De genitura gives a causal explanation of such phaenomenon. Instead, in Aristotle and Galen erotic dream is evidence for or against emission of female seed and female contribution to generation. As the argument ofHistoria animalium book X shows clear theoretical differences from that of De generatione animalium, the topic of erotic dream also concerns issues of authenticity.

  19. Normal Female Reproductive Anatomy

    Science.gov (United States)

    ... historical Searches are case-insensitive Reproductive System, Female, Anatomy Add to My Pictures View /Download : Small: 720x756 ... Large: 3000x3150 View Download Title: Reproductive System, Female, Anatomy Description: Anatomy of the female reproductive system; drawing ...

  20. On Weighted Support Vector Regression

    DEFF Research Database (Denmark)

    Han, Xixuan; Clemmensen, Line Katrine Harder

    2014-01-01

    We propose a new type of weighted support vector regression (SVR), motivated by modeling local dependencies in time and space in prediction of house prices. The classic weights of the weighted SVR are added to the slack variables in the objective function (OF‐weights). This procedure directly...... shrinks the coefficient of each observation in the estimated functions; thus, it is widely used for minimizing influence of outliers. We propose to additionally add weights to the slack variables in the constraints (CF‐weights) and call the combination of weights the doubly weighted SVR. We illustrate...... the differences and similarities of the two types of weights by demonstrating the connection between the Least Absolute Shrinkage and Selection Operator (LASSO) and the SVR. We show that an SVR problem can be transformed to a LASSO problem plus a linear constraint and a box constraint. We demonstrate...

  1. The relationship between psychosocial maturity and assertiveness in males and females.

    Science.gov (United States)

    Goldman, J A; Olczak, P V

    1981-02-01

    The relationship between psychosocial maturity (psychological health) and assertiveness was investigated in a sample of United States college males and females. Results revealed a moderately high positive relationship between psychosocial maturity (PSM) and self-reported assertiveness on the Rathus and Galassi scales for both sexes. This relationship was slightly stronger (in terms of variance accounted for) for males than females, significant differences being obtained for Intimacy on the Rathus scale and PSM and Intimacy on the Galassi scale. Multiple regression analyses revealed that the personality components most consistently accounting for major portions of the variance in predicting male assertiveness scores on both the Rathus Assertiveness Schedule and the College Self-Expression Scale were Intimacy and Initiative, while in predicting female assertiveness, only Initiative was involved. The findings were related to previous research, recent work on the androgyny construct (instrumental vs. expressive behaviors), and exhortations for increased cooperation between schools of psychotherapy to establish it as a more unified discipline.

  2. Female self-employment and children

    NARCIS (Netherlands)

    Noseleit, Florian

    2014-01-01

    Several analyses report a positive correlation between fertility and female self-employment; however, scholars disagree about the direction of this relationship. Knowing about the causal relationship is important because the relevant mechanisms and possible implications differ tremendously. This

  3. Credit Scoring Problem Based on Regression Analysis

    OpenAIRE

    Khassawneh, Bashar Suhil Jad Allah

    2014-01-01

    ABSTRACT: This thesis provides an explanatory introduction to the regression models of data mining and contains basic definitions of key terms in the linear, multiple and logistic regression models. Meanwhile, the aim of this study is to illustrate fitting models for the credit scoring problem using simple linear, multiple linear and logistic regression models and also to analyze the found model functions by statistical tools. Keywords: Data mining, linear regression, logistic regression....

  4. Variable selection and model choice in geoadditive regression models.

    Science.gov (United States)

    Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard

    2009-06-01

    Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.

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

    DEFF Research Database (Denmark)

    Merlo, Juan; Wagner, Philippe; Ghith, Nermin

    2016-01-01

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

  6. Interpreting Multiple Linear Regression: A Guidebook of Variable Importance

    Science.gov (United States)

    Nathans, Laura L.; Oswald, Frederick L.; Nimon, Kim

    2012-01-01

    Multiple regression (MR) analyses are commonly employed in social science fields. It is also common for interpretation of results to typically reflect overreliance on beta weights, often resulting in very limited interpretations of variable importance. It appears that few researchers employ other methods to obtain a fuller understanding of what…

  7. Regularized Label Relaxation Linear Regression.

    Science.gov (United States)

    Fang, Xiaozhao; Xu, Yong; Li, Xuelong; Lai, Zhihui; Wong, Wai Keung; Fang, Bingwu

    2018-04-01

    Linear regression (LR) and some of its variants have been widely used for classification problems. Most of these methods assume that during the learning phase, the training samples can be exactly transformed into a strict binary label matrix, which has too little freedom to fit the labels adequately. To address this problem, in this paper, we propose a novel regularized label relaxation LR method, which has the following notable characteristics. First, the proposed method relaxes the strict binary label matrix into a slack variable matrix by introducing a nonnegative label relaxation matrix into LR, which provides more freedom to fit the labels and simultaneously enlarges the margins between different classes as much as possible. Second, the proposed method constructs the class compactness graph based on manifold learning and uses it as the regularization item to avoid the problem of overfitting. The class compactness graph is used to ensure that the samples sharing the same labels can be kept close after they are transformed. Two different algorithms, which are, respectively, based on -norm and -norm loss functions are devised. These two algorithms have compact closed-form solutions in each iteration so that they are easily implemented. Extensive experiments show that these two algorithms outperform the state-of-the-art algorithms in terms of the classification accuracy and running time.

  8. Estimating the exceedance probability of rain rate by logistic regression

    Science.gov (United States)

    Chiu, Long S.; Kedem, Benjamin

    1990-01-01

    Recent studies have shown that the fraction of an area with rain intensity above a fixed threshold is highly correlated with the area-averaged rain rate. To estimate the fractional rainy area, a logistic regression model, which estimates the conditional probability that rain rate over an area exceeds a fixed threshold given the values of related covariates, is developed. The problem of dependency in the data in the estimation procedure is bypassed by the method of partial likelihood. Analyses of simulated scanning multichannel microwave radiometer and observed electrically scanning microwave radiometer data during the Global Atlantic Tropical Experiment period show that the use of logistic regression in pixel classification is superior to multiple regression in predicting whether rain rate at each pixel exceeds a given threshold, even in the presence of noisy data. The potential of the logistic regression technique in satellite rain rate estimation is discussed.

  9. Use of probabilistic weights to enhance linear regression myoelectric control.

    Science.gov (United States)

    Smith, Lauren H; Kuiken, Todd A; Hargrove, Levi J

    2015-12-01

    Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts' law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p linear regression control. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

  10. Independent contrasts and PGLS regression estimators are equivalent.

    Science.gov (United States)

    Blomberg, Simon P; Lefevre, James G; Wells, Jessie A; Waterhouse, Mary

    2012-05-01

    We prove that the slope parameter of the ordinary least squares regression of phylogenetically independent contrasts (PICs) conducted through the origin is identical to the slope parameter of the method of generalized least squares (GLSs) regression under a Brownian motion model of evolution. This equivalence has several implications: 1. Understanding the structure of the linear model for GLS regression provides insight into when and why phylogeny is important in comparative studies. 2. The limitations of the PIC regression analysis are the same as the limitations of the GLS model. In particular, phylogenetic covariance applies only to the response variable in the regression and the explanatory variable should be regarded as fixed. Calculation of PICs for explanatory variables should be treated as a mathematical idiosyncrasy of the PIC regression algorithm. 3. Since the GLS estimator is the best linear unbiased estimator (BLUE), the slope parameter estimated using PICs is also BLUE. 4. If the slope is estimated using different branch lengths for the explanatory and response variables in the PIC algorithm, the estimator is no longer the BLUE, so this is not recommended. Finally, we discuss whether or not and how to accommodate phylogenetic covariance in regression analyses, particularly in relation to the problem of phylogenetic uncertainty. This discussion is from both frequentist and Bayesian perspectives.

  11. Somatic symptoms among US adolescent females: associations with sexual and physical violence exposure.

    Science.gov (United States)

    Halpern, Carolyn Tucker; Tucker, Christine M; Bengtson, Angela; Kupper, Lawrence L; McLean, Samuel A; Martin, Sandra L

    2013-12-01

    The objective of this study is to examine the association between physical and sexual violence exposure and somatic symptoms among female adolescents. We studied a nationally representative sample of 8,531 females, aged 11-21 years, who participated in the 1994-1995 Wave I of the National Longitudinal Study of Adolescent Health (Add Health). Female adolescents were asked how often they had experienced 16 specific somatic symptoms during the past 12 months. Two summary categorical measures were constructed based on tertiles of the distributions for the entire female sample: (a) total number of different types of symptoms experienced, and (b) number of frequent (once a week or more often) different symptoms experienced. Groups were mutually exclusive. We examined associations between adolescents' violence exposure and somatic symptoms using multinomial logistic regression analyses. About 5 % of adolescent females reported both sexual and non-sexual violence, 3 % reported sexual violence only, 36 % reported non-sexual violence only, and 57 % reported no violence. Adolescents who experienced both sexual and non-sexual violence were the most likely to report many different symptoms and to experience very frequent or chronic symptoms. Likelihood of high symptomatology was next highest among adolescents who experienced sexual violence only, followed by females who experienced non-sexual violence only. Findings support an exposure-response association between violence exposure and somatic symptoms, suggesting that symptoms can be markers of victimization. Treating symptoms alone, without addressing the potential violence experienced, may not adequately improve adolescents' somatic complaints and well-being.

  12. 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.

  13. Comparing parametric and nonparametric regression methods for panel data

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    We investigate and compare the suitability of parametric and non-parametric stochastic regression methods for analysing production technologies and the optimal firm size. Our theoretical analysis shows that the most commonly used functional forms in empirical production analysis, Cobb......-Douglas and Translog, are unsuitable for analysing the optimal firm size. We show that the Translog functional form implies an implausible linear relationship between the (logarithmic) firm size and the elasticity of scale, where the slope is artificially related to the substitutability between the inputs....... The practical applicability of the parametric and non-parametric regression methods is scrutinised and compared by an empirical example: we analyse the production technology and investigate the optimal size of Polish crop farms based on a firm-level balanced panel data set. A nonparametric specification test...

  14. Male and Female Perception of Physical Attractiveness

    Directory of Open Access Journals (Sweden)

    Ray Garza

    2016-02-01

    Full Text Available Waist-to-hip ratio (WHR and breast size are morphological traits that are associated with female attractiveness. Previous studies using line drawings of women have shown that men across cultures rate low WHRs (0.6 and 0.7 as most attractive. In this study, we used additional viewing measurements (i.e., first fixation duration and visual regressions to measure visual attention and record how long participants first focused on the female body and whether they regressed back to an area of interest. Additionally, we manipulated skin tone to determine whether they preferred light- or dark-skinned women. In two eye tracking experiments, participants rated the attractiveness of female nude images varying in WHR (0.5–0.9, breast size, and skin tone. We measured first fixation duration, gaze duration, and total time. The overall results of both studies revealed that visual attention fell mostly on the face, the breasts, and the midriff of the female body, supporting the evolutionary view that reproductively relevant regions of the female body are important to female attractiveness. Because the stimuli varied in skin tone and the participants were mainly Hispanic of Mexican American descent, the findings from these studies also support a preference for low WHRs and reproductively relevant regions of the female body.

  15. Emotional control in Chinese female cancer survivors.

    Science.gov (United States)

    Ho, Rainbow T H; Chan, Cecilia L W; Ho, Samuel M Y

    2004-11-01

    Chinese persons are not known as strong in expressing emotions, especially negative ones. However, being diagnosed with cancer and going through treatment can be an emotionally traumatic experience and cancer patients are supposed to have a stronger need to express these negative feelings. The control of expression of negative emotions such as anger, anxiety and depression in Chinese female cancer survivors (n=139) was examined in the present study using the Chinese version of the Courtauld Emotional Control Scale (CECS). The reliability, internal consistency and validity of the Chinese CECS were comparable to the original English scale. Correlation analyses suggested that cancer survivors with higher emotional control tended to have higher stress, anxiety and depression levels and to adopt negative coping with cancer. Regression analysis showed that emotional control would positively predict stress level even after the effect of depressed mood was under control. Further investigations are suggested in order to elucidate the causal relationships and specific cultural factors affecting emotional control in Chinese cancer survivors and, most importantly, its effect on health outcomes. Copyright (c) 2004 John Wiley & Sons, Ltd.

  16. Queering gender in contemporary female Bildung narrative

    Directory of Open Access Journals (Sweden)

    Šnircová Soňa

    2015-09-01

    Full Text Available The paper explores, in the context of feminist discussions about the Bildungsroman, a contemporary British novel that offers shocking images of female coming of age at the turn of the millennium. Queering gender and introducing male elements into the heroine’s process of maturation, the analysed novel appears to raise questions about the continuous relevance of the feminist distinction between male and female version of the genre. The paper however argues that although significantly rewriting both female Bildung and pornographic narratives, Helen Walsh’s Brass can still be read as a variation of the female Bildungsroman and an example of its contemporary developments.

  17. Cortical activation during mental rotation in male-to-female and female-to-male transsexuals under hormonal treatment.

    Science.gov (United States)

    Carrillo, Beatriz; Gómez-Gil, Esther; Rametti, Giuseppina; Junque, Carme; Gomez, Angel; Karadi, Kazmer; Segovia, Santiago; Guillamon, Antonio

    2010-09-01

    There is strong evidence of sex differences in mental rotation tasks. Transsexualism is an extreme gender identity disorder in which individuals seek cross-gender treatment to change their sex. The aim of our study was to investigate if male-to-female (MF) and female-to-male (FM) transsexuals receiving cross-sex hormonal treatment have different patterns of cortical activation during a three-dimensional (3D) mental rotation task. An fMRI study was performed using a 3-T scan in a sample of 18 MF and 19 FM under chronic cross-sex hormonal treatment. Twenty-three males and 19 females served as controls. The general pattern of cerebral activation seen while visualizing the rotated and non-rotated figures was similar for all four groups showing strong occipito-parieto-frontal brain activation. However, compared to control males, the activation of MF transsexuals during the task was lower in the superior parietal lobe. Compared to control females, MF transsexuals showed higher activation in orbital and right dorsolateral prefrontal regions and lower activation in the left prefrontal gyrus. FM transsexuals did not differ from either the MF transsexual or control groups. Regression analyses between cerebral activation and the number of months of hormonal treatment showed a significant negative correlation in parietal, occipital and temporal regions in the MF transsexuals. No significant correlations with time were seen in the FM transsexuals. In conclusion, although we did not find a specific pattern of cerebral activation in the FM transsexuals, we have identified a specific pattern of cerebral activation during a mental 3D rotation task in MF transsexuals under cross-sex hormonal treatment that differed from control males in the parietal region and from control females in the orbital prefrontal region. The hypoactivation in MF transsexuals in the parietal region could be due to the hormonal treatment or could reflect a priori cerebral differences between MF transsexual

  18. Unbalanced Regressions and the Predictive Equation

    DEFF Research Database (Denmark)

    Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo

    Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness in the theoreti......Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness...

  19. Semiparametric regression during 2003–2007

    KAUST Repository

    Ruppert, David; Wand, M.P.; Carroll, Raymond J.

    2009-01-01

    Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.

  20. Gaussian process regression analysis for functional data

    CERN Document Server

    Shi, Jian Qing

    2011-01-01

    Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed covariates of functional and scalar variables.Covering the basics of Gaussian process regression, the first several chapters discuss functional data analysis, theoretical aspects based on the asymptotic properties of Gaussian process regression models, and new methodological developments for high dime

  1. Cholecystokinin in plasma predicts cardiovascular mortality in elderly females

    DEFF Research Database (Denmark)

    Gøtze, Jens P.; Rehfeld, Jens F; Alehagen, Urban

    2016-01-01

    BACKGROUND: Cholecystokinin (CCK) and gastrin are related gastrointestinal hormones with documented cardiovascular effects of exogenous administration. It is unknown whether measurement of endogenous CCK or gastrin in plasma contains information regarding cardiovascular mortality. METHODS......: Mortality risk was evaluated using Cox proportional hazard regression and Kaplan-Meier analyses. Elderly patients in a primary care setting with symptoms of cardiac disease, i.e. shortness of breath, peripheral edema, and/or fatigue, were evaluated (n=470). Primary care patients were followed for 13years...... information was obtained from 4th quartile gastrin concentrations on 5-year cardiovascular mortality risk. CONCLUSIONS: CCK in plasma is an independent marker of cardiovascular mortality in elderly female patients. The study thus introduces measurement of plasma CCK in gender-specific cardiovascular risk...

  2. Regression Analysis by Example. 5th Edition

    Science.gov (United States)

    Chatterjee, Samprit; Hadi, Ali S.

    2012-01-01

    Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. "Regression Analysis by Example, Fifth Edition" has been expanded and thoroughly…

  3. Standards for Standardized Logistic Regression Coefficients

    Science.gov (United States)

    Menard, Scott

    2011-01-01

    Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…

  4. A Seemingly Unrelated Poisson Regression Model

    OpenAIRE

    King, Gary

    1989-01-01

    This article introduces a new estimator for the analysis of two contemporaneously correlated endogenous event count variables. This seemingly unrelated Poisson regression model (SUPREME) estimator combines the efficiencies created by single equation Poisson regression model estimators and insights from "seemingly unrelated" linear regression models.

  5. Predictors of insubordinate aggression among captive female rhesus macaques.

    Science.gov (United States)

    Seil, Shannon K; Hannibal, Darcy L; Beisner, Brianne A; McCowan, Brenda

    2017-11-01

    Cercopithicine primates tend to have nepotistic hierarchies characterized by predictable, kinship-based dominance. Although aggression is typically directed down the hierarchy, insubordinate aggression does occur. Insubordination is important to understand because it can precipitate social upheaval and undermine group stability; however, the factors underlying it are not well understood. We test whether key social and demographic variables predict insubordination among captive female rhesus macaques. To identify factors influencing insubordination, multivariate analyses of 10,821 dyadic conflicts among rhesus macaque females were conducted, using data from six captive groups. A segmented regression analysis was used to identify dyads with insubordination. Negative binomial regression analyses and an information theoretic approach were used to assess predictors of insubordination among dyads. In the best models, weight difference (w = 1.0; IRR = 0.930), age (dominant: w = 1.0, IRR = 0.681; subordinate: w = 1.0, IRR = 1.069), the subordinate's total number of allies (w = 0.727, IRR = 1.060) or non-kin allies (w = 0.273, IRR = 1.165), the interaction of the dominant's kin allies and weight difference (w = 0.938, IRR = 1.046), violation of youngest ascendancy (w = 1.0; IRR = 2.727), and the subordinate's maternal support (w = 1.0; IRR = 2.928), are important predictors of insubordination. These results show that both intrinsic and social factors influence insubordinate behavior. This adds to evidence of the importance of intrinsic factors and flexibility in a social structure thought to be rigid and predetermined by external factors. Further, because insubordination can precipitate social overthrow, determining predictors of insubordination will shed light on mechanisms underlying stability in nepotistic societies. © 2017 Wiley Periodicals, Inc.

  6. Female children with incarcerated adult family members at risk for lifelong neurological decline.

    Science.gov (United States)

    Brewer-Smyth, Kathleen; Pohlig, Ryan T; Bucurescu, Gabriel

    2016-07-01

    A secondary analysis of data from adult female prison inmates in the mid-Atlantic United States defined relationships between having incarcerated adult family members during childhood and neurological outcomes. Of 135 inmates, 99 (60%) had one or more incarcerated adult family members during childhood. Regression analyses revealed that having incarcerated adult family members was related to greater frequency and severity of childhood abuse and higher incidence of neurological deficits in adulthood, especially related to traumatic brain injuries, compared to those without incarcerated adult family members. Along with being role models, adult family members impact the neurological health of children throughout their life-span.

  7. Female children with incarcerated adult family members at risk for life-long neurological decline

    Science.gov (United States)

    Brewer-Smyth, Kathleen; Pohlig, Ryan T.; Bucurescu, Gabriel

    2016-01-01

    A secondary analysis of data from adult female prison inmates in the mid-Atlantic United States defined relationships between having incarcerated adult family members during childhood and neurological outcomes. Of 135 inmates, 99(73%) had one or more incarcerated adult family members during childhood. Regression analyses revealed that having incarcerated adult family members was related to greater frequency and severity of childhood abuse and higher incidence of neurological deficits in adulthood, especially related to traumatic brain injuries, compared to those without incarcerated adult family members. Along with being role models, adult family members impact the neurological health of children throughout their lifespan. PMID:26788781

  8. FEMALE SOCIAL ENTREPRENEURSHIP AND SOCIO-CULTURAL CONTEXT: AN INTERNATIONAL ANALYSIS

    Directory of Open Access Journals (Sweden)

    David Urbano Pulido

    2014-12-01

    Full Text Available In this article we analyse the socio-cultural factors that influence the likelihood of women becoming social entrepreneurs, using institutional economics. Binary logistic regression has been applied as the statistical method to test the hypotheses proposed, using data (40 countries and 56,875 individuals from the World Value Survey (WVS and the World Bank (WB. The main findings of the study reaffirm the relevance of socio-cultural factors to social entrepreneurship. Particularly, we have found that altruistic attitudes and being a member of a social organization are the most relevant socio-cultural factors for social female entrepreneurship.

  9. PARAMETRIC AND NON PARAMETRIC (MARS: MULTIVARIATE ADDITIVE REGRESSION SPLINES) LOGISTIC REGRESSIONS FOR PREDICTION OF A DICHOTOMOUS RESPONSE VARIABLE WITH AN EXAMPLE FOR PRESENCE/ABSENCE OF AMPHIBIANS

    Science.gov (United States)

    The purpose of this report is to provide a reference manual that could be used by investigators for making informed use of logistic regression using two methods (standard logistic regression and MARS). The details for analyses of relationships between a dependent binary response ...

  10. Regression with Sparse Approximations of Data

    DEFF Research Database (Denmark)

    Noorzad, Pardis; Sturm, Bob L.

    2012-01-01

    We propose sparse approximation weighted regression (SPARROW), a method for local estimation of the regression function that uses sparse approximation with a dictionary of measurements. SPARROW estimates the regression function at a point with a linear combination of a few regressands selected...... by a sparse approximation of the point in terms of the regressors. We show SPARROW can be considered a variant of \\(k\\)-nearest neighbors regression (\\(k\\)-NNR), and more generally, local polynomial kernel regression. Unlike \\(k\\)-NNR, however, SPARROW can adapt the number of regressors to use based...

  11. Spontaneous regression of a congenital melanocytic nevus

    Directory of Open Access Journals (Sweden)

    Amiya Kumar Nath

    2011-01-01

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

  12. Self catheterization - female

    Science.gov (United States)

    ... female Images Bladder catheterization, female References Davis JE, Silverman MA. Urologic procedures. In: Roberts JR, ed. Roberts ... provided by VeriMed Healthcare Network. Also reviewed by David Zieve, MD, MHA, Medical Director, Brenda Conaway, Editorial ...

  13. The Use of Nonparametric Kernel Regression Methods in Econometric Production Analysis

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard

    and nonparametric estimations of production functions in order to evaluate the optimal firm size. The second paper discusses the use of parametric and nonparametric regression methods to estimate panel data regression models. The third paper analyses production risk, price uncertainty, and farmers' risk preferences...... within a nonparametric panel data regression framework. The fourth paper analyses the technical efficiency of dairy farms with environmental output using nonparametric kernel regression in a semiparametric stochastic frontier analysis. The results provided in this PhD thesis show that nonparametric......This PhD thesis addresses one of the fundamental problems in applied econometric analysis, namely the econometric estimation of regression functions. The conventional approach to regression analysis is the parametric approach, which requires the researcher to specify the form of the regression...

  14. Female reproductive disorders

    DEFF Research Database (Denmark)

    Crain, D Andrew; Janssen, Sarah J; Edwards, Thea M

    2008-01-01

    To evaluate the possible role of endocrine-disrupting compounds (EDCs) on female reproductive disorders emphasizing developmental plasticity and the complexity of endocrine-dependent ontogeny of reproductive organs. Declining conception rates and the high incidence of female reproductive...... disruptions warrant evaluation of the impact of EDCs on female reproductive health....

  15. Analyses of developmental rate isomorphy in ectotherms: Introducing the dirichlet regression

    Czech Academy of Sciences Publication Activity Database

    Boukal S., David; Ditrich, Tomáš; Kutcherov, D.; Sroka, Pavel; Dudová, Pavla; Papáček, M.

    2015-01-01

    Roč. 10, č. 6 (2015), e0129341 E-ISSN 1932-6203 R&D Projects: GA ČR GAP505/10/0096 Grant - others:European Fund(CZ) PERG04-GA-2008-239543; GA JU(CZ) 145/2013/P Institutional support: RVO:60077344 Keywords : ectotherms Subject RIV: ED - Physiology Impact factor: 3.057, year: 2015 http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0129341

  16. The benefits of using quantile regression for analysing the effect of weeds on organic winter wheat

    NARCIS (Netherlands)

    Casagrande, M.; Makowski, D.; Jeuffroy, M.H.; Valantin-Morison, M.; David, C.

    2010-01-01

    P>In organic farming, weeds are one of the threats that limit crop yield. An early prediction of weed effect on yield loss and the size of late weed populations could help farmers and advisors to improve weed management. Numerous studies predicting the effect of weeds on yield have already been

  17. Quantitative Research Methods in Chaos and Complexity: From Probability to Post Hoc Regression Analyses

    Science.gov (United States)

    Gilstrap, Donald L.

    2013-01-01

    In addition to qualitative methods presented in chaos and complexity theories in educational research, this article addresses quantitative methods that may show potential for future research studies. Although much in the social and behavioral sciences literature has focused on computer simulations, this article explores current chaos and…

  18. Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression

    DEFF Research Database (Denmark)

    Scott, Neil W.; Fayers, Peter M.; Aaronson, Neil K.

    2010-01-01

    Differential item functioning (DIF) methods can be used to determine whether different subgroups respond differently to particular items within a health-related quality of life (HRQoL) subscale, after allowing for overall subgroup differences in that scale. This article reviews issues that arise...

  19. Female reproductive disorders

    DEFF Research Database (Denmark)

    Crain, D Andrew; Janssen, Sarah J; Edwards, Thea M

    2008-01-01

    To evaluate the possible role of endocrine-disrupting compounds (EDCs) on female reproductive disorders emphasizing developmental plasticity and the complexity of endocrine-dependent ontogeny of reproductive organs. Declining conception rates and the high incidence of female reproductive disrupti......To evaluate the possible role of endocrine-disrupting compounds (EDCs) on female reproductive disorders emphasizing developmental plasticity and the complexity of endocrine-dependent ontogeny of reproductive organs. Declining conception rates and the high incidence of female reproductive...... disruptions warrant evaluation of the impact of EDCs on female reproductive health....

  20. Female Surgeons as Counter Stereotype: The Impact of Gender Perceptions on Trainee Evaluations of Physician Faculty.

    Science.gov (United States)

    Fassiotto, Magali; Li, Jie; Maldonado, Yvonne; Kothary, Nishita

    2018-02-02

    Similar to women in Science, Technology, Engineering and Mathematics disciplines, women in medicine are subject to negative stereotyping when they do not adhere to their sex-role expectations. These biases may vary by specialty, largely dependent on the gender's representation in that specialty. Thus, females in male-dominated surgical specialties are especially at risk of stereotype threat. Herein, we present the role of gender expectations using trainee evaluations of physician faculty at a single academic center, over a 5-year period (2010-2014). Using Graduate Medical Education evaluation data of physician faculty from MedHub, we examined the differences in evaluation scores for male and female physicians within specialties that have traditionally had low female representation (e.g., surgical fields) compared to those with average or high female representation (e.g., pediatrics). Stanford Medicine residents and fellows' MedHub ratings of their physician faculty from 2010 to 2014. A total of 3648 evaluations across 1066 physician faculty. Overall, female physicians received lower median scores than their male counterparts across all specialties. When using regression analyses controlling for race, age, rank, and specialty-specific characteristics, the negative effect persists only for female physicians in specialties with low female representation. This finding suggests that female physicians in traditionally male-dominated specialties may face different criteria based on sex-role expectations when being evaluated by trainees. As trainee evaluations play an important role in career advancement decisions, dictate perceptions of quality within academic medical centers and affect overall job satisfaction, we propose that these differences in evaluations based merely on gender stereotypes could account, in part, for the narrowing pipeline of women promoted to higher ranks in academic medicine. Copyright © 2018 Association of Program Directors in Surgery. Published

  1. Intermediate and advanced topics in multilevel logistic regression analysis.

    Science.gov (United States)

    Austin, Peter C; Merlo, Juan

    2017-09-10

    Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within-cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population-average effect of covariates measured at the subject and cluster level, in contrast to the within-cluster or cluster-specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster-level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

  2. Applied regression analysis a research tool

    CERN Document Server

    Pantula, Sastry; Dickey, David

    1998-01-01

    Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool. Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to...

  3. Occupational factors and reproductive outcomes among a cohort of female veterinarians.

    Science.gov (United States)

    Wilkins, J R; Steele, L L

    1998-07-01

    To estimate absolute and relative risks of preterm delivery (PTD) and small-for-gestational-age (SGA) births among a cohort of female veterinarians in relation to selected occupational factors, including clinical practice type (CPT). Retrospective cohort survey. 2,997 female graduates from US veterinary colleges between 1970 and 1980. Relevant health and occupational data were collected through a self-administered mail questionnaire with telephone follow-up of nonrespondents. Absolute and relative risks of PTD and SGA births were estimated in relation to maternal CPT at the time of conception and exposure to 13 occupational factors. Attempts were made to control confounding by use of multiple logistic regression analyses. Absolute and relative risks of PTD were highest for veterinarians employed in exclusively equine clinical practice. Although several increased, none of the CPT-specific relative risk estimates were significantly different from the null value of 1. Exposure-specific analyses indicated that occupational involvement with solvents among exclusively small animal practitioners was associated with the highest relative risk of PTD. A small number of SGA births limited information that could be obtained from these analyses. Overall absolute risks of PTD and SGA births among cohort members were much lower in comparison with the general female population. Given the large number of women currently practicing and entering the profession of veterinary medicine, clinical tasks associated with potential reproductive hazards should be approached with heightened awareness and increased caution, especially activities that may involve exposure to solvents.

  4. Analysis of Setting Efficacy in Young Male and Female Volleyball Players.

    Science.gov (United States)

    González-Silva, Jara; Domínguez, Alberto Moreno; Fernández-Echeverría, Carmen; Rabaz, Fernando Claver; Arroyo, M Perla Moreno

    2016-12-01

    The main objective of this study was to analyse the variables that predicted setting efficacy in complex I (KI) in volleyball, in formative categories and depending on gender. The study sample was comprised of 5842 game actions carried out by the 16 male category and the 18 female category teams that participated in the Under-16 Spanish Championship. The dependent variable was setting efficacy. The independent variables were grouped into: serve variables (a serve zone, the type of serve, striking technique, an in-game role of the server and serve direction), reception variables (a reception zone, a receiver player and reception efficacy) and setting variables (a setter's position, a setting zone, the type of a set, setting technique, a set's area and tempo of a set). Multinomial logistic regression showed that the best predictive variables of setting efficacy, both in female and male categories, were reception efficacy, setting technique and tempo of a set. In the male category, the jump serve was the greatest predictor of setting efficacy, while in the female category, it was the set's area. Therefore, in the male category, it was not only the preceding action that affected setting efficacy, but also the serve. On the contrary, in the female category, only variables of the action itself and of the previous action, reception, affected setting efficacy. The results obtained in the present study should be taken into account in the training process of both male and female volleyball players in formative stages.

  5. Analysis of Setting Efficacy in Young Male and Female Volleyball Players

    Directory of Open Access Journals (Sweden)

    González-Silva Jara

    2016-12-01

    Full Text Available The main objective of this study was to analyse the variables that predicted setting efficacy in complex I (KI in volleyball, in formative categories and depending on gender. The study sample was comprised of 5842 game actions carried out by the 16 male category and the 18 female category teams that participated in the Under-16 Spanish Championship. The dependent variable was setting efficacy. The independent variables were grouped into: serve variables (a serve zone, the type of serve, striking technique, an in-game role of the server and serve direction, reception variables (a reception zone, a receiver player and reception efficacy and setting variables (a setter‘s position, a setting zone, the type of a set, setting technique, a set’s area and tempo of a set. Multinomial logistic regression showed that the best predictive variables of setting efficacy, both in female and male categories, were reception efficacy, setting technique and tempo of a set. In the male category, the jump serve was the greatest predictor of setting efficacy, while in the female category, it was the set’s area. Therefore, in the male category, it was not only the preceding action that affected setting efficacy, but also the serve. On the contrary, in the female category, only variables of the action itself and of the previous action, reception, affected setting efficacy. The results obtained in the present study should be taken into account in the training process of both male and female volleyball players in formative stages.

  6. Comparative analysis of female physicists in the physical sciences: Motivation and background variables

    Science.gov (United States)

    Dabney, Katherine P.; Tai, Robert H.

    2014-06-01

    The majority of existing science, technology, engineering, and mathematics (STEM) research studies compare women to men, yet a paucity of research exists that examines what differentiates female career choice within the physical sciences. In light of these research trends and recommendations, this study examines the following question: On average, do females who select physics as compared to chemistry doctoral programs differ in their reported personal motivations and background factors prior to entering the field? This question is analyzed using variables from the Project Crossover Survey data set through a subset of female physical science doctoral students and scientists (n =1137). A logistic regression analysis and prototypical odds ratio uncover what differentiates women in the physical sciences based on their academic achievement and experiences ranging from high school through undergraduate education. Results indicate that females who have negative undergraduate chemistry experiences as well as higher grades and positive experiences in undergraduate physics are more likely to pursue a career in physics as opposed to chemistry. Conclusions suggest that a greater emphasis should be placed on the classroom experiences that are provided to females in gateway physics courses. Analyses show that women are not a single entity that should only be examined as a whole group or in comparison to men. Instead women can be compared to one another to see what influences their differences in educational experiences and career choice in STEM-based fields as well as other academic areas of study.

  7. Comparative analysis of female physicists in the physical sciences: Motivation and background variables

    Directory of Open Access Journals (Sweden)

    Katherine P. Dabney

    2014-02-01

    Full Text Available The majority of existing science, technology, engineering, and mathematics (STEM research studies compare women to men, yet a paucity of research exists that examines what differentiates female career choice within the physical sciences. In light of these research trends and recommendations, this study examines the following question: On average, do females who select physics as compared to chemistry doctoral programs differ in their reported personal motivations and background factors prior to entering the field? This question is analyzed using variables from the Project Crossover Survey data set through a subset of female physical science doctoral students and scientists (n=1137. A logistic regression analysis and prototypical odds ratio uncover what differentiates women in the physical sciences based on their academic achievement and experiences ranging from high school through undergraduate education. Results indicate that females who have negative undergraduate chemistry experiences as well as higher grades and positive experiences in undergraduate physics are more likely to pursue a career in physics as opposed to chemistry. Conclusions suggest that a greater emphasis should be placed on the classroom experiences that are provided to females in gateway physics courses. Analyses show that women are not a single entity that should only be examined as a whole group or in comparison to men. Instead women can be compared to one another to see what influences their differences in educational experiences and career choice in STEM-based fields as well as other academic areas of study.

  8. Physical capacity and risk for long-term sickness absence: a prospective cohort study among 8664 female health care workers.

    Science.gov (United States)

    Rasmussen, Charlotte Diana Nørregaard; Andersen, Lars Louis; Clausen, Thomas; Strøyer, Jesper; Jørgensen, Marie Birk; Holtermann, Andreas

    2015-05-01

    To assess the prospective associations between self-reported physical capacity and risk of long-term sickness absence among female health care workers. Female health care workers answered a questionnaire about physical capacity and were followed in a national register of sickness absence lasting for two or more consecutive weeks during 1-year follow-up. Using Cox regression hazard ratio analyses adjusted for age, smoking, body mass index, physical workload, job seniority, psychosocial work conditions, and previous sickness absence, we modeled risk estimates for sickness absence from low and medium physical capacity. Low and medium aerobic fitness, low muscle strength, low flexibility, and low overall physical capacity significantly increased the risk for sickness absence with 20% to 34% compared with health care workers with high capacity. Low physical capacity increases the risk of long-term sickness absence among female health care workers.

  9. Regression models of reactor diagnostic signals

    International Nuclear Information System (INIS)

    Vavrin, J.

    1989-01-01

    The application is described of an autoregression model as the simplest regression model of diagnostic signals in experimental analysis of diagnostic systems, in in-service monitoring of normal and anomalous conditions and their diagnostics. The method of diagnostics is described using a regression type diagnostic data base and regression spectral diagnostics. The diagnostics is described of neutron noise signals from anomalous modes in the experimental fuel assembly of a reactor. (author)

  10. 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…

  11. Multivariate Regression Analysis and Slaughter Livestock,

    Science.gov (United States)

    AGRICULTURE, *ECONOMICS), (*MEAT, PRODUCTION), MULTIVARIATE ANALYSIS, REGRESSION ANALYSIS , ANIMALS, WEIGHT, COSTS, PREDICTIONS, STABILITY, MATHEMATICAL MODELS, STORAGE, BEEF, PORK, FOOD, STATISTICAL DATA, ACCURACY

  12. [From clinical judgment to linear regression model.

    Science.gov (United States)

    Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O

    2013-01-01

    When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R 2 ) indicates the importance of independent variables in the outcome.

  13. Evaluation of Linear Regression Simultaneous Myoelectric Control Using Intramuscular EMG.

    Science.gov (United States)

    Smith, Lauren H; Kuiken, Todd A; Hargrove, Levi J

    2016-04-01

    The objective of this study was to evaluate the ability of linear regression models to decode patterns of muscle coactivation from intramuscular electromyogram (EMG) and provide simultaneous myoelectric control of a virtual 3-DOF wrist/hand system. Performance was compared to the simultaneous control of conventional myoelectric prosthesis methods using intramuscular EMG (parallel dual-site control)-an approach that requires users to independently modulate individual muscles in the residual limb, which can be challenging for amputees. Linear regression control was evaluated in eight able-bodied subjects during a virtual Fitts' law task and was compared to performance of eight subjects using parallel dual-site control. An offline analysis also evaluated how different types of training data affected prediction accuracy of linear regression control. The two control systems demonstrated similar overall performance; however, the linear regression method demonstrated improved performance for targets requiring use of all three DOFs, whereas parallel dual-site control demonstrated improved performance for targets that required use of only one DOF. Subjects using linear regression control could more easily activate multiple DOFs simultaneously, but often experienced unintended movements when trying to isolate individual DOFs. Offline analyses also suggested that the method used to train linear regression systems may influence controllability. Linear regression myoelectric control using intramuscular EMG provided an alternative to parallel dual-site control for 3-DOF simultaneous control at the wrist and hand. The two methods demonstrated different strengths in controllability, highlighting the tradeoff between providing simultaneous control and the ability to isolate individual DOFs when desired.

  14. Use of probabilistic weights to enhance linear regression myoelectric control

    Science.gov (United States)

    Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.

    2015-12-01

    Objective. Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Approach. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts’ law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Main results. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p < 0.05) by preventing extraneous movement at additional DOFs. Similar results were seen in experiments with two transradial amputees. Though goodness-of-fit evaluations suggested that the EMG feature distributions showed some deviations from the Gaussian, equal-covariance assumptions used in this experiment, the assumptions were sufficiently met to provide improved performance compared to linear regression control. Significance. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

  15. Female feticide in India.

    Science.gov (United States)

    Ahmad, Nehaluddin

    2010-01-01

    Women are murdered all over the world. But in India a most brutal form of killing females takes place regularly, even before they have the opportunity to be born. Female feticide--the selective abortion of female fetuses--is killing upwards of one million females in India annually with far-ranging and tragic consequences. In some areas, the sex ratio of females to males has dropped to less than 8000:1000. Females not only face inequality in this culture, they are even denied the right to be born. Why do so many families selectively abort baby daughters? In a word: economics. Aborting female fetuses is both practical and socially acceptable in India. Female feticide is driven by many factors, but primarily by the prospect of having to pay a dowry to the future bridegroom of a daughter. While sons offer security to their families in old age and can perform the rites for the souls of deceased parents and ancestors, daughters are perceived as a social and economic burden. Prenatal sex detection technologies have been misused, allowing the selective abortions of female offspring to proliferate. Legally, however, female feticide is a penal offence. Although female infanticide has long been committed in India, feticide is a relatively new practice, emerging concurrently with the advent of technological advancements in prenatal sex determination on a large scale in the 1990s. While abortion is legal in India, it is a crime to abort a pregnancy solely because the fetus is female. Strict laws and penalties are in place for violators. These laws, however, have not stemmed the tide of this abhorrent practice. This article will discuss the socio-legal conundrum female feticide presents, as well as the consequences of having too few women in Indian society.

  16. Social representations of female orgasm.

    Science.gov (United States)

    Lavie-Ajayi, Maya; Joffe, Hélène

    2009-01-01

    This study examines women's social representations of female orgasm. Fifty semi-structured interviews were conducted with British women. The data were thematically analysed and compared with the content of female orgasm-related writing in two women's magazines over a 30-year period. The results indicate that orgasm is deemed the goal of sex with emphasis on its physiological dimension. However, the women and the magazines graft onto this scientifically driven representation the importance of relational and emotive aspects of orgasm. For the women, particularly those who experience themselves as having problems with orgasm, the scientifically driven representations induce feelings of failure, but are also resisted. The findings highlight the role played by the social context in women's subjective experience of their sexual health.

  17. Regression modeling methods, theory, and computation with SAS

    CERN Document Server

    Panik, Michael

    2009-01-01

    Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs.The text presents the popular ordinary least squares (OLS) approach before introducing many alternative regression methods. It covers nonparametric regression, logistic regression (including Poisson regression), Bayesian regression, robust regression, fuzzy regression, random coefficients regression,

  18. Prediction of radiation levels in residences: A methodological comparison of CART [Classification and Regression Tree Analysis] and conventional regression

    International Nuclear Information System (INIS)

    Janssen, I.; Stebbings, J.H.

    1990-01-01

    In environmental epidemiology, trace and toxic substance concentrations frequently have very highly skewed distributions ranging over one or more orders of magnitude, and prediction by conventional regression is often poor. Classification and Regression Tree Analysis (CART) is an alternative in such contexts. To compare the techniques, two Pennsylvania data sets and three independent variables are used: house radon progeny (RnD) and gamma levels as predicted by construction characteristics in 1330 houses; and ∼200 house radon (Rn) measurements as predicted by topographic parameters. CART may identify structural variables of interest not identified by conventional regression, and vice versa, but in general the regression models are similar. CART has major advantages in dealing with other common characteristics of environmental data sets, such as missing values, continuous variables requiring transformations, and large sets of potential independent variables. CART is most useful in the identification and screening of independent variables, greatly reducing the need for cross-tabulations and nested breakdown analyses. There is no need to discard cases with missing values for the independent variables because surrogate variables are intrinsic to CART. The tree-structured approach is also independent of the scale on which the independent variables are measured, so that transformations are unnecessary. CART identifies important interactions as well as main effects. The major advantages of CART appear to be in exploring data. Once the important variables are identified, conventional regressions seem to lead to results similar but more interpretable by most audiences. 12 refs., 8 figs., 10 tabs

  19. RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM,

    Science.gov (United States)

    This memorandum gives instructions for the use and operation of a revised version of RAWS, a multiple regression analysis program. The program...of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. (Author)

  20. Hierarchical regression analysis in structural Equation Modeling

    NARCIS (Netherlands)

    de Jong, P.F.

    1999-01-01

    In a hierarchical or fixed-order regression analysis, the independent variables are entered into the regression equation in a prespecified order. Such an analysis is often performed when the extra amount of variance accounted for in a dependent variable by a specific independent variable is the main

  1. Categorical regression dose-response modeling

    Science.gov (United States)

    The goal of this training is to provide participants with training on the use of the U.S. EPA’s Categorical Regression soft¬ware (CatReg) and its application to risk assessment. Categorical regression fits mathematical models to toxicity data that have been assigned ord...

  2. Variable importance in latent variable regression models

    NARCIS (Netherlands)

    Kvalheim, O.M.; Arneberg, R.; Bleie, O.; Rajalahti, T.; Smilde, A.K.; Westerhuis, J.A.

    2014-01-01

    The quality and practical usefulness of a regression model are a function of both interpretability and prediction performance. This work presents some new graphical tools for improved interpretation of latent variable regression models that can also assist in improved algorithms for variable

  3. Stepwise versus Hierarchical Regression: Pros and Cons

    Science.gov (United States)

    Lewis, Mitzi

    2007-01-01

    Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…

  4. Suppression Situations in Multiple Linear Regression

    Science.gov (United States)

    Shieh, Gwowen

    2006-01-01

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

  5. Gibrat’s law and quantile regressions

    DEFF Research Database (Denmark)

    Distante, Roberta; Petrella, Ivan; Santoro, Emiliano

    2017-01-01

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

  6. Regression Analysis and the Sociological Imagination

    Science.gov (United States)

    De Maio, Fernando

    2014-01-01

    Regression analysis is an important aspect of most introductory statistics courses in sociology but is often presented in contexts divorced from the central concerns that bring students into the discipline. Consequently, we present five lesson ideas that emerge from a regression analysis of income inequality and mortality in the USA and Canada.

  7. 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

  8. Principles of Quantile Regression and an Application

    Science.gov (United States)

    Chen, Fang; Chalhoub-Deville, Micheline

    2014-01-01

    Newer statistical procedures are typically introduced to help address the limitations of those already in practice or to deal with emerging research needs. Quantile regression (QR) is introduced in this paper as a relatively new methodology, which is intended to overcome some of the limitations of least squares mean regression (LMR). QR is more…

  9. ON REGRESSION REPRESENTATIONS OF STOCHASTIC-PROCESSES

    NARCIS (Netherlands)

    RUSCHENDORF, L; DEVALK, [No Value

    We construct a.s. nonlinear regression representations of general stochastic processes (X(n))n is-an-element-of N. As a consequence we obtain in particular special regression representations of Markov chains and of certain m-dependent sequences. For m-dependent sequences we obtain a constructive

  10. Regression of environmental noise in LIGO data

    International Nuclear Information System (INIS)

    Tiwari, V; Klimenko, S; Mitselmakher, G; Necula, V; Drago, M; Prodi, G; Frolov, V; Yakushin, I; Re, V; Salemi, F; Vedovato, G

    2015-01-01

    We address the problem of noise regression in the output of gravitational-wave (GW) interferometers, using data from the physical environmental monitors (PEM). The objective of the regression analysis is to predict environmental noise in the GW channel from the PEM measurements. One of the most promising regression methods is based on the construction of Wiener–Kolmogorov (WK) filters. Using this method, the seismic noise cancellation from the LIGO GW channel has already been performed. In the presented approach the WK method has been extended, incorporating banks of Wiener filters in the time–frequency domain, multi-channel analysis and regulation schemes, which greatly enhance the versatility of the regression analysis. Also we present the first results on regression of the bi-coherent noise in the LIGO data. (paper)

  11. Pathological assessment of liver fibrosis regression

    Directory of Open Access Journals (Sweden)

    WANG Bingqiong

    2017-03-01

    Full Text Available Hepatic fibrosis is the common pathological outcome of chronic hepatic diseases. An accurate assessment of fibrosis degree provides an important reference for a definite diagnosis of diseases, treatment decision-making, treatment outcome monitoring, and prognostic evaluation. At present, many clinical studies have proven that regression of hepatic fibrosis and early-stage liver cirrhosis can be achieved by effective treatment, and a correct evaluation of fibrosis regression has become a hot topic in clinical research. Liver biopsy has long been regarded as the gold standard for the assessment of hepatic fibrosis, and thus it plays an important role in the evaluation of fibrosis regression. This article reviews the clinical application of current pathological staging systems in the evaluation of fibrosis regression from the perspectives of semi-quantitative scoring system, quantitative approach, and qualitative approach, in order to propose a better pathological evaluation system for the assessment of fibrosis regression.

  12. Should metacognition be measured by logistic regression?

    Science.gov (United States)

    Rausch, Manuel; Zehetleitner, Michael

    2017-03-01

    Are logistic regression slopes suitable to quantify metacognitive sensitivity, i.e. the efficiency with which subjective reports differentiate between correct and incorrect task responses? We analytically show that logistic regression slopes are independent from rating criteria in one specific model of metacognition, which assumes (i) that rating decisions are based on sensory evidence generated independently of the sensory evidence used for primary task responses and (ii) that the distributions of evidence are logistic. Given a hierarchical model of metacognition, logistic regression slopes depend on rating criteria. According to all considered models, regression slopes depend on the primary task criterion. A reanalysis of previous data revealed that massive numbers of trials are required to distinguish between hierarchical and independent models with tolerable accuracy. It is argued that researchers who wish to use logistic regression as measure of metacognitive sensitivity need to control the primary task criterion and rating criteria. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. [Negative prognostic impact of female gender on oncological outcomes following radical cystectomy].

    Science.gov (United States)

    Dabi, Y; Rouscoff, Y; Delongchamps, N B; Sibony, M; Saighi, D; Zerbib, M; Peyraumore, M; Xylinas, E

    2016-02-01

    To confirm gender specific differences in pathologic factors and survival rates of urothelial bladder cancer patients treated with radical cystectomy. We conducted a retrospective monocentric study on 701 patients treated with radical cystectomy and pelvic lymphadenectomy for muscle invasive bladder cancer. Impact of gender on recurrence rate, specific and non-specific mortality rate were evaluated using Cox regression models in univariate and multivariate analysis. We collected data on 553 males (78.9%) and 148 females (21.1%) between 1998 and 2011. Both groups were comparable at inclusion regarding age, pathologic stage, nodal status and lymphovascular invasion. Mean follow-up time was 45 months (interquartile 23-73) and by that time, 163 patients (23.3%) had recurrence of their tumor and 127 (18.1%) died from their disease. In multivariable Cox regression analyses, female gender was independently associated with disease recurrence (RR: 1.73; 95% CI 1.22-2.47; P=0.02) and cancer-specific mortality (RR=2.50, 95% CI=1.71-3.68; P<0.001). We confirmed female gender to be an independent negative prognosis factor for patients following a radical cystectomy and lymphadenectomy for an invasive muscle bladder cancer. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  14. Prevalence and correlates of sexual risk among male and female sex workers in Tijuana, Mexico.

    Science.gov (United States)

    Katsulis, Yasmina; Durfee, Alesha

    2012-01-01

    We investigated prevalence and correlates of sexual risk behaviours among male and female sex workers in Tijuana, Mexico, the busiest border crossing area on the US - Mexico border, analysing survey data from a purposive, cross-sectional sample of male and female sex workers who worked in a range of indoor and outdoor settings. Logistic regression was used to determine factors that were associated with sexual risk-taking, defined as failing to use a condom with last client. In bivariate regression models, gender, work setting (e.g., indoor vs. outdoor), poverty, engaging in survival sex, marital status and perceived drug addiction were correlated with sexual risk. When controlling for work location, housing insecurity, poverty, survival sex, marital status and perceived drug addiction, male sex workers were still 10 times more likely than female sex workers (FSW) to engage in sex without a condom during their last encounter with a client. And, although FSW were significantly more likely than males to have used a condom with a client, they were significantly less likely than males to have used a condom with their regular partner. Future research should further examine how gender shapes sexual risk activities in both commercial and non-commercial relationships.

  15. Charismatic female leadership and gender

    DEFF Research Database (Denmark)

    Meret, Susi

    2015-01-01

    Research on the leadership and electorates of populist right-wing parties emphasizes that most of these parties are charismatic and male-dominated, both as regards their leadership and voters. However, while studies about the gender gap focus mainly on demand-side factors, such as electoral support......, socio-economic characteristics and the voters' attitudes towards issues such as immigration, those that analyse the role and position of gender issues are still rare. Similarly, or even more, overlooked is an analysis of the rhetoric, style, charisma and discourse of populist female leaders...

  16. Psychiatric and addictive symptoms of young adult female indoor tanners.

    Science.gov (United States)

    Heckman, Carolyn J; Cohen-Filipic, Jessye; Darlow, Susan; Kloss, Jacqueline D; Manne, Sharon L; Munshi, Teja

    2014-01-01

    Indoor tanning (IT) increases risk for melanoma and is particularly common among young adult women. IT has also been linked with some psychiatric symptoms, and frequent tanning may indicate tanning dependence (addiction) associated with endorphin release during ultraviolet radiation exposure. The objective of the current study was to investigate associations between IT, tanning dependence, and psychiatric and substance use symptoms in young adult women. Cross-sectional survey and psychiatric interview. Online, except for the Mini International Neuropsychiatric Interview (MINI), which was completed over the telephone. Participants were 306 female university students aged 18 to 25 years. MINI, Seasonal Scale Index, tanning dependence scales, reporting ever having used a tanning bed or booth with tanning lamps (single item), reporting smoking a cigarette in the last 30 days (single item). Descriptive statistics, χ(2) analysis, multivariate logistic regression. Forty-six percent of the sample reported a history of IT, and 25% were classified as tanning dependent. Multivariate logistic regression analyses showed that IT was significantly associated with symptoms of alcohol use disorders, generalized anxiety, and not having social anxiety. Tanning dependence was associated with symptoms of alcohol use disorders. Tanning is of concern not only for its association with skin cancer but for its association with psychiatric and substance use symptoms. Young women with certain psychological problems may seek relief from their symptoms by IT. These findings suggest that indoor tanners may benefit from health behavior and other psychosocial interventions.

  17. Logistic Regression Analysis of Operational Errors and Routine Operations Using Sector Characteristics

    National Research Council Canada - National Science Library

    Pfleiderer, Elaine M; Scroggins, Cheryl L; Manning, Carol A

    2009-01-01

    Two separate logistic regression analyses were conducted for low- and high-altitude sectors to determine whether a set of dynamic sector characteristics variables could reliably discriminate between operational error (OE...

  18. Regression of a vaginal leiomyoma after ovariohysterectomy in a dog: a case report.

    Science.gov (United States)

    Sathya, Suresh; Linn, Kathleen

    2014-01-01

    An 11 yr old female mixed-breed Siberian husky was presented with a history of sanguineous vaginal discharge, swelling of the perineal area, decreased appetite, and lethargy. A single, large vaginal leiomyoma and multiple mammary tumors were diagnosed. Mastectomy and ovariohysterectomy were performed. The vaginal leiomyoma regressed completely after ovariohysterectomy. This is the first reported case of spontaneous regression of a vaginal leiomyoma after ovariohysterectomy in a dog.

  19. Easy methods for extracting individual regression slopes: Comparing SPSS, R, and Excel

    Directory of Open Access Journals (Sweden)

    Roland Pfister

    2013-10-01

    Full Text Available Three different methods for extracting coefficientsof linear regression analyses are presented. The focus is on automatic and easy-to-use approaches for common statistical packages: SPSS, R, and MS Excel / LibreOffice Calc. Hands-on examples are included for each analysis, followed by a brief description of how a subsequent regression coefficient analysis is performed.

  20. Regression modeling of ground-water flow

    Science.gov (United States)

    Cooley, R.L.; Naff, R.L.

    1985-01-01

    Nonlinear multiple regression methods are developed to model and analyze groundwater flow systems. Complete descriptions of regression methodology as applied to groundwater flow models allow scientists and engineers engaged in flow modeling to apply the methods to a wide range of problems. Organization of the text proceeds from an introduction that discusses the general topic of groundwater flow modeling, to a review of basic statistics necessary to properly apply regression techniques, and then to the main topic: exposition and use of linear and nonlinear regression to model groundwater flow. Statistical procedures are given to analyze and use the regression models. A number of exercises and answers are included to exercise the student on nearly all the methods that are presented for modeling and statistical analysis. Three computer programs implement the more complex methods. These three are a general two-dimensional, steady-state regression model for flow in an anisotropic, heterogeneous porous medium, a program to calculate a measure of model nonlinearity with respect to the regression parameters, and a program to analyze model errors in computed dependent variables such as hydraulic head. (USGS)

  1. Cervical Cancer Incidence in Young U.S. Females After Human Papillomavirus Vaccine Introduction.

    Science.gov (United States)

    Guo, Fangjian; Cofie, Leslie E; Berenson, Abbey B

    2018-05-30

    Since 2006, human papillomavirus vaccine has been recommended for young females in the U.S. This study aimed to compare cervical cancer incidence among young women before and after the human papillomavirus vaccine was introduced. This cross-sectional study used data from the National Program for Cancer Registries and Surveillance, Epidemiology, and End Results Incidence-U.S. Cancer Statistics 2001-2014 database for U.S. females aged 15-34 years. This study compared the 4-year average annual incidence of invasive cervical cancer in the 4 years before human papillomavirus vaccine was introduced (2003-2006) and the 4 most recent years in the vaccine era (2011-2014). Joinpoint regression models of cervical incidence from 2001 to 2014 were fitted to identify the discrete joints (year) that represent statistically significant changes in the direction of the trend after the introduction of human papillomavirus vaccination in 2006. Data were collected in 2001-2014, released, and analyzed in 2017. The 4-year average annual incidence rates for cervical cancer in 2011-2014 were 29% lower than that in 2003-2006 (6.0 vs 8.4 per 1,000,000 people, rate ratio=0.71, 95% CI=0.64, 0.80) among females aged 15-24 years, and 13.0% lower among females aged 25-34 years. Joinpoint analyses of cervical cancer incidence among females aged 15-24 years revealed a significant joint at 2009 for both squamous cell carcinoma and non-squamous cell carcinoma. Among females aged 25-34 years, there was no significant decrease in cervical cancer incidence after 2006. A significant decrease in the incidence of cervical cancer among young females after the introduction of human papillomavirus vaccine may indicate early effects of human papillomavirus vaccination. Copyright © 2018 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

  2. Female Labor Supply

    NARCIS (Netherlands)

    Maassen-van den Brink, te Henriet

    1994-01-01

    To gain insight on factors that impede economic independence of women, this book concentrates on female labor supply in relation to child care, male-female wage differentials, the division of unpaid labor, and marital conflicts between women and men. It may very well be that restrictions on the

  3. Logistic Regression in the Identification of Hazards in Construction

    Science.gov (United States)

    Drozd, Wojciech

    2017-10-01

    The construction site and its elements create circumstances that are conducive to the formation of risks to safety during the execution of works. Analysis indicates the critical importance of these factors in the set of characteristics that describe the causes of accidents in the construction industry. This article attempts to analyse the characteristics related to the construction site, in order to indicate their importance in defining the circumstances of accidents at work. The study includes sites inspected in 2014 - 2016 by the employees of the District Labour Inspectorate in Krakow (Poland). The analysed set of detailed (disaggregated) data includes both quantitative and qualitative characteristics. The substantive task focused on classification modelling in the identification of hazards in construction and identifying those of the analysed characteristics that are important in an accident. In terms of methodology, resource data analysis using statistical classifiers, in the form of logistic regression, was the method used.

  4. Variable and subset selection in PLS regression

    DEFF Research Database (Denmark)

    Høskuldsson, Agnar

    2001-01-01

    The purpose of this paper is to present some useful methods for introductory analysis of variables and subsets in relation to PLS regression. We present here methods that are efficient in finding the appropriate variables or subset to use in the PLS regression. The general conclusion...... is that variable selection is important for successful analysis of chemometric data. An important aspect of the results presented is that lack of variable selection can spoil the PLS regression, and that cross-validation measures using a test set can show larger variation, when we use different subsets of X, than...

  5. Applied Regression Modeling A Business Approach

    CERN Document Server

    Pardoe, Iain

    2012-01-01

    An applied and concise treatment of statistical regression techniques for business students and professionals who have little or no background in calculusRegression analysis is an invaluable statistical methodology in business settings and is vital to model the relationship between a response variable and one or more predictor variables, as well as the prediction of a response value given values of the predictors. In view of the inherent uncertainty of business processes, such as the volatility of consumer spending and the presence of market uncertainty, business professionals use regression a

  6. Linear regression metamodeling as a tool to summarize and present simulation model results.

    Science.gov (United States)

    Jalal, Hawre; Dowd, Bryan; Sainfort, François; Kuntz, Karen M

    2013-10-01

    Modelers lack a tool to systematically and clearly present complex model results, including those from sensitivity analyses. The objective was to propose linear regression metamodeling as a tool to increase transparency of decision analytic models and better communicate their results. We used a simplified cancer cure model to demonstrate our approach. The model computed the lifetime cost and benefit of 3 treatment options for cancer patients. We simulated 10,000 cohorts in a probabilistic sensitivity analysis (PSA) and regressed the model outcomes on the standardized input parameter values in a set of regression analyses. We used the regression coefficients to describe measures of sensitivity analyses, including threshold and parameter sensitivity analyses. We also compared the results of the PSA to deterministic full-factorial and one-factor-at-a-time designs. The regression intercept represented the estimated base-case outcome, and the other coefficients described the relative parameter uncertainty in the model. We defined simple relationships that compute the average and incremental net benefit of each intervention. Metamodeling produced outputs similar to traditional deterministic 1-way or 2-way sensitivity analyses but was more reliable since it used all parameter values. Linear regression metamodeling is a simple, yet powerful, tool that can assist modelers in communicating model characteristics and sensitivity analyses.

  7. Binge eating disorder and depressive symptoms among females of child-bearing age: the Korea Nurses' Health Study.

    Science.gov (United States)

    Kim, O; Kim, M S; Kim, J; Lee, J E; Jung, H

    2018-01-17

    Most studies regarding the relationship between binge eating disorder (BED) and depression have targeted obese populations. However, nurses, particularly female nurses, are one of the vocations that face these issues due to various reasons including high stress and shift work. This study investigated the prevalence of BED and the correlation between BED and severity of self-reported depressive symptoms among female nurses in South Korea. Participants were 7,267 female nurses, of which 502 had symptoms of BED. Using the propensity score matching (PSM) technique, 502 nurses with BED and 502 without BED were included in the analyses. Data were analyzed using descriptive statistics, Spearman's correlation, and multivariable ordinal logistic regression analysis. The proportion of binge eating disorder was 6.90% among the nurses, and 81.3% of nurses displayed some levels of depressive symptoms. Multivariable ordinal logistic regression analysis revealed that age (40 years old and older), alcohol consumption (frequent drinkers), self-rated health, sleep problems, and stress were associated with self-reported depression symptoms. Overall, after adjusting for confounders, nurses with BED had 1.80 times the risk (95% CI = [1.41-2.30]; p-value depression symptoms. Korean female nurse showed a higher prevalence of both binge eating disorder and depressive symptoms, and the association between the two factors was proven in the study. Therefore, hospital management and health policy makers should be alarmed and agreed on both examining nurses on such problems and providing organized and systematic assistance.

  8. Vectors, a tool in statistical regression theory

    NARCIS (Netherlands)

    Corsten, L.C.A.

    1958-01-01

    Using linear algebra this thesis developed linear regression analysis including analysis of variance, covariance analysis, special experimental designs, linear and fertility adjustments, analysis of experiments at different places and times. The determination of the orthogonal projection, yielding

  9. Genetics Home Reference: caudal regression syndrome

    Science.gov (United States)

    ... umbilical artery: Further support for a caudal regression-sirenomelia spectrum. Am J Med Genet A. 2007 Dec ... AK, Dickinson JE, Bower C. Caudal dysgenesis and sirenomelia-single centre experience suggests common pathogenic basis. Am ...

  10. Dynamic travel time estimation using regression trees.

    Science.gov (United States)

    2008-10-01

    This report presents a methodology for travel time estimation by using regression trees. The dissemination of travel time information has become crucial for effective traffic management, especially under congested road conditions. In the absence of c...

  11. Two Paradoxes in Linear Regression Analysis

    Science.gov (United States)

    FENG, Ge; PENG, Jing; TU, Dongke; ZHENG, Julia Z.; FENG, Changyong

    2016-01-01

    Summary Regression is one of the favorite tools in applied statistics. However, misuse and misinterpretation of results from regression analysis are common in biomedical research. In this paper we use statistical theory and simulation studies to clarify some paradoxes around this popular statistical method. In particular, we show that a widely used model selection procedure employed in many publications in top medical journals is wrong. Formal procedures based on solid statistical theory should be used in model selection. PMID:28638214

  12. Discriminative Elastic-Net Regularized Linear Regression.

    Science.gov (United States)

    Zhang, Zheng; Lai, Zhihui; Xu, Yong; Shao, Ling; Wu, Jian; Xie, Guo-Sen

    2017-03-01

    In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However, most of the existing linear regression methods exploit the conventional zero-one matrix as the regression targets, which greatly narrows the flexibility of the regression model. Another major limitation of these methods is that the learned projection matrix fails to precisely project the image features to the target space due to their weak discriminative capability. To this end, we present an elastic-net regularized linear regression (ENLR) framework, and develop two robust linear regression models which possess the following special characteristics. First, our methods exploit two particular strategies to enlarge the margins of different classes by relaxing the strict binary targets into a more feasible variable matrix. Second, a robust elastic-net regularization of singular values is introduced to enhance the compactness and effectiveness of the learned projection matrix. Third, the resulting optimization problem of ENLR has a closed-form solution in each iteration, which can be solved efficiently. Finally, rather than directly exploiting the projection matrix for recognition, our methods employ the transformed features as the new discriminate representations to make final image classification. Compared with the traditional linear regression model and some of its variants, our method is much more accurate in image classification. Extensive experiments conducted on publicly available data sets well demonstrate that the proposed framework can outperform the state-of-the-art methods. The MATLAB codes of our methods can be available at http://www.yongxu.org/lunwen.html.

  13. Fuzzy multiple linear regression: A computational approach

    Science.gov (United States)

    Juang, C. H.; Huang, X. H.; Fleming, J. W.

    1992-01-01

    This paper presents a new computational approach for performing fuzzy regression. In contrast to Bardossy's approach, the new approach, while dealing with fuzzy variables, closely follows the conventional regression technique. In this approach, treatment of fuzzy input is more 'computational' than 'symbolic.' The following sections first outline the formulation of the new approach, then deal with the implementation and computational scheme, and this is followed by examples to illustrate the new procedure.

  14. 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

  15. There is No Quantum Regression Theorem

    International Nuclear Information System (INIS)

    Ford, G.W.; OConnell, R.F.

    1996-01-01

    The Onsager regression hypothesis states that the regression of fluctuations is governed by macroscopic equations describing the approach to equilibrium. It is here asserted that this hypothesis fails in the quantum case. This is shown first by explicit calculation for the example of quantum Brownian motion of an oscillator and then in general from the fluctuation-dissipation theorem. It is asserted that the correct generalization of the Onsager hypothesis is the fluctuation-dissipation theorem. copyright 1996 The American Physical Society

  16. Caudal regression syndrome : a case report

    International Nuclear Information System (INIS)

    Lee, Eun Joo; Kim, Hi Hye; Kim, Hyung Sik; Park, So Young; Han, Hye Young; Lee, Kwang Hun

    1998-01-01

    Caudal regression syndrome is a rare congenital anomaly, which results from a developmental failure of the caudal mesoderm during the fetal period. We present a case of caudal regression syndrome composed of a spectrum of anomalies including sirenomelia, dysplasia of the lower lumbar vertebrae, sacrum, coccyx and pelvic bones,genitourinary and anorectal anomalies, and dysplasia of the lung, as seen during infantography and MR imaging

  17. Caudal regression syndrome : a case report

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Eun Joo; Kim, Hi Hye; Kim, Hyung Sik; Park, So Young; Han, Hye Young; Lee, Kwang Hun [Chungang Gil Hospital, Incheon (Korea, Republic of)

    1998-07-01

    Caudal regression syndrome is a rare congenital anomaly, which results from a developmental failure of the caudal mesoderm during the fetal period. We present a case of caudal regression syndrome composed of a spectrum of anomalies including sirenomelia, dysplasia of the lower lumbar vertebrae, sacrum, coccyx and pelvic bones,genitourinary and anorectal anomalies, and dysplasia of the lung, as seen during infantography and MR imaging.

  18. Spontaneous regression of metastatic Merkel cell carcinoma.

    LENUS (Irish Health Repository)

    Hassan, S J

    2010-01-01

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

  19. Forecasting exchange rates: a robust regression approach

    OpenAIRE

    Preminger, Arie; Franck, Raphael

    2005-01-01

    The least squares estimation method as well as other ordinary estimation method for regression models can be severely affected by a small number of outliers, thus providing poor out-of-sample forecasts. This paper suggests a robust regression approach, based on the S-estimation method, to construct forecasting models that are less sensitive to data contamination by outliers. A robust linear autoregressive (RAR) and a robust neural network (RNN) models are estimated to study the predictabil...

  20. Marginal longitudinal semiparametric regression via penalized splines

    KAUST Repository

    Al Kadiri, M.

    2010-08-01

    We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.

  1. Marginal longitudinal semiparametric regression via penalized splines

    KAUST Repository

    Al Kadiri, M.; Carroll, R.J.; Wand, M.P.

    2010-01-01

    We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.

  2. Post-processing through linear regression

    Science.gov (United States)

    van Schaeybroeck, B.; Vannitsem, S.

    2011-03-01

    Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS) method, a new time-dependent Tikhonov regularization (TDTR) method, the total least-square method, a new geometric-mean regression (GM), a recently introduced error-in-variables (EVMOS) method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified. These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise). At long lead times the regression schemes (EVMOS, TDTR) which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.

  3. Post-processing through linear regression

    Directory of Open Access Journals (Sweden)

    B. Van Schaeybroeck

    2011-03-01

    Full Text Available Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS method, a new time-dependent Tikhonov regularization (TDTR method, the total least-square method, a new geometric-mean regression (GM, a recently introduced error-in-variables (EVMOS method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified.

    These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise. At long lead times the regression schemes (EVMOS, TDTR which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.

  4. Unbalanced Regressions and the Predictive Equation

    DEFF Research Database (Denmark)

    Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo

    Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness in the theoreti......Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness...... in the theoretical predictive equation by suggesting a data generating process, where returns are generated as linear functions of a lagged latent I(0) risk process. The observed predictor is a function of this latent I(0) process, but it is corrupted by a fractionally integrated noise. Such a process may arise due...... to aggregation or unexpected level shifts. In this setup, the practitioner estimates a misspecified, unbalanced, and endogenous predictive regression. We show that the OLS estimate of this regression is inconsistent, but standard inference is possible. To obtain a consistent slope estimate, we then suggest...

  5. Impact of military trauma exposures on posttraumatic stress and depression in female veterans.

    Science.gov (United States)

    Goldstein, Lizabeth A; Dinh, Julie; Donalson, Rosemary; Hebenstreit, Claire L; Maguen, Shira

    2017-03-01

    Previous research has demonstrated the deleterious effects of traumatic military experiences on symptoms of posttraumatic stress disorder (PTSD) and depression in female veterans. However, more research is needed to identify the unique predictors of distressing psychological symptoms when both combat-related and sexual trauma are considered, particularly as women's combat exposure in the military increases. Female veterans who had attended at least one appointment at a large Veterans Health Administration medical center were invited to complete questionnaires about traumatic military exposures and psychiatric symptoms. A total of 403 veterans responded, with 383 respondents' data used in analyses. Multiple regression analyses were conducted with trauma exposure items entered simultaneously to determine their association with symptoms of (1) PTSD and (2) depression. Sexual assault had the strongest relationship with both posttraumatic and depressive symptoms. Sexual assault, sexual harassment, feeling in danger of being killed, and seeing others killed/injured were associated with symptoms of PTSD, but only sexual assault and sexual harassment were associated with symptoms of depression, even when accounting for several aspects of combat exposure. Improving assessment for trauma exposure and developing treatments personalized to type of trauma experienced are important clinical research priorities as female service members' roles in the military expand. Published by Elsevier B.V.

  6. Mutation in filamin A causes periventricular heterotopia, developmental regression, and West syndrome in males.

    Science.gov (United States)

    Masruha, Marcelo R; Caboclo, Luis O S F; Carrete, Henrique; Cendes, Iscia L; Rodrigues, Murilo G; Garzon, Eliana; Yacubian, Elza M T; Sakamoto, Américo C; Sheen, Volney; Harney, Megan; Neal, Jason; Hill, R Sean; Bodell, Adria; Walsh, Christopher; Vilanova, Luiz C P

    2006-01-01

    Familial periventricular heterotopia (PH) represents a disorder of neuronal migration resulting in multiple gray-matter nodules along the lateral ventricular walls. Prior studies have shown that mutations in the filamin A (FLNA) gene can cause PH through an X-linked dominant pattern. Heterozygotic female patients usually remain asymptomatic until the second or third decade of life, when they may have predominantly focal seizures, whereas hemizygotic male fetuses typically die in utero. Recent studies have also reported mutations in FLNA in male patients with PH who are cognitively normal. We describe PH in three male siblings with PH due to FLNA, severe developmental regression, and West syndrome. The study includes the three affected brothers and their parents. Video-EEG recordings and magnetic resonance image (MRI) scanning were performed on all individuals. Mutations for FLNA were detected by using polymerase chain reaction (PCR) on genomic DNA followed by single-stranded conformational polymorphism (SSCP) analysis or sequencing. Two of the siblings are monozygotic twins, and all had West syndrome with hypsarrhythmia on EEG. MRI of the brain revealed periventricular nodules of cerebral gray-matter intensity, typical for PH. Mutational analyses demonstrated a cytosine-to-thymidine missense mutation (c. C1286T), resulting in a threonine-to-methionine amino acid substitution in exon 9 of the FLNA gene. The association between PH and West syndrome, to our knowledge, has not been previously reported. Males with PH have been known to harbor FLNA mutations, although uniformly, they either show early lethality or survive and have a normal intellect. The current studies show that FLNA mutations can cause periventricular heterotopia, developmental regression, and West syndrome in male patients, suggesting that this type of FLNA mutation may contribute to severe neurologic deficits.

  7. Gender roles and binge drinking among Latino emerging adults: a latent class regression analysis.

    Science.gov (United States)

    Vaughan, Ellen L; Wong, Y Joel; Middendorf, Katharine G

    2014-09-01

    Gender roles are often cited as a culturally specific predictor of drinking among Latino populations. This study used latent class regression to test the relationships between gender roles and binge drinking in a sample of Latino emerging adults. Participants were Latino emerging adults who participated in Wave III of the National Longitudinal Study of Adolescent Health (N = 2,442). A subsample of these participants (n = 660) completed the Bem Sex Role Inventory--Short. We conducted latent class regression using 3 dimensions of gender roles (femininity, social masculinity, and personal masculinity) to predict binge drinking. Results indicated a 3-class solution. In Class 1, the protective personal masculinity class, personal masculinity (e.g., being a leader, defending one's own beliefs) was associated with a reduction in the odds of binge drinking. In Class 2, the nonsignificant class, gender roles were not related to binge drinking. In Class 3, the mixed masculinity class, personal masculinity was associated with a reduction in the odds of binge drinking, whereas social masculinity (e.g., forceful, dominant) was associated with an increase in the odds of binge drinking. Post hoc analyses found that females, those born outside the United States, and those with greater English language usage were at greater odds of being in Class 1 (vs. Class 2). Males, those born outside the United States, and those with greater Spanish language usage were at greater odds of being in Class 3 (vs. Class 2). Directions for future research and implications for practice with Latino emerging adults are discussed.

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

    Science.gov (United States)

    Baldwin, Scott A; Larson, Michael J

    2017-11-01

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

  9. Covariate Imbalance and Adjustment for Logistic Regression Analysis of Clinical Trial Data

    Science.gov (United States)

    Ciolino, Jody D.; Martin, Reneé H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.

    2014-01-01

    In logistic regression analysis for binary clinical trial data, adjusted treatment effect estimates are often not equivalent to unadjusted estimates in the presence of influential covariates. This paper uses simulation to quantify the benefit of covariate adjustment in logistic regression. However, International Conference on Harmonization guidelines suggest that covariate adjustment be pre-specified. Unplanned adjusted analyses should be considered secondary. Results suggest that that if adjustment is not possible or unplanned in a logistic setting, balance in continuous covariates can alleviate some (but never all) of the shortcomings of unadjusted analyses. The case of log binomial regression is also explored. PMID:24138438

  10. Economic Analyses of Ware Yam Production in Orlu Agricultural ...

    African Journals Online (AJOL)

    Economic Analyses of Ware Yam Production in Orlu Agricultural Zone of Imo State. ... International Journal of Agriculture and Rural Development ... statistics, gross margin analysis, marginal analysis and multiple regression analysis. Results ...

  11. The best of both worlds: Phylogenetic eigenvector regression and mapping

    Directory of Open Access Journals (Sweden)

    José Alexandre Felizola Diniz Filho

    2015-09-01

    Full Text Available Eigenfunction analyses have been widely used to model patterns of autocorrelation in time, space and phylogeny. In a phylogenetic context, Diniz-Filho et al. (1998 proposed what they called Phylogenetic Eigenvector Regression (PVR, in which pairwise phylogenetic distances among species are submitted to a Principal Coordinate Analysis, and eigenvectors are then used as explanatory variables in regression, correlation or ANOVAs. More recently, a new approach called Phylogenetic Eigenvector Mapping (PEM was proposed, with the main advantage of explicitly incorporating a model-based warping in phylogenetic distance in which an Ornstein-Uhlenbeck (O-U process is fitted to data before eigenvector extraction. Here we compared PVR and PEM in respect to estimated phylogenetic signal, correlated evolution under alternative evolutionary models and phylogenetic imputation, using simulated data. Despite similarity between the two approaches, PEM has a slightly higher prediction ability and is more general than the original PVR. Even so, in a conceptual sense, PEM may provide a technique in the best of both worlds, combining the flexibility of data-driven and empirical eigenfunction analyses and the sounding insights provided by evolutionary models well known in comparative analyses.

  12. Older maternal age is associated with depression, anxiety, and stress symptoms in young adult female offspring.

    Science.gov (United States)

    Tearne, Jessica E; Robinson, Monique; Jacoby, Peter; Allen, Karina L; Cunningham, Nadia K; Li, Jianghong; McLean, Neil J

    2016-01-01

    The evidence regarding older parental age and incidence of mood disorder symptoms in offspring is limited, and that which exists is mixed. We sought to clarify these relationships by using data from the Western Australian Pregnancy Cohort (Raine) Study. The Raine Study provided comprehensive data from 2,900 pregnancies, resulting in 2,868 live born children. A total of 1,220 participants completed the short form of the Depression Anxiety Stress Scale (DASS-21) at the 20-year cohort follow-up. We used negative binomial regression analyses with log link and with adjustment for known perinatal risk factors to examine the extent to which maternal and paternal age at childbirth predicted continuous DASS-21 index scores. In the final multivariate models, a maternal age of 30-34 years was associated with significant increases in stress DASS-21 scores in female offspring relative to female offspring of 25- to 29-year-old mothers. A maternal age of 35 years and over was associated with increased scores on all DASS-21 scales in female offspring. Our results indicate that older maternal age is associated with depression, anxiety, and stress symptoms in young adult females. Further research into the mechanisms underpinning this relationship is needed. (c) 2016 APA, all rights reserved.

  13. Poisson regression for modeling count and frequency outcomes in trauma research.

    Science.gov (United States)

    Gagnon, David R; Doron-LaMarca, Susan; Bell, Margret; O'Farrell, Timothy J; Taft, Casey T

    2008-10-01

    The authors describe how the Poisson regression method for analyzing count or frequency outcome variables can be applied in trauma studies. The outcome of interest in trauma research may represent a count of the number of incidents of behavior occurring in a given time interval, such as acts of physical aggression or substance abuse. Traditional linear regression approaches assume a normally distributed outcome variable with equal variances over the range of predictor variables, and may not be optimal for modeling count outcomes. An application of Poisson regression is presented using data from a study of intimate partner aggression among male patients in an alcohol treatment program and their female partners. Results of Poisson regression and linear regression models are compared.

  14. Global Prevalence of Elder Abuse: A Meta-analysis and Meta-regression.

    Science.gov (United States)

    Ho, C Sh; Wong, S Y; Chiu, M M; Ho, R Cm

    2017-06-01

    Elder abuse is increasingly recognised as a global public health and social problem. There has been limited inter-study comparison of the prevalence and risk factors for elder abuse. This study aimed to estimate the pooled and subtype prevalence of elder abuse worldwide and identify significant associated risk factors. We conducted a meta-analysis and meta-regression of 34 population-based and 17 non-population-based studies. The pooled prevalences of elder abuse were 10.0% (95% confidence interval, 5.2%-18.6%) and 34.3% (95% confidence interval, 22.9%-47.8%) in population-based studies and third party- or caregiver-reported studies, respectively. Being in a marital relationship was found to be a significant moderator using random-effects model. This meta-analysis revealed that third parties or caregivers were more likely to report abuse than older abused adults. Subgroup analyses showed that females and those resident in non-western countries were more likely to be abused. Emotional abuse was the most prevalent elder abuse subtype and financial abuse was less commonly reported by third parties or caregivers. Heterogeneity in the prevalence was due to the high proportion of married older adults in the sample. Subgroup analysis showed that cultural factors, subtypes of abuse, and gender also contributed to heterogeneity in the pooled prevalence of elder abuse.

  15. Female urethral carcinoma

    International Nuclear Information System (INIS)

    Saitoh, Masahiko; Kondo, Atsuo; Sakakibara, Toshihumi

    1988-01-01

    Urethral carcinoma in 2 females has been treated with irradiation together with adjunct chemotherapy. In case 1, a 73-year-old female with squamous cell carcinoma was successfully treated with irradiation of 4,000 rad and peplomycin of 60 mg intravenously given. She has been free from the disease for the past 43 months. In case 2, a 61-year-old female with transitional cell carcinoma was initially treated with irradiation of 5,000 rad together with peplomycin 90 mg, which was followed by another 5,000 rad irradiation. The tumor recurred and the patient was operated on for cystourethrectomy and partial resection of the vagina. A further chemotherapy of cisplatin, peplomycin, and mitomycin C was instituted. She died of the tumor recurrence 23 months after the first visit to our clinic. Diagnosis and treatment modalities on the female urethral carcinoma are briefly discussed. (author)

  16. Female Reproductive System

    Science.gov (United States)

    ... of the Female Reproductive System Print en español Sistema reproductor femenino About Human Reproduction All living things ... of Use Notice of Nondiscrimination Visit the Nemours Web site. Note: All information on KidsHealth® is for ...

  17. Female pattern baldness

    Science.gov (United States)

    Alopecia in women; Baldness - female; Hair loss in women; Androgenetic alopecia in women; Hereditary balding or thinning in women ... in the skin called a follicle. In general, baldness occurs when the hair follicle shrinks over time, ...

  18. Female Athlete Triad

    Science.gov (United States)

    ... for some competitive female athletes, problems such as low self-esteem, a tendency toward perfectionism, and family stress place ... depression, pressure from coaches or family members, or low self-esteem and can help her find ways to deal ...

  19. Bodily integrity and male and female circumcision.

    NARCIS (Netherlands)

    Dekkers, W.J.M.; Hoffer, C.; Wils, J.P.

    2005-01-01

    This paper explores the ambiguous notion of bodily integrity, focusing on male and female circumcision. In the empirical part of the study we describe and analyse the various meanings that are given to the notion of bodily integrity by people in their daily lives. In the philosophical part we

  20. Redefining Female Desire: Angela Carter's Bloody Chamber

    Directory of Open Access Journals (Sweden)

    Sabrina Antonella Abeni

    2014-03-01

    This article analyses some passages of those tales, combining them with the ideas expressed by the author in her famous essay, demonstrating the originality and unconventionality of her interpretation of female desire, subject to misunderstanding and disputes, but strongly appreciated in recent years .

  1. Female Directors on Corporate Boards: Does Female Leadership Drive Corporate Environmental Transparency?

    Directory of Open Access Journals (Sweden)

    Phua Michelle Siew Huei

    2017-01-01

    Full Text Available This paper examines the role of female directors on corporate boardroom on the extent of corporate environmental disclosure (CED of 260 Malaysian listed companies in year 2013. Resource dependence theory is utilized as the theoretical framework to explain the role of female directors on corporate boards. Content analysis is employed to gauge the extent of CED based on a self-constructed index that is derived from Global Reporting Initiatives (GRI and prior studies. Multiple regression is conducted and findings revealed that female directors– presence and female holding multiple directorships to be significant predictors of extent of CED. The findings lend support to the resource dependence theory on the contribution of board gender diversity and are useful for both policy makers and regulators.

  2. Female Sex Tourism

    OpenAIRE

    Mc Intyre, Maria Kleivan

    2017-01-01

    ABSTRACT This project explores the phenomenon of North American and Western European women, who travel to the Global South and engage in sexual encounters with the local men. This project has positioned itself as a postcolonial critique, arguing that female sex tourism is a form of neocolonialism. It has also investigated the term romance tourism, where it has found that as a result of essentialist gender stereotyping, the female version of sex tourism has been titled ‘romance tourism’. The p...

  3. Female physicist doctoral experiences

    OpenAIRE

    Katherine P. Dabney; Robert H. Tai

    2013-01-01

    The underrepresentation of women in physics doctorate programs and in tenured academic positions indicates a need to evaluate what may influence their career choice and persistence. This qualitative paper examines eleven females in physics doctoral programs and professional science positions in order to provide a more thorough understanding of why and how women make career choices based on aspects both inside and outside of school and their subsequent interaction. Results indicate that female...

  4. The lonely female partner

    DEFF Research Database (Denmark)

    Bruun, Poul; Pedersen, Birthe D; Osther, Palle J

    2011-01-01

    The aim of this qualitative study was to investigate the experiences of female partners to men with prostate cancer. The women found the capacity to manage their lives through mutual love in the family and through their faith.......The aim of this qualitative study was to investigate the experiences of female partners to men with prostate cancer. The women found the capacity to manage their lives through mutual love in the family and through their faith....

  5. Female pattern hair loss

    Directory of Open Access Journals (Sweden)

    İdil Ünal

    2014-06-01

    Full Text Available Female androgenetic alopecia is the commonest cause of hair loss in women. It is characterized by a diffuse reduction in hair density over the crown and frontal scalp with retention of the frontal hairline and a characteristic pattern distribution in genetically predisposed women. Because of the uncertain relationship with the androgens Female Pattern Hair Loss (FPHL is the most preferred definition of the condition. This review has been focused on the clinical features, diagnosis and treatment alternatives of FPHL.

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

    Science.gov (United States)

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

    2015-10-01

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

  7. Regression analysis using dependent Polya trees.

    Science.gov (United States)

    Schörgendorfer, Angela; Branscum, Adam J

    2013-11-30

    Many commonly used models for linear regression analysis force overly simplistic shape and scale constraints on the residual structure of data. We propose a semiparametric Bayesian model for regression analysis that produces data-driven inference by using a new type of dependent Polya tree prior to model arbitrary residual distributions that are allowed to evolve across increasing levels of an ordinal covariate (e.g., time, in repeated measurement studies). By modeling residual distributions at consecutive covariate levels or time points using separate, but dependent Polya tree priors, distributional information is pooled while allowing for broad pliability to accommodate many types of changing residual distributions. We can use the proposed dependent residual structure in a wide range of regression settings, including fixed-effects and mixed-effects linear and nonlinear models for cross-sectional, prospective, and repeated measurement data. A simulation study illustrates the flexibility of our novel semiparametric regression model to accurately capture evolving residual distributions. In an application to immune development data on immunoglobulin G antibodies in children, our new model outperforms several contemporary semiparametric regression models based on a predictive model selection criterion. Copyright © 2013 John Wiley & Sons, Ltd.

  8. Is past life regression therapy ethical?

    Science.gov (United States)

    Andrade, Gabriel

    2017-01-01

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

  9. Progression and regression of atherosclerosis in APOE3-Leiden transgenic mice : An immunohistochemical study

    NARCIS (Netherlands)

    Gijbels, M.J.J.; Cammen, M. van der; Laan, L.J.W. van der; Emeis, J.J.; Havekes, L.M.; Hofker, M.H.; Kraal, G.

    1999-01-01

    Apolipoprotein E3-Leiden (APOE3-Leiden) transgenic mice develop hyperlipidemia and are highly susceptible to diet-induced atherosclerosis. We have studied the progression and regression of atherosclerosis using immunohistochemistry. Female transgenic mice were fed a moderate fat diet to study

  10. Motivation Factors for Female Entrepreneurship in Mexico

    Directory of Open Access Journals (Sweden)

    Martha Cantú Cavada

    2017-09-01

    Full Text Available Objective: The objective of this paper is to analyse motivation factors for female entrepreneurship in Mexico. In the proposed article, the authors discuss the factors which compelled women to start their enterprises in Mexico. Research Design & Methods: Based on in-depth interviews with female entrepreneurs and entrepreneurship experts, the authors show which factors motivated women to start their own business in Mexico. Findings: The study proves that women in Mexico are motivated by a combination of push and pull factors, where the majority of the factors are pull factors. The findings of the study help to conclude that female entrepreneurship development is influenced by different factors including the entrepreneurs’ personal traits, social and economic factors. Due to their conservative traditional attitude, risk adverse tendency, and non-cooperation of family members, etc. women entrepreneurs are sometimes deterred to start a business in Mexico. Implications & Recommendations: It is necessary to raise the awareness of different factors that promote female entrepreneurship in Mexico. Governmental programmes which support female entrepreneurship, business incubators, and networking could be very helpful for women when starting their own business. Contribution & Value Added: The originality of this work lies in studying motivational factors for female entrepreneurship in Mexico. The Mexican society faces a big revolution towards female entrepreneurship. Based on the change of family structure and traditions, women nowadays are having more opportunities to develop as entrepreneurs.

  11. Female Sex Offenders: Public Awareness and Attributions.

    Science.gov (United States)

    Cain, Calli M; Anderson, Amy L

    2016-12-01

    Traditional gender roles, sex scripts, and the way female sex offenders are portrayed in the media may lead to misconceptions about who can commit sexual offenses. Sexual crimes by women may go unnoticed or unreported if there is a general lack of awareness that females commit these crimes. Data from the 2012 Nebraska Annual Social Indicators Survey were used to determine whether the public perceives women as capable sex offenders and the perceived causes of female sex offending. The traditional focus on male sex offenders by researchers, media, and politicians, in addition to gender stereotypes, introduces the possibility of group differences (e.g., between men and women) in perceptions of female sex offenders. Consequently, two secondary analyses were conducted that tested for group differences in both the public's perception of whether females can commit sex offenses and the explanations selected for why females sexually offend. The findings suggest that the public does perceive women as capable sex offenders, although there were group differences in the causal attributions for female sex offending.

  12. Female genital cutting.

    Science.gov (United States)

    Perron, Liette; Senikas, Vyta; Burnett, Margaret; Davis, Victoria

    2013-11-01

    To strengthen the national framework for care of adolescents and women affected by female genital cutting (FGC) in Canada by providing health care professionals with: (1) information intended to strengthen their knowledge and understanding of the practice; (2) directions with regard to the legal issues related to the practice; (3) clinical guidelines for the management of obstetric and gynaecological care, including FGC related complications; and (4) guidance on the provision of culturally competent care to adolescents and women with FGC. Published literature was retrieved through searches of PubMed, CINAHL, and The Cochrane Library in September 2010 using appropriate controlled vocabulary (e.g., Circumcision, Female) and keywords (e.g., female genital mutilation, clitoridectomy, infibulation). We also searched Social Science Abstracts, Sociological Abstracts, Gender Studies Database, and ProQuest Dissertations and Theses in 2010 and 2011. There were no date or language restrictions. Searches were updated on a regular basis and incorporated in the guideline to December 2011. Grey (unpublished) literature was identified through searching the websites of health technology assessment and health technology-related agencies, clinical practice guideline collections, clinical trial registries, and national and international medical specialty societies. The quality of evidence in this document was rated using the criteria described in the Report of the Canadian Task Force on Preventive Health Care (Table 1). Summary Statements 1. Female genital cutting is internationally recognized as a harmful practice and a violation of girls' and women's rights to life, physical integrity, and health. (II-3) 2. The immediate and long-term health risks and complications of female genital cutting can be serious and life threatening. (II-3) 3. Female genital cutting continues to be practised in many countries, particularly in sub-Saharan Africa, Egypt, and Sudan. (II-3) 4. Global migration

  13. Interpret with caution: multicollinearity in multiple regression of cognitive data.

    Science.gov (United States)

    Morrison, Catriona M

    2003-08-01

    Shibihara and Kondo in 2002 reported a reanalysis of the 1997 Kanji picture-naming data of Yamazaki, Ellis, Morrison, and Lambon-Ralph in which independent variables were highly correlated. Their addition of the variable visual familiarity altered the previously reported pattern of results, indicating that visual familiarity, but not age of acquisition, was important in predicting Kanji naming speed. The present paper argues that caution should be taken when drawing conclusions from multiple regression analyses in which the independent variables are so highly correlated, as such multicollinearity can lead to unreliable output.

  14. Preference learning with evolutionary Multivariate Adaptive Regression Spline model

    DEFF Research Database (Denmark)

    Abou-Zleikha, Mohamed; Shaker, Noor; Christensen, Mads Græsbøll

    2015-01-01

    This paper introduces a novel approach for pairwise preference learning through combining an evolutionary method with Multivariate Adaptive Regression Spline (MARS). Collecting users' feedback through pairwise preferences is recommended over other ranking approaches as this method is more appealing...... for function approximation as well as being relatively easy to interpret. MARS models are evolved based on their efficiency in learning pairwise data. The method is tested on two datasets that collectively provide pairwise preference data of five cognitive states expressed by users. The method is analysed...

  15. Nonparametric regression using the concept of minimum energy

    International Nuclear Information System (INIS)

    Williams, Mike

    2011-01-01

    It has recently been shown that an unbinned distance-based statistic, the energy, can be used to construct an extremely powerful nonparametric multivariate two sample goodness-of-fit test. An extension to this method that makes it possible to perform nonparametric regression using multiple multivariate data sets is presented in this paper. The technique, which is based on the concept of minimizing the energy of the system, permits determination of parameters of interest without the need for parametric expressions of the parent distributions of the data sets. The application and performance of this new method is discussed in the context of some simple example analyses.

  16. Publicizing female athletes' weights: implications for female psychology undergraduates acting as spectators.

    Science.gov (United States)

    Holm-Denoma, Jill; Smith, April; Waesche, Matthew

    2014-09-01

    The purpose of this study was to examine the effects of including female athletes' weights in athletic event programs on female spectators' body image, eating disorder symptoms, self-esteem, and affective state and to investigate whether the magnitude of the athletes' reported weights had differential effects on female spectators (i.e., do female spectators who view heavier athletes respond differently than those who view less heavy athletes?). We used an experimental design to examine hypotheses derived from competing theories to determine whether exposure to female athletes of varying weight would adversely or beneficially impact female undergraduates (N = 152) who served as athletic event spectators. Analyses indicated that in this simulated study, female spectators' body image, eating disorder symptoms, self-esteem, and affective states were not impacted by the presence or by the magnitude of female athletes' weights in athletic event programs. The results imply that including athletes' weights in game-day programs at women's athletic events does not affect female spectators on an individual level.

  17. Male sexual harassment alters female social behaviour towards other females.

    Science.gov (United States)

    Darden, Safi K; Watts, Lauren

    2012-04-23

    Male harassment of females to gain mating opportunities is a consequence of an evolutionary conflict of interest between the sexes over reproduction and is common among sexually reproducing species. Male Trinidadian guppies Poecilia reticulata spend a large proportion of their time harassing females for copulations and their presence in female social groups has been shown to disrupt female-female social networks and the propensity for females to develop social recognition based on familiarity. In this study, we investigate the behavioural mechanisms that may lead to this disruption of female sociality. Using two experiments, we test the hypothesis that male presence will directly affect social behaviours expressed by females towards other females in the population. In experiment one, we tested for an effect of male presence on female shoaling behaviour and found that, in the presence of a free-swimming male guppy, females spent shorter amounts of time with other females than when in the presence of a free-swimming female guppy. In experiment two, we tested for an effect of male presence on the incidence of aggressive behaviour among female guppies. When males were present in a shoal, females exhibited increased levels of overall aggression towards other females compared with female only shoals. Our work provides direct evidence that the presence of sexually harassing males alters female-female social behaviour, an effect that we expect will be recurrent across taxonomic groups.

  18. On Solving Lq-Penalized Regressions

    Directory of Open Access Journals (Sweden)

    Tracy Zhou Wu

    2007-01-01

    Full Text Available Lq-penalized regression arises in multidimensional statistical modelling where all or part of the regression coefficients are penalized to achieve both accuracy and parsimony of statistical models. There is often substantial computational difficulty except for the quadratic penalty case. The difficulty is partly due to the nonsmoothness of the objective function inherited from the use of the absolute value. We propose a new solution method for the general Lq-penalized regression problem based on space transformation and thus efficient optimization algorithms. The new method has immediate applications in statistics, notably in penalized spline smoothing problems. In particular, the LASSO problem is shown to be polynomial time solvable. Numerical studies show promise of our approach.

  19. 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.

  20. Influence diagnostics in meta-regression model.

    Science.gov (United States)

    Shi, Lei; Zuo, ShanShan; Yu, Dalei; Zhou, Xiaohua

    2017-09-01

    This paper studies the influence diagnostics in meta-regression model including case deletion diagnostic and local influence analysis. We derive the subset deletion formulae for the estimation of regression coefficient and heterogeneity variance and obtain the corresponding influence measures. The DerSimonian and Laird estimation and maximum likelihood estimation methods in meta-regression are considered, respectively, to derive the results. Internal and external residual and leverage measure are defined. The local influence analysis based on case-weights perturbation scheme, responses perturbation scheme, covariate perturbation scheme, and within-variance perturbation scheme are explored. We introduce a method by simultaneous perturbing responses, covariate, and within-variance to obtain the local influence measure, which has an advantage of capable to compare the influence magnitude of influential studies from different perturbations. An example is used to illustrate the proposed methodology. Copyright © 2017 John Wiley & Sons, Ltd.

  1. Principal component regression for crop yield estimation

    CERN Document Server

    Suryanarayana, T M V

    2016-01-01

    This book highlights the estimation of crop yield in Central Gujarat, especially with regard to the development of Multiple Regression Models and Principal Component Regression (PCR) models using climatological parameters as independent variables and crop yield as a dependent variable. It subsequently compares the multiple linear regression (MLR) and PCR results, and discusses the significance of PCR for crop yield estimation. In this context, the book also covers Principal Component Analysis (PCA), a statistical procedure used to reduce a number of correlated variables into a smaller number of uncorrelated variables called principal components (PC). This book will be helpful to the students and researchers, starting their works on climate and agriculture, mainly focussing on estimation models. The flow of chapters takes the readers in a smooth path, in understanding climate and weather and impact of climate change, and gradually proceeds towards downscaling techniques and then finally towards development of ...

  2. Regression Models for Market-Shares

    DEFF Research Database (Denmark)

    Birch, Kristina; Olsen, Jørgen Kai; Tjur, Tue

    2005-01-01

    On the background of a data set of weekly sales and prices for three brands of coffee, this paper discusses various regression models and their relation to the multiplicative competitive-interaction model (the MCI model, see Cooper 1988, 1993) for market-shares. Emphasis is put on the interpretat......On the background of a data set of weekly sales and prices for three brands of coffee, this paper discusses various regression models and their relation to the multiplicative competitive-interaction model (the MCI model, see Cooper 1988, 1993) for market-shares. Emphasis is put...... on the interpretation of the parameters in relation to models for the total sales based on discrete choice models.Key words and phrases. MCI model, discrete choice model, market-shares, price elasitcity, regression model....

  3. Gender Gaps in Mathematics, Science and Reading Achievements in Muslim Countries: A Quantile Regression Approach

    Science.gov (United States)

    Shafiq, M. Najeeb

    2013-01-01

    Using quantile regression analyses, this study examines gender gaps in mathematics, science, and reading in Azerbaijan, Indonesia, Jordan, the Kyrgyz Republic, Qatar, Tunisia, and Turkey among 15-year-old students. The analyses show that girls in Azerbaijan achieve as well as boys in mathematics and science and overachieve in reading. In Jordan,…

  4. The analysis of nonstationary time series using regression, correlation and cointegration

    DEFF Research Database (Denmark)

    Johansen, Søren

    2012-01-01

    There are simple well-known conditions for the validity of regression and correlation as statistical tools. We analyse by examples the effect of nonstationarity on inference using these methods and compare them to model based inference using the cointegrated vector autoregressive model. Finally we...... analyse some monthly data from US on interest rates as an illustration of the methods...

  5. The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration

    Directory of Open Access Journals (Sweden)

    Søren Johansen

    2012-06-01

    Full Text Available There are simple well-known conditions for the validity of regression and correlation as statistical tools. We analyse by examples the effect of nonstationarity on inference using these methods and compare them to model based inference using the cointegrated vector autoregressive model. Finally we analyse some monthly data from US on interest rates as an illustration of the methods.

  6. Sexually transmitted infection screening uptake and knowledge of sexually transmitted infection symptoms among female sex workers participating in a community randomised trial in Peru.

    Science.gov (United States)

    Kohler, Pamela K; Campos, Pablo E; Garcia, Patricia J; Carcamo, Cesar P; Buendia, Clara; Hughes, James P; Mejia, Carolina; Garnett, Geoff P; Holmes, King K

    2016-04-01

    This study aims to evaluate condom use, sexually transmitted infection (STI) screening, and knowledge of STI symptoms among female sex workers in Peru associated with sex work venues and a community randomised trial of STI control. One component of the Peru PREVEN intervention conducted mobile-team outreach to female sex workers to reduce STIs and increase condom use and access to government clinics for STI screening and evaluation. Prevalence ratios were calculated using multivariate Poisson regression models with robust standard errors, clustering by city. As-treated analyses were conducted to assess outcomes associated with reported exposure to the intervention. Care-seeking was more frequent in intervention communities, but differences were not statistically significant. Female sex workers reporting exposure to the intervention had a significantly higher likelihood of condom use, STI screening at public health clinics, and symptom recognition compared to those not exposed. Compared with street- or bar-based female sex workers, brothel-based female sex workers reported significantly higher rates of condom use with last client, recent screening exams for STIs, and HIV testing. Brothel-based female sex workers also more often reported knowledge of STIs and recognition of STI symptoms in women and in men. Interventions to promote STI detection and prevention among female sex workers in Peru should consider structural or regulatory factors related to sex work venues. © The Author(s) 2015.

  7. Female married illiteracy as the most important continual determinant of total fertility rate among districts of Empowered Action Group States of India: Evidence from Annual Health Survey 2011–12

    Directory of Open Access Journals (Sweden)

    Rajesh Kumar

    2017-01-01

    Full Text Available Background: District level determinants of total fertility rate in Empowered Action Group states of India can help in ongoing population stabilization programs in India. Objective: Present study intends to assess the role of district level determinants in predicting total fertility rate among districts of the Empowered Action Group states of India. Material and Methods: Data from Annual Health Survey (2011-12 was analysed using STATA and R software packages. Multiple linear regression models were built and evaluated using Akaike Information Criterion. For further understanding, recursive partitioning was used to prepare a regression tree. Results: Female married illiteracy positively associated with total fertility rate and explained more than half (53% of variance. Under multiple linear regression model, married illiteracy, infant mortality rate, Ante natal care registration, household size, median age of live birth and sex ratio explained 70% of total variance in total fertility rate. In regression tree, female married illiteracy was the root node and splits at 42% determined TFR = 2.7. The next left side branch was again married illiteracy with splits at 23% to determine TFR = 2.1. Conclusion: We conclude that female married illiteracy is one of the most important determinants explaining total fertility rate among the districts of an Empowered Action Group states. Focus on female literacy is required to stabilize the population growth in long run.

  8. Beliefs and attitudes of male and female adolescents and the risk of smoking behavior.

    Science.gov (United States)

    Kasim, K; Al-Zalabani, A; Abd El-Moneim, E S; Abd El-Moneim, S

    2016-01-01

    Adolescent smoking relates to numerous risk factors, of which beliefs and attitudes toward smoking may play a role. The study aimed to investigate the association between beliefs and attitudes and the risk of adolescent smoking. In a school-based cross-sectional study, 3,400 students were recruited from 34 intermediate and secondary schools in Madinah City, Al Madinah Region, Saudi Arabia. Data about sociodemographics, smoking-related factors, and beliefs and attitudes toward smoking were collected using a valid and reliable self-administered questionnaire. Prevalence of smoking was estimated and the studied beliefs and attitudes were compared by smoking status and sex using appropriate statistical analyses including multivariate logistic regression. Of the 3,322 respondents, 33.02% (38.9% males and 26.4% females) were current smokers. Beliefs and attitudes toward smoking significantly differed between smokers and nonsmokers in the studied male and female students. The adjusted risk of smoking was significantly increased among female adolescents who believed that male smokers were more attractive [odds ratio (OR) = 2.2; 95% confidence interval (CI) = 1.6-2.9] and among male smokers who believed that female smokers are more attractive (OR = 1.7; 95% CI = 1.2-2.2). The risk was also increased among all adolescents who believed that smoking lent comfort in social gatherings. Belief that smoking is harmful, however, was negatively associated with the risk of smoking, particularly among females (OR = 0.55; 95% CI = 0.35-0.91). The study revealed a considerable high prevalence of smoking among male and female adolescents. Addressing the beliefs and knowledge about smoking during childhood is crucial in any antismoking program.

  9. Neural correlates of moral and non-moral emotion in female psychopathy

    Directory of Open Access Journals (Sweden)

    Carla L Harenski

    2014-09-01

    Full Text Available This study presents the first neuroimaging investigation of female psychopathy in an incarcerated population. Prior studies have found that male psychopathy is associated with reduced limbic and paralimbic activation when processing emotional stimuli and making moral judgments. The goal of this study was to investigate whether these findings extend to female psychopathy. During fMRI scanning, 157 incarcerated and 46 non-incarcerated female participants viewed unpleasant pictures, half which depicted moral transgressions, and neutral pictures. Participants rated each picture on moral transgression severity. Psychopathy was assessed using the Psychopathy Checklist-Revised (PCL-R in all incarcerated participants. Non-incarcerated participants were included as a control group to derive brain regions of interest associated with viewing unpleasant versus neutral pictures (emotion contrast, and unpleasant pictures depicting moral transgressions versus unpleasant pictures without moral transgressions (moral contrast. Regression analyses in the incarcerated group examined the association between PCL-R scores and brain activation in the emotion and moral contrasts. Results of the emotion contrast revealed a negative correlation between PCL-R scores and activation in the right amygdala and rostral anterior cingulate. Results of the moral contrast revealed a negative correlation between PCL-R scores and activation in the right temporo-parietal junction. These results indicate that female psychopathy, like male psychopathy, is characterized by reduced limbic activation during emotion processing. In contrast, reduced temporo-parietal activation to moral transgressions has been less observed in male psychopathy. These results extend prior findings in male psychopathy to female psychopathy, and reveal aberrant neural responses to morally-salient stimuli that may be unique to female psychopathy.

  10. Beliefs and attitudes of male and female adolescents and the risk of smoking behavior

    Directory of Open Access Journals (Sweden)

    K Kasim

    2016-01-01

    Full Text Available Background: Adolescent smoking relates to numerous risk factors, of which beliefs and attitudes toward smoking may play a role. The study aimed to investigate the association between beliefs and attitudes and the risk of adolescent smoking. Materials and Methods: In a school-based cross-sectional study, 3,400 students were recruited from 34 intermediate and secondary schools in Madinah City, Al Madinah Region, Saudi Arabia. Data about sociodemographics, smoking-related factors, and beliefs and attitudes toward smoking were collected using a valid and reliable self-administered questionnaire. Prevalence of smoking was estimated and the studied beliefs and attitudes were compared by smoking status and sex using appropriate statistical analyses including multivariate logistic regression. Results: Of the 3,322 respondents, 33.02% (38.9% males and 26.4% females were current smokers. Beliefs and attitudes toward smoking significantly differed between smokers and nonsmokers in the studied male and female students. The adjusted risk of smoking was significantly increased among female adolescents who believed that male smokers were more attractive [odds ratio (OR = 2.2; 95% confidence interval (CI = 1.6-2.9] and among male smokers who believed that female smokers are more attractive (OR = 1.7; 95% CI = 1.2-2.2. The risk was also increased among all adolescents who believed that smoking lent comfort in social gatherings. Belief that smoking is harmful, however, was negatively associated with the risk of smoking, particularly among females (OR = 0.55; 95% CI = 0.35-0.91. Conclusions: The study revealed a considerable high prevalence of smoking among male and female adolescents. Addressing the beliefs and knowledge about smoking during childhood is crucial in any antismoking program.

  11. Cessation-related weight concern among homeless male and female smokers.

    Science.gov (United States)

    Pinsker, Erika Ashley; Hennrikus, Deborah Jane; Erickson, Darin J; Call, Kathleen Thiede; Forster, Jean Lois; Okuyemi, Kolawole Stephen

    2017-09-01

    Concern about post-cessation weight gain is a barrier to making attempts to quit smoking; however, its effect on smoking cessation is unclear. In this study we examine cessation-related weight concern among the homeless, which hasn't been studied. Homeless males (n = 320) and females (n = 110) participating in a smoking cessation RCT in the Twin Cities, Minnesota from 2009 to 2011 completed surveys on cessation-related weight concern, smoking status, and components from the Behavioral Model for Vulnerable Populations. Generalized estimating equations were used to examine baseline predictors of cessation-related weight concern at baseline, the end of treatment, and 26-weeks follow-up. Logistic regression models were used to examine the relationship between cessation-related weight concern and smoking status at the end of treatment and follow-up. Females had higher cessation-related weight concern than males. Among males, older age, Black race, higher BMI, depression, and having health insurance were associated with higher cessation-related weight concern. Among females, nicotine dependence, greater cigarette consumption, indicating quitting is more important, older age of smoking initiation, and less support to quit from family were associated with higher cessation-related weight concern. In multivariate analyses, cessation-related weight concern decreased over time among females. Cessation-related weight concern wasn't associated with smoking cessation. Although several types of characteristics predicted cessation-related weight concern among males, only smoking characteristics predicted cessation-related weight concern among females. Given the small proportion of quitters in this study (8% of males and 5% of females), further research on the impact of cessation-related weight concern on smoking cessation among the homeless is warranted.

  12. 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

  13. Removing Malmquist bias from linear regressions

    Science.gov (United States)

    Verter, Frances

    1993-01-01

    Malmquist bias is present in all astronomical surveys where sources are observed above an apparent brightness threshold. Those sources which can be detected at progressively larger distances are progressively more limited to the intrinsically luminous portion of the true distribution. This bias does not distort any of the measurements, but distorts the sample composition. We have developed the first treatment to correct for Malmquist bias in linear regressions of astronomical data. A demonstration of the corrected linear regression that is computed in four steps is presented.

  14. 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

  15. 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.

  16. Laser Beam Focus Analyser

    DEFF Research Database (Denmark)

    Nielsen, Peter Carøe; Hansen, Hans Nørgaard; Olsen, Flemming Ove

    2007-01-01

    the obtainable features in direct laser machining as well as heat affected zones in welding processes. This paper describes the development of a measuring unit capable of analysing beam shape and diameter of lasers to be used in manufacturing processes. The analyser is based on the principle of a rotating......The quantitative and qualitative description of laser beam characteristics is important for process implementation and optimisation. In particular, a need for quantitative characterisation of beam diameter was identified when using fibre lasers for micro manufacturing. Here the beam diameter limits...... mechanical wire being swept through the laser beam at varying Z-heights. The reflected signal is analysed and the resulting beam profile determined. The development comprised the design of a flexible fixture capable of providing both rotation and Z-axis movement, control software including data capture...

  17. Contesting Citizenship: Comparative Analyses

    DEFF Research Database (Denmark)

    Siim, Birte; Squires, Judith

    2007-01-01

    importance of particularized experiences and multiple ineequality agendas). These developments shape the way citizenship is both practiced and analysed. Mapping neat citizenship modles onto distinct nation-states and evaluating these in relation to formal equality is no longer an adequate approach....... Comparative citizenship analyses need to be considered in relation to multipleinequalities and their intersections and to multiple governance and trans-national organisinf. This, in turn, suggests that comparative citizenship analysis needs to consider new spaces in which struggles for equal citizenship occur...

  18. Demonstration of a Fiber Optic Regression Probe

    Science.gov (United States)

    Korman, Valentin; Polzin, Kurt A.

    2010-01-01

    The capability to provide localized, real-time monitoring of material regression rates in various applications has the potential to provide a new stream of data for development testing of various components and systems, as well as serving as a monitoring tool in flight applications. These applications include, but are not limited to, the regression of a combusting solid fuel surface, the ablation of the throat in a chemical rocket or the heat shield of an aeroshell, and the monitoring of erosion in long-life plasma thrusters. The rate of regression in the first application is very fast, while the second and third are increasingly slower. A recent fundamental sensor development effort has led to a novel regression, erosion, and ablation sensor technology (REAST). The REAST sensor allows for measurement of real-time surface erosion rates at a discrete surface location. The sensor is optical, using two different, co-located fiber-optics to perform the regression measurement. The disparate optical transmission properties of the two fiber-optics makes it possible to measure the regression rate by monitoring the relative light attenuation through the fibers. As the fibers regress along with the parent material in which they are embedded, the relative light intensities through the two fibers changes, providing a measure of the regression rate. The optical nature of the system makes it relatively easy to use in a variety of harsh, high temperature environments, and it is also unaffected by the presence of electric and magnetic fields. In addition, the sensor could be used to perform optical spectroscopy on the light emitted by a process and collected by fibers, giving localized measurements of various properties. The capability to perform an in-situ measurement of material regression rates is useful in addressing a variety of physical issues in various applications. An in-situ measurement allows for real-time data regarding the erosion rates, providing a quick method for

  19. Kinematic gait analyses in healthy Golden Retrievers

    OpenAIRE

    Silva, Gabriela C.A.; Cardoso, Mariana Trés; Gaiad, Thais P.; Brolio, Marina P.; Oliveira, Vanessa C.; Assis Neto, Antonio; Martins, Daniele S.; Ambrósio, Carlos E.

    2014-01-01

    Kinematic analysis relates to the relative movement between rigid bodies and finds application in gait analysis and other body movements, interpretation of their data when there is change, determines the choice of treatment to be instituted. The objective of this study was to standardize the march of Dog Golden Retriever Healthy to assist in the diagnosis and treatment of musculoskeletal disorders. We used a kinematic analysis system to analyse the gait of seven dogs Golden Retriever, female,...

  20. Female physicist doctoral experiences

    Directory of Open Access Journals (Sweden)

    Katherine P. Dabney

    2013-04-01

    Full Text Available The underrepresentation of women in physics doctorate programs and in tenured academic positions indicates a need to evaluate what may influence their career choice and persistence. This qualitative paper examines eleven females in physics doctoral programs and professional science positions in order to provide a more thorough understanding of why and how women make career choices based on aspects both inside and outside of school and their subsequent interaction. Results indicate that female physicists experience conflict in achieving balance within their graduate school experiences and personal lives and that this then influences their view of their future careers and possible career choices. Female physicists report both early and long-term support outside of school by family, and later departmental support, as being essential to their persistence within the field. A greater focus on informal and out-of-school science activities for females, especially those that involve family members, early in life may help influence their entrance into a physics career later in life. Departmental support, through advisers, mentors, peers, and women’s support groups, with a focus on work-life balance can help females to complete graduate school and persist into an academic career.

  1. Female physicist doctoral experiences

    Science.gov (United States)

    Dabney, Katherine P.; Tai, Robert H.

    2013-06-01

    The underrepresentation of women in physics doctorate programs and in tenured academic positions indicates a need to evaluate what may influence their career choice and persistence. This qualitative paper examines eleven females in physics doctoral programs and professional science positions in order to provide a more thorough understanding of why and how women make career choices based on aspects both inside and outside of school and their subsequent interaction. Results indicate that female physicists experience conflict in achieving balance within their graduate school experiences and personal lives and that this then influences their view of their future careers and possible career choices. Female physicists report both early and long-term support outside of school by family, and later departmental support, as being essential to their persistence within the field. A greater focus on informal and out-of-school science activities for females, especially those that involve family members, early in life may help influence their entrance into a physics career later in life. Departmental support, through advisers, mentors, peers, and women’s support groups, with a focus on work-life balance can help females to complete graduate school and persist into an academic career.

  2. Female genital mutilation.

    Science.gov (United States)

    Ladjali, M; Rattray, T W; Walder, R J

    1993-08-21

    Female genital mutilation, also misleadingly known as female circumcision, is usually performed on girls ranging in from 1 week to puberty. Immediate physical complications include severe pain, shock, infection, bleeding, acute urinary infection, tetanus, and death. Longterm problems include chronic pain, difficulties with micturition and menstruation, pelvic infection leading to infertility, and prolonged and obstructed labor during childbirth. An estimated 80 million girls and women have undergone female genital mutilation. In Britain alone an estimated 10,000 girls are currently at risk. Religious, cultural, medical, and moral grounds rationalize the custom which is practiced primarily in sub-Saharan Africa, the Arab world, Malaysia, Indonesia, and among migrant populations in Western countries. According to WHO it is correlated with poverty, illiteracy, and the low status of women. Women who escape mutilation are not sought in marriage. WHO, the UN Population Fund, the UN Children's Fund, the International Planned Parenthood Federation, and the UN Convention on the Rights of the Child have issued declarations on the eradication of female genital mutilation. In Britain, local authorities have intervened to prevent parents from mutilating their daughters. In 1984, the Inter-African Committee Against Harmful Traditional Practices Affecting Women and Children was established to work toward eliminating female genital mutilation and other damaging customs. National committees in 26 African countries coordinate projects run by local people using theater, dance, music, and storytelling for communication. In Australia, Canada, Europe, and the US women have organized to prevent the practice among vulnerable migrants and refugees.

  3. Black Female Homicide Offenders and Victims: Are They from the Same Population?

    Science.gov (United States)

    McClain, Paula D.

    1982-01-01

    Explores the social and environmental characteristics of Black female homicide victims and offenders. Assembled data on 661 Black female homicide victims and 119 Black female homicide offenders. Analyses indicated that Black female homicide victims and offenders exhibit low socioeconomic status and essentially similar behavior patterns. (Author)

  4. Method for nonlinear exponential regression analysis

    Science.gov (United States)

    Junkin, B. G.

    1972-01-01

    Two computer programs developed according to two general types of exponential models for conducting nonlinear exponential regression analysis are described. Least squares procedure is used in which the nonlinear problem is linearized by expanding in a Taylor series. Program is written in FORTRAN 5 for the Univac 1108 computer.

  5. Measurement Error in Education and Growth Regressions

    NARCIS (Netherlands)

    Portela, Miguel; Alessie, Rob; Teulings, Coen

    2010-01-01

    The use of the perpetual inventory method for the construction of education data per country leads to systematic measurement error. This paper analyzes its effect on growth regressions. We suggest a methodology for correcting this error. The standard attenuation bias suggests that using these

  6. The M Word: Multicollinearity in Multiple Regression.

    Science.gov (United States)

    Morrow-Howell, Nancy

    1994-01-01

    Notes that existence of substantial correlation between two or more independent variables creates problems of multicollinearity in multiple regression. Discusses multicollinearity problem in social work research in which independent variables are usually intercorrelated. Clarifies problems created by multicollinearity, explains detection of…

  7. Regression Discontinuity Designs Based on Population Thresholds

    DEFF Research Database (Denmark)

    Eggers, Andrew C.; Freier, Ronny; Grembi, Veronica

    In many countries, important features of municipal government (such as the electoral system, mayors' salaries, and the number of councillors) depend on whether the municipality is above or below arbitrary population thresholds. Several papers have used a regression discontinuity design (RDD...

  8. Deriving the Regression Line with Algebra

    Science.gov (United States)

    Quintanilla, John A.

    2017-01-01

    Exploration with spreadsheets and reliance on previous skills can lead students to determine the line of best fit. To perform linear regression on a set of data, students in Algebra 2 (or, in principle, Algebra 1) do not have to settle for using the mysterious "black box" of their graphing calculators (or other classroom technologies).…

  9. Piecewise linear regression splines with hyperbolic covariates

    International Nuclear Information System (INIS)

    Cologne, John B.; Sposto, Richard

    1992-09-01

    Consider the problem of fitting a curve to data that exhibit a multiphase linear response with smooth transitions between phases. We propose substituting hyperbolas as covariates in piecewise linear regression splines to obtain curves that are smoothly joined. The method provides an intuitive and easy way to extend the two-phase linear hyperbolic response model of Griffiths and Miller and Watts and Bacon to accommodate more than two linear segments. The resulting regression spline with hyperbolic covariates may be fit by nonlinear regression methods to estimate the degree of curvature between adjoining linear segments. The added complexity of fitting nonlinear, as opposed to linear, regression models is not great. The extra effort is particularly worthwhile when investigators are unwilling to assume that the slope of the response changes abruptly at the join points. We can also estimate the join points (the values of the abscissas where the linear segments would intersect if extrapolated) if their number and approximate locations may be presumed known. An example using data on changing age at menarche in a cohort of Japanese women illustrates the use of the method for exploratory data analysis. (author)

  10. Targeting: Logistic Regression, Special Cases and Extensions

    Directory of Open Access Journals (Sweden)

    Helmut Schaeben

    2014-12-01

    Full Text Available Logistic regression is a classical linear model for logit-transformed conditional probabilities of a binary target variable. It recovers the true conditional probabilities if the joint distribution of predictors and the target is of log-linear form. Weights-of-evidence is an ordinary logistic regression with parameters equal to the differences of the weights of evidence if all predictor variables are discrete and conditionally independent given the target variable. The hypothesis of conditional independence can be tested in terms of log-linear models. If the assumption of conditional independence is violated, the application of weights-of-evidence does not only corrupt the predicted conditional probabilities, but also their rank transform. Logistic regression models, including the interaction terms, can account for the lack of conditional independence, appropriate interaction terms compensate exactly for violations of conditional independence. Multilayer artificial neural nets may be seen as nested regression-like models, with some sigmoidal activation function. Most often, the logistic function is used as the activation function. If the net topology, i.e., its control, is sufficiently versatile to mimic interaction terms, artificial neural nets are able to account for violations of conditional independence and yield very similar results. Weights-of-evidence cannot reasonably include interaction terms; subsequent modifications of the weights, as often suggested, cannot emulate the effect of interaction terms.

  11. Functional data analysis of generalized regression quantiles

    KAUST Repository

    Guo, Mengmeng

    2013-11-05

    Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.

  12. Regression testing Ajax applications : Coping with dynamism

    NARCIS (Netherlands)

    Roest, D.; Mesbah, A.; Van Deursen, A.

    2009-01-01

    Note: This paper is a pre-print of: Danny Roest, Ali Mesbah and Arie van Deursen. Regression Testing AJAX Applications: Coping with Dynamism. In Proceedings of the 3rd International Conference on Software Testing, Verification and Validation (ICST’10), Paris, France. IEEE Computer Society, 2010.

  13. Group-wise partial least square regression

    NARCIS (Netherlands)

    Camacho, José; Saccenti, Edoardo

    2018-01-01

    This paper introduces the group-wise partial least squares (GPLS) regression. GPLS is a new sparse PLS technique where the sparsity structure is defined in terms of groups of correlated variables, similarly to what is done in the related group-wise principal component analysis. These groups are

  14. Functional data analysis of generalized regression quantiles

    KAUST Repository

    Guo, Mengmeng; Zhou, Lan; Huang, Jianhua Z.; Hä rdle, Wolfgang Karl

    2013-01-01

    Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.

  15. Finite Algorithms for Robust Linear Regression

    DEFF Research Database (Denmark)

    Madsen, Kaj; Nielsen, Hans Bruun

    1990-01-01

    The Huber M-estimator for robust linear regression is analyzed. Newton type methods for solution of the problem are defined and analyzed, and finite convergence is proved. Numerical experiments with a large number of test problems demonstrate efficiency and indicate that this kind of approach may...

  16. Function approximation with polynomial regression slines

    International Nuclear Information System (INIS)

    Urbanski, P.

    1996-01-01

    Principles of the polynomial regression splines as well as algorithms and programs for their computation are presented. The programs prepared using software package MATLAB are generally intended for approximation of the X-ray spectra and can be applied in the multivariate calibration of radiometric gauges. (author)

  17. Assessing risk factors for periodontitis using regression

    Science.gov (United States)

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

    2013-10-01

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

  18. Predicting Social Trust with Binary Logistic Regression

    Science.gov (United States)

    Adwere-Boamah, Joseph; Hufstedler, Shirley

    2015-01-01

    This study used binary logistic regression to predict social trust with five demographic variables from a national sample of adult individuals who participated in The General Social Survey (GSS) in 2012. The five predictor variables were respondents' highest degree earned, race, sex, general happiness and the importance of personally assisting…

  19. Yet another look at MIDAS regression

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans)

    2016-01-01

    textabstractA MIDAS regression involves a dependent variable observed at a low frequency and independent variables observed at a higher frequency. This paper relates a true high frequency data generating process, where also the dependent variable is observed (hypothetically) at the high frequency,

  20. Revisiting Regression in Autism: Heller's "Dementia Infantilis"

    Science.gov (United States)

    Westphal, Alexander; Schelinski, Stefanie; Volkmar, Fred; Pelphrey, Kevin

    2013-01-01

    Theodor Heller first described a severe regression of adaptive function in normally developing children, something he termed dementia infantilis, over one 100 years ago. Dementia infantilis is most closely related to the modern diagnosis, childhood disintegrative disorder. We translate Heller's paper, Uber Dementia Infantilis, and discuss…

  1. Fast multi-output relevance vector regression

    OpenAIRE

    Ha, Youngmin

    2017-01-01

    This paper aims to decrease the time complexity of multi-output relevance vector regression from O(VM^3) to O(V^3+M^3), where V is the number of output dimensions, M is the number of basis functions, and V

  2. Regression Equations for Birth Weight Estimation using ...

    African Journals Online (AJOL)

    In this study, Birth Weight has been estimated from anthropometric measurements of hand and foot. Linear regression equations were formed from each of the measured variables. These simple equations can be used to estimate Birth Weight of new born babies, in order to identify those with low birth weight and referred to ...

  3. Superquantile Regression: Theory, Algorithms, and Applications

    Science.gov (United States)

    2014-12-01

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

  4. transformation of independent variables in polynomial regression ...

    African Journals Online (AJOL)

    Ada

    preferable when possible to work with a simple functional form in transformed variables rather than with a more complicated form in the original variables. In this paper, it is shown that linear transformations applied to independent variables in polynomial regression models affect the t ratio and hence the statistical ...

  5. Multiple Linear Regression: A Realistic Reflector.

    Science.gov (United States)

    Nutt, A. T.; Batsell, R. R.

    Examples of the use of Multiple Linear Regression (MLR) techniques are presented. This is done to show how MLR aids data processing and decision-making by providing the decision-maker with freedom in phrasing questions and by accurately reflecting the data on hand. A brief overview of the rationale underlying MLR is given, some basic definitions…

  6. Risico-analyse brandstofpontons

    NARCIS (Netherlands)

    Uijt de Haag P; Post J; LSO

    2001-01-01

    Voor het bepalen van de risico's van brandstofpontons in een jachthaven is een generieke risico-analyse uitgevoerd. Er is een referentiesysteem gedefinieerd, bestaande uit een betonnen brandstofponton met een relatief grote inhoud en doorzet. Aangenomen is dat de ponton gelegen is in een

  7. Fast multichannel analyser

    Energy Technology Data Exchange (ETDEWEB)

    Berry, A; Przybylski, M M; Sumner, I [Science Research Council, Daresbury (UK). Daresbury Lab.

    1982-10-01

    A fast multichannel analyser (MCA) capable of sampling at a rate of 10/sup 7/ s/sup -1/ has been developed. The instrument is based on an 8 bit parallel encoding analogue to digital converter (ADC) reading into a fast histogramming random access memory (RAM) system, giving 256 channels of 64 k count capacity. The prototype unit is in CAMAC format.

  8. A fast multichannel analyser

    International Nuclear Information System (INIS)

    Berry, A.; Przybylski, M.M.; Sumner, I.

    1982-01-01

    A fast multichannel analyser (MCA) capable of sampling at a rate of 10 7 s -1 has been developed. The instrument is based on an 8 bit parallel encoding analogue to digital converter (ADC) reading into a fast histogramming random access memory (RAM) system, giving 256 channels of 64 k count capacity. The prototype unit is in CAMAC format. (orig.)

  9. Z linkage of female promiscuity genes in the moth Utetheisa ornatrix: support for the sexy-sperm hypothesis?

    Science.gov (United States)

    Iyengar, Vikram K; Reeve, Hudson K

    2010-05-01

    Female preference genes for large males in the highly promiscuous moth Utetheisa ornatrix (Lepidoptera: Arctiidae) have previously been shown to be mostly Z-linked, in accordance with the hypothesis that ZZ-ZW sex chromosome systems should facilitate Fisherian sexual selection. We determined the heritability of both female and male promiscuity in the highly promiscuous moth U. ornatrix (Lepidoptera: Arctiidae) through parent-offspring and grandparent-offspring regression analyses. Our data show that male promiscuity is not sex-limited and either autosomal or sex-linked whereas female promiscuity is primarily determined by sex-limited, Z-linked genes. These data are consistent with the "sexy-sperm hypothesis," which posits that multiple-mating and sperm competitiveness coevolve through a Fisherian-like process in which female promiscuity is a kind of mate choice in which sperm-competitiveness is the trait favored in males. Such a Fisherian process should also be more potent when female preferences are Z-linked and sex-limited than when autosomal or not limited.

  10. Female athlete triad update.

    Science.gov (United States)

    Beals, Katherine A; Meyer, Nanna L

    2007-01-01

    The passage of Title IX legislation in 1972 provided enormous opportunities for women to reap the benefits of sports participation. For most female athletes, sports participation is a positive experience, providing improved physical fitness, enhanced self-esteem, and better physical and mental health. Nonetheless, for a few female athletes, the desire for athletic success combined with the pressure to achieve a prescribed body weight may lead to the development of a triad of medical disorders including disordered eating, menstrual dysfunction, and low bone mineral density (BMD)--known collectively as the female athlete triad. Alone or in combination, the disorders of the triad can have a negative impact on health and impair athletic performance.

  11. Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

    Directory of Open Access Journals (Sweden)

    Minh Vu Trieu

    2017-03-01

    Full Text Available This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS, Brazilian tensile strength (BTS, rock brittleness index (BI, the distance between planes of weakness (DPW, and the alpha angle (Alpha between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP. Four (4 statistical regression models (two linear and two nonlinear are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2 of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

  12. Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

    Science.gov (United States)

    Minh, Vu Trieu; Katushin, Dmitri; Antonov, Maksim; Veinthal, Renno

    2017-03-01

    This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM) based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), rock brittleness index (BI), the distance between planes of weakness (DPW), and the alpha angle (Alpha) between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP). Four (4) statistical regression models (two linear and two nonlinear) are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2) of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

  13. Physics constrained nonlinear regression models for time series

    International Nuclear Information System (INIS)

    Majda, Andrew J; Harlim, John

    2013-01-01

    A central issue in contemporary science is the development of data driven statistical nonlinear dynamical models for time series of partial observations of nature or a complex physical model. It has been established recently that ad hoc quadratic multi-level regression (MLR) models can have finite-time blow up of statistical solutions and/or pathological behaviour of their invariant measure. Here a new class of physics constrained multi-level quadratic regression models are introduced, analysed and applied to build reduced stochastic models from data of nonlinear systems. These models have the advantages of incorporating memory effects in time as well as the nonlinear noise from energy conserving nonlinear interactions. The mathematical guidelines for the performance and behaviour of these physics constrained MLR models as well as filtering algorithms for their implementation are developed here. Data driven applications of these new multi-level nonlinear regression models are developed for test models involving a nonlinear oscillator with memory effects and the difficult test case of the truncated Burgers–Hopf model. These new physics constrained quadratic MLR models are proposed here as process models for Bayesian estimation through Markov chain Monte Carlo algorithms of low frequency behaviour in complex physical data. (paper)

  14. Spontaneous regression of intracranial malignant lymphoma. Case report

    Energy Technology Data Exchange (ETDEWEB)

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

    1988-05-01

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

  15. 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.

  16. Genetic evaluation of European quails by random regression models

    Directory of Open Access Journals (Sweden)

    Flaviana Miranda Gonçalves

    2012-09-01

    Full Text Available The objective of this study was to compare different random regression models, defined from different classes of heterogeneity of variance combined with different Legendre polynomial orders for the estimate of (covariance of quails. The data came from 28,076 observations of 4,507 female meat quails of the LF1 lineage. Quail body weights were determined at birth and 1, 14, 21, 28, 35 and 42 days of age. Six different classes of residual variance were fitted to Legendre polynomial functions (orders ranging from 2 to 6 to determine which model had the best fit to describe the (covariance structures as a function of time. According to the evaluated criteria (AIC, BIC and LRT, the model with six classes of residual variances and of sixth-order Legendre polynomial was the best fit. The estimated additive genetic variance increased from birth to 28 days of age, and dropped slightly from 35 to 42 days. The heritability estimates decreased along the growth curve and changed from 0.51 (1 day to 0.16 (42 days. Animal genetic and permanent environmental correlation estimates between weights and age classes were always high and positive, except for birth weight. The sixth order Legendre polynomial, along with the residual variance divided into six classes was the best fit for the growth rate curve of meat quails; therefore, they should be considered for breeding evaluation processes by random regression models.

  17. Quantile regression analysis of body mass and wages.

    Science.gov (United States)

    Johar, Meliyanni; Katayama, Hajime

    2012-05-01

    Using the National Longitudinal Survey of Youth 1979, we explore the relationship between body mass and wages. We use quantile regression to provide a broad description of the relationship across the wage distribution. We also allow the relationship to vary by the degree of social skills involved in different jobs. Our results find that for female workers body mass and wages are negatively correlated at all points in their wage distribution. The strength of the relationship is larger at higher-wage levels. For male workers, the relationship is relatively constant across wage distribution but heterogeneous across ethnic groups. When controlling for the endogeneity of body mass, we find that additional body mass has a negative causal impact on the wages of white females earning more than the median wages and of white males around the median wages. Among these workers, the wage penalties are larger for those employed in jobs that require extensive social skills. These findings may suggest that labor markets reward white workers for good physical shape differently, depending on the level of wages and the type of job a worker has. Copyright © 2011 John Wiley & Sons, Ltd.

  18. Tax System in Poland – Progressive or Regressive?

    Directory of Open Access Journals (Sweden)

    Jacek Tomkiewicz

    2016-03-01

    Full Text Available Purpose: To analyse the impact of the Polish fiscal regime on the general revenue of the country, and specifically to establish whether the cumulative tax burden borne by Polish households is progressive or regressive.Methodology: On the basis of Eurostat and OECD data, the author has analysed fiscal regimes in EU Member States and in OECD countries. The tax burden of households within different income groups has also been examined pursuant to applicable fiscal laws and data pertaining to the revenue and expenditure of households published by the Central Statistical Office (CSO.Conclusions: The fiscal regime in Poland is regressive; that is, the relative fiscal burden decreases as the taxpayer’s income increases.Research Implications: The article contributes to the on-going discussion on social cohesion, in particular with respect to economic policy instruments aimed at the redistribution of income within the economy.Originality: The author presents an analysis of data pertaining to fiscal policies in EU Member States and OECD countries and assesses the impact of the legal environment (fiscal regime and social security system in Poland on income distribution within the economy. The impact of the total tax burden (direct and indirect taxes, social security contributions on the economic situation of households from different income groups has been calculated using an original formula.

  19. Detecting overdispersion in count data: A zero-inflated Poisson regression analysis

    Science.gov (United States)

    Afiqah Muhamad Jamil, Siti; Asrul Affendi Abdullah, M.; Kek, Sie Long; Nor, Maria Elena; Mohamed, Maryati; Ismail, Norradihah

    2017-09-01

    This study focusing on analysing count data of butterflies communities in Jasin, Melaka. In analysing count dependent variable, the Poisson regression model has been known as a benchmark model for regression analysis. Continuing from the previous literature that used Poisson regression analysis, this study comprising the used of zero-inflated Poisson (ZIP) regression analysis to gain acute precision on analysing the count data of butterfly communities in Jasin, Melaka. On the other hands, Poisson regression should be abandoned in the favour of count data models, which are capable of taking into account the extra zeros explicitly. By far, one of the most popular models include ZIP regression model. The data of butterfly communities which had been called as the number of subjects in this study had been taken in Jasin, Melaka and consisted of 131 number of subjects visits Jasin, Melaka. Since the researchers are considering the number of subjects, this data set consists of five families of butterfly and represent the five variables involve in the analysis which are the types of subjects. Besides, the analysis of ZIP used the SAS procedure of overdispersion in analysing zeros value and the main purpose of continuing the previous study is to compare which models would be better than when exists zero values for the observation of the count data. The analysis used AIC, BIC and Voung test of 5% level significance in order to achieve the objectives. The finding indicates that there is a presence of over-dispersion in analysing zero value. The ZIP regression model is better than Poisson regression model when zero values exist.

  20. The New Strategic Imperative: Understanding the Female Business Traveler

    OpenAIRE

    Francine Newth

    2011-01-01

    This paper explores the characteristics, needs, and behaviors of women who travel on business and analyzes the data for potential segmentation. The study focuses exclusively on the female business traveler. The sample consists of 235 female business travelers from a variety of industries. The statistical methods include correlation analyses, factor analysis, and cluster analysis. The findings show that 6 factors explain 60.4% of the variance in characteristics, behaviors and needs of female b...

  1. Female Institutional Directors on Boards and Firm Value

    OpenAIRE

    Pucheta Martínez, María Consuelo; Bel Oms, Inmaculada; Olcina Sempere, Gustau

    2016-01-01

    The aim of this research is to examine what impact female institutional directors on boards have on corporate performance. Previous research shows that institutional female directors cannot be considered as a homogeneous group since they represent investors who may or may not maintain business relations with the companies on whose corporate boards they sit. Thus, it is not only the effect of female institutional directors as a whole on firm value that has been analysed, but also the impact of...

  2. 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.

  3. Representation and beyond : female victims in Post-Suharto media

    NARCIS (Netherlands)

    Sushartami, Wiwik

    2012-01-01

    This study analyses representations of female victims in post-Suharto media. In focusing on the discourse of female victimisation, it also underlines the import of the fall of the New Order regime and the opening of the media world in Indonesia at the same time. It selected notably prevalent and

  4. Female ethnicity: Understanding Muslim immigrant businesswomen in the Netherlands

    NARCIS (Netherlands)

    Essers, C.; Benschop, Y.W.M.; Doorewaard, J.A.C.M.

    2010-01-01

    Building on theories of intersectionality, in this article we develop the concept of female ethnicity in order to understand the meanings of femininity for Muslim immigrant businesswomen in the context of entrepreneurship. Through the notion of female ethnicity we analyse four life stories and

  5. Do (Female) Founders Influence (Female) Joiners to Become Founders too?

    DEFF Research Database (Denmark)

    Rocha, Vera; Van Praag, Mirjam

    -founder (gender) homophily affects the likelihood of female and male joiners to become founders themselves. We find a relatively large and robust positive effect among female joiners that can be attributed to the role modeling function of female founders. Female entrepreneurs hiring personnel may thus have...

  6. Iron status of toddlers, nonpregnant females, and pregnant females in the United States.

    Science.gov (United States)

    Gupta, Priya M; Hamner, Heather C; Suchdev, Parminder S; Flores-Ayala, Rafael; Mei, Zuguo

    2017-12-01

    Background: Total-body iron stores (TBI), which are calculated from serum ferritin and soluble transferrin receptor concentrations, can be used to assess the iron status of populations in the United States. Objective: This analysis, developed to support workshop discussions, describes the distribution of TBI and the prevalence of iron deficiency (ID) and ID anemia (IDA) among toddlers, nonpregnant females, and pregnant females. Design: We analyzed data from NHANES; toddlers aged 12-23 mo (NHANES 2003-2010), nonpregnant females aged 15-49 y (NHANES 2007-2010), and pregnant females aged 12-49 y (NHANES 1999-2010). We used SAS survey procedures to plot distributions of TBI and produce prevalence estimates of ID and IDA for each target population. All analyses were weighted to account for the complex survey design. Results: According to these data, ID prevalences (± SEs) were 15.1% ± 1.7%, 10.4% ± 0.5%, and 16.3% ± 1.3% in toddlers, nonpregnant females, and pregnant females, respectively. ID prevalence in pregnant females increased significantly with each trimester (5.3% ± 1.5%, 12.7% ± 2.3%, and 27.5% ± 3.5% in the first, second, and third trimesters, respectively). Racial disparities in the prevalence of ID among both nonpregnant and pregnant females exist, with Mexican American and non-Hispanic black females at greater risk of ID than non-Hispanic white females. IDA prevalence was 5.0% ± 0.4% and 2.6% ± 0.7% in nonpregnant and pregnant females, respectively. Conclusions: Available nationally representative data suggest that ID and IDA remain a concern in the United States. Estimates of iron-replete status cannot be made at this time in the absence of established cutoffs for iron repletion based on TBI. The study was registered at clinicaltrials.gov as NCT03274726. © 2017 American Society for Nutrition.

  7. Females and Toxic Leadership

    Science.gov (United States)

    2012-12-14

    labeled as toxic, can he or she be rehabilitated?; Are there leadership styles that can be promoted to combat toxic leadership?; and Are the senior...examines leadership styles that are favorable for female leaders, and offers Transformational/Adaptive leadership as a style promising rehabilitative tools

  8. Perspectives on Female Entrepreneurs

    DEFF Research Database (Denmark)

    Kuada, John Ernest; Janulevièienë, Rûta

    2003-01-01

    The aim of this paper is to compare the contents of the academic evidence and debate on female entrepreneurship in the West with the current stream of research and thinking in the Central and Eastern European Countries with a view to identifying similarities and differences in thoughts and findin...

  9. Female sexual dysfunction

    DEFF Research Database (Denmark)

    Giraldi, Annamaria; Wåhlin-Jacobsen, Sarah

    2016-01-01

    Female sexual dysfunction (FSD) is a controversial condition, which has prompted much debate regarding its aetiology, components, and even its existence. Our inability to work together as clinicians, psychologists, patients, and advocates hinders our understanding of FSD, and we will only improve...

  10. Female sexual arousal disorders

    NARCIS (Netherlands)

    Giraldi, Annamaria; Rellini, Alessandra H.; Pfaus, James; Laan, Ellen

    2013-01-01

    Definitions and terminology for female sexual arousal disorder (FSAD) are currently being debated. While some authors have suggested that FSAD is more a subjective response rather than a genital response, others have suggested that desire and arousal disorders should be combined in one entity.

  11. Female Pattern Hair Loss

    Science.gov (United States)

    Herskovitz, Ingrid; Tosti, Antonella

    2013-01-01

    Context: Female pattern hair loss (FPHL) also known as female androgenetic alopecia is a common condition afflicting millions of women that can be cosmetically disrupting. Prompt diagnosis and treatment are essential for obtaining optimal outcome. This review addresses the clinical presentation of female pattern hair loss, its differential diagnosis and treatment modalities. Evidence Acquisition: A) Diffuse thinning of the crown region with preservation of the frontal hairline (Ludwig’s type) B) The “Christmas tree pattern” where the thinning is wider in the frontal scalp giving the alopecic area a triangular shaped figure resembling a christmas tree. C) Thinning associated with bitemporal recession (Hamilton type). Generally, FPHL is not associated with elevated androgens. Less commonly females with FPHL may have other skin or general signs of hyperandrogenism such as hirsutism, acne, irregular menses, infertility, galactorrhea and insulin resistance. The most common endocrinological abnormality associated with FPHL is polycystic ovarian syndrome (PCOS). Results: The most important diseases to consider in the differential diagnosis of FPHL include Chronic Telogen Effluvium (CTE), Permanent Alopecia after Chemotherapy (PAC), Alopecia Areata Incognito (AAI) and Frontal Fibrosing Alopecia (FFA). This review describes criteria for distinguishing these conditions from FPHL. Conclusions: The only approved treatment for FPHL, which is 2% topical Minoxidil, should be applied at the dosage of 1ml twice day for a minimum period of 12 months. This review will discuss off-label alternative modalities of treatment including 5-alfa reductase inhibitors, antiandrogens, estrogens, prostaglandin analogs, lasers, light treatments and hair transplantation. PMID:24719635

  12. The female athlete triad.

    Science.gov (United States)

    Kazis, Keren; Iglesias, Elba

    2003-02-01

    The female athlete triad is a syndrome consisting of disordered eating, amenorrhea, and osteoporosis. The syndrome is increasing in prevalence as more women are participating in sports at a competitive level. Behaviors such as intense exercise or disordered eating patterns can lead to dysregulation of the hypothalamic-pituitarian-ovarian (HPO) axis, resulting in amenorrhea. Hypothalamic amenorrhea can lead to osteoporosis and increased fracture risk. Adolescents may particularly be at risk because it is during this crucial time that females attain their peak bone mass. Prevention of the female athlete triad through education and identification of athletes at risk may decrease the incidence of long-term deleterious consequences. Treatment of the female athlete triad is initially aimed at increasing caloric intake and decreasing physical activity until there is resumption of normal menses. Treatment of decreased bone mineral density and osteoporosis in the adolescent population, however, is controversial, with new treatment modalities currently being investigated in order to aid in the management of this disorder.

  13. Female pattern hair loss.

    Science.gov (United States)

    Herskovitz, Ingrid; Tosti, Antonella

    2013-10-01

    Female pattern hair loss (FPHL) also known as female androgenetic alopecia is a common condition afflicting millions of women that can be cosmetically disrupting. Prompt diagnosis and treatment are essential for obtaining optimal outcome. This review addresses the clinical presentation of female pattern hair loss, its differential diagnosis and treatment modalities. A) Diffuse thinning of the crown region with preservation of the frontal hairline (Ludwig's type) B) The "Christmas tree pattern" where the thinning is wider in the frontal scalp giving the alopecic area a triangular shaped figure resembling a christmas tree. C) Thinning associated with bitemporal recession (Hamilton type). Generally, FPHL is not associated with elevated androgens. Less commonly females with FPHL may have other skin or general signs of hyperandrogenism such as hirsutism, acne, irregular menses, infertility, galactorrhea and insulin resistance. The most common endocrinological abnormality associated with FPHL is polycystic ovarian syndrome (PCOS). The most important diseases to consider in the differential diagnosis of FPHL include Chronic Telogen Effluvium (CTE), Permanent Alopecia after Chemotherapy (PAC), Alopecia Areata Incognito (AAI) and Frontal Fibrosing Alopecia (FFA). This review describes criteria for distinguishing these conditions from FPHL. The only approved treatment for FPHL, which is 2% topical Minoxidil, should be applied at the dosage of 1ml twice day for a minimum period of 12 months. This review will discuss off-label alternative modalities of treatment including 5-alfa reductase inhibitors, antiandrogens, estrogens, prostaglandin analogs, lasers, light treatments and hair transplantation.

  14. Possible future HERA analyses

    International Nuclear Information System (INIS)

    Geiser, Achim

    2015-12-01

    A variety of possible future analyses of HERA data in the context of the HERA data preservation programme is collected, motivated, and commented. The focus is placed on possible future analyses of the existing ep collider data and their physics scope. Comparisons to the original scope of the HERA pro- gramme are made, and cross references to topics also covered by other participants of the workshop are given. This includes topics on QCD, proton structure, diffraction, jets, hadronic final states, heavy flavours, electroweak physics, and the application of related theory and phenomenology topics like NNLO QCD calculations, low-x related models, nonperturbative QCD aspects, and electroweak radiative corrections. Synergies with other collider programmes are also addressed. In summary, the range of physics topics which can still be uniquely covered using the existing data is very broad and of considerable physics interest, often matching the interest of results from colliders currently in operation. Due to well-established data and MC sets, calibrations, and analysis procedures the manpower and expertise needed for a particular analysis is often very much smaller than that needed for an ongoing experiment. Since centrally funded manpower to carry out such analyses is not available any longer, this contribution not only targets experienced self-funded experimentalists, but also theorists and master-level students who might wish to carry out such an analysis.

  15. Biomass feedstock analyses

    Energy Technology Data Exchange (ETDEWEB)

    Wilen, C.; Moilanen, A.; Kurkela, E. [VTT Energy, Espoo (Finland). Energy Production Technologies

    1996-12-31

    The overall objectives of the project `Feasibility of electricity production from biomass by pressurized gasification systems` within the EC Research Programme JOULE II were to evaluate the potential of advanced power production systems based on biomass gasification and to study the technical and economic feasibility of these new processes with different type of biomass feed stocks. This report was prepared as part of this R and D project. The objectives of this task were to perform fuel analyses of potential woody and herbaceous biomasses with specific regard to the gasification properties of the selected feed stocks. The analyses of 15 Scandinavian and European biomass feed stock included density, proximate and ultimate analyses, trace compounds, ash composition and fusion behaviour in oxidizing and reducing atmospheres. The wood-derived fuels, such as whole-tree chips, forest residues, bark and to some extent willow, can be expected to have good gasification properties. Difficulties caused by ash fusion and sintering in straw combustion and gasification are generally known. The ash and alkali metal contents of the European biomasses harvested in Italy resembled those of the Nordic straws, and it is expected that they behave to a great extent as straw in gasification. Any direct relation between the ash fusion behavior (determined according to the standard method) and, for instance, the alkali metal content was not found in the laboratory determinations. A more profound characterisation of the fuels would require gasification experiments in a thermobalance and a PDU (Process development Unit) rig. (orig.) (10 refs.)

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

    Science.gov (United States)

    Vaeth, Michael; Skovlund, Eva

    2004-06-15

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

  17. 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.

  18. Stochastic development regression using method of moments

    DEFF Research Database (Denmark)

    Kühnel, Line; Sommer, Stefan Horst

    2017-01-01

    This paper considers the estimation problem arising when inferring parameters in the stochastic development regression model for manifold valued non-linear data. Stochastic development regression captures the relation between manifold-valued response and Euclidean covariate variables using...... the stochastic development construction. It is thereby able to incorporate several covariate variables and random effects. The model is intrinsically defined using the connection of the manifold, and the use of stochastic development avoids linearizing the geometry. We propose to infer parameters using...... the Method of Moments procedure that matches known constraints on moments of the observations conditional on the latent variables. The performance of the model is investigated in a simulation example using data on finite dimensional landmark manifolds....

  19. Beta-binomial regression and bimodal utilization.

    Science.gov (United States)

    Liu, Chuan-Fen; Burgess, James F; Manning, Willard G; Maciejewski, Matthew L

    2013-10-01

    To illustrate how the analysis of bimodal U-shaped distributed utilization can be modeled with beta-binomial regression, which is rarely used in health services research. Veterans Affairs (VA) administrative data and Medicare claims in 2001-2004 for 11,123 Medicare-eligible VA primary care users in 2000. We compared means and distributions of VA reliance (the proportion of all VA/Medicare primary care visits occurring in VA) predicted from beta-binomial, binomial, and ordinary least-squares (OLS) models. Beta-binomial model fits the bimodal distribution of VA reliance better than binomial and OLS models due to the nondependence on normality and the greater flexibility in shape parameters. Increased awareness of beta-binomial regression may help analysts apply appropriate methods to outcomes with bimodal or U-shaped distributions. © Health Research and Educational Trust.

  20. Testing homogeneity in Weibull-regression models.

    Science.gov (United States)

    Bolfarine, Heleno; Valença, Dione M

    2005-10-01

    In survival studies with families or geographical units it may be of interest testing whether such groups are homogeneous for given explanatory variables. In this paper we consider score type tests for group homogeneity based on a mixing model in which the group effect is modelled as a random variable. As opposed to hazard-based frailty models, this model presents survival times that conditioned on the random effect, has an accelerated failure time representation. The test statistics requires only estimation of the conventional regression model without the random effect and does not require specifying the distribution of the random effect. The tests are derived for a Weibull regression model and in the uncensored situation, a closed form is obtained for the test statistic. A simulation study is used for comparing the power of the tests. The proposed tests are applied to real data sets with censored data.

  1. Are increases in cigarette taxation regressive?

    Science.gov (United States)

    Borren, P; Sutton, M

    1992-12-01

    Using the latest published data from Tobacco Advisory Council surveys, this paper re-evaluates the question of whether or not increases in cigarette taxation are regressive in the United Kingdom. The extended data set shows no evidence of increasing price-elasticity by social class as found in a major previous study. To the contrary, there appears to be no clear pattern in the price responsiveness of smoking behaviour across different social classes. Increases in cigarette taxation, while reducing smoking levels in all groups, fall most heavily on men and women in the lowest social class. Men and women in social class five can expect to pay eight and eleven times more of a tax increase respectively, than their social class one counterparts. Taken as a proportion of relative incomes, the regressive nature of increases in cigarette taxation is even more pronounced.

  2. 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.

  3. Regression Models For Multivariate Count Data.

    Science.gov (United States)

    Zhang, Yiwen; Zhou, Hua; Zhou, Jin; Sun, Wei

    2017-01-01

    Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data.

  4. Model selection in kernel ridge regression

    DEFF Research Database (Denmark)

    Exterkate, Peter

    2013-01-01

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

  5. Confidence bands for inverse regression models

    International Nuclear Information System (INIS)

    Birke, Melanie; Bissantz, Nicolai; Holzmann, Hajo

    2010-01-01

    We construct uniform confidence bands for the regression function in inverse, homoscedastic regression models with convolution-type operators. Here, the convolution is between two non-periodic functions on the whole real line rather than between two periodic functions on a compact interval, since the former situation arguably arises more often in applications. First, following Bickel and Rosenblatt (1973 Ann. Stat. 1 1071–95) we construct asymptotic confidence bands which are based on strong approximations and on a limit theorem for the supremum of a stationary Gaussian process. Further, we propose bootstrap confidence bands based on the residual bootstrap and prove consistency of the bootstrap procedure. A simulation study shows that the bootstrap confidence bands perform reasonably well for moderate sample sizes. Finally, we apply our method to data from a gel electrophoresis experiment with genetically engineered neuronal receptor subunits incubated with rat brain extract

  6. [High prevalence of work-family conflict among female physicians: lack of social support as a potential antecedent].

    Science.gov (United States)

    Adám, Szilvia

    2009-12-13

    According to stress theory, social support from work and non-work-related sources may influence the level of perceived work-family conflict. Despite the high prevalence of work-family conflict as a source of distress among female physicians, no information is available on the associations between work-family conflict and social support in a traditional, family-centric cultural setting, where female role expectations are demanding. The author hypothesized that high prevalence of work-family conflict could be attributed to the lack of social support among female physicians. To investigate the prevalence and psychosocial characteristics of social support and its relations to work-family conflict among female physicians. Quantitative and qualitative study using questionnaires ( n = 420) and in-depth interviews ( n = 123) among female and male physicians. Female physicians reported significantly higher mean level and prevalence of work-family conflict compared to men. The predominant form of work-family was work-to-family conflict among physicians; however, significantly more female physicians experienced family-to-work conflict and strain-based work-family conflict compared to men (39% vs. 18% and 68% vs. 20%, respectively). Significantly more male physicians experienced time-based work-family conflict compared to women. Content analyses of interview data revealed that provision of support to physicians manifested itself in parental support in career selection, spousal support with household duties, peer support with enabling access to professional role models-mentors, peer support to ensure gender equity, and organizational support with family-centric policies. Female physicians reported significantly less parental, spousal, and peer support compared to men. Female physicians lacking parental, peer, or organizational support experienced significantly higher level of work-family conflict compared to appropriate control. In regression analyses, high job demands, job

  7. Regressing Atherosclerosis by Resolving Plaque Inflammation

    Science.gov (United States)

    2017-07-01

    regression requires the alteration of macrophages in the plaques to a tissue repair “alternatively” activated state. This switch in activation state... tissue repair “alternatively” activated state. This switch in activation state requires the action of TH2 cytokines interleukin (IL)-4 or IL-13. To...regulation of tissue macrophage and dendritic cell population dynamics by CSF-1. J Exp Med. 2011;208(9):1901–1916. 35. Xu H, Exner BG, Chilton PM

  8. Determination of regression laws: Linear and nonlinear

    International Nuclear Information System (INIS)

    Onishchenko, A.M.

    1994-01-01

    A detailed mathematical determination of regression laws is presented in the article. Particular emphasis is place on determining the laws of X j on X l to account for source nuclei decay and detector errors in nuclear physics instrumentation. Both linear and nonlinear relations are presented. Linearization of 19 functions is tabulated, including graph, relation, variable substitution, obtained linear function, and remarks. 6 refs., 1 tab

  9. 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

  10. Logistic regression a self-learning text

    CERN Document Server

    Kleinbaum, David G

    1994-01-01

    This textbook provides students and professionals in the health sciences with a presentation of the use of logistic regression in research. The text is self-contained, and designed to be used both in class or as a tool for self-study. It arises from the author's many years of experience teaching this material and the notes on which it is based have been extensively used throughout the world.

  11. PSYCHOLOGICAL FEATURES OF CONFLICT BEHAVIOUR AMONG FEMALE INMATES

    Directory of Open Access Journals (Sweden)

    Anna Leonidovna Plotnikova

    2017-04-01

    Full Text Available In this article the results of the research concerning the special features of behaviour in the conflicts among the female inmates are given, psychological features of the female inmates are analysed, their psychological typology is presented, inmates gender differences are characterized as well as psychological reasons of interpersonal conflicts among the female inmates in the correctional facilities, the most conflict categories of female inmates are distinguished. Purpose: revealing of dominant strategies of behaviour in the conflict of the female inmates, specific features of female inmates conflict behaviour according to age and type of committed crime. Method: ascertaining experiment Results: dominant strategies of female inmates conflict behaviour are compromise and adjustment. Areas of use: the penitentiary system.

  12. Multitask Quantile Regression under the Transnormal Model.

    Science.gov (United States)

    Fan, Jianqing; Xue, Lingzhou; Zou, Hui

    2016-01-01

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

  13. Complex regression Doppler optical coherence tomography

    Science.gov (United States)

    Elahi, Sahar; Gu, Shi; Thrane, Lars; Rollins, Andrew M.; Jenkins, Michael W.

    2018-04-01

    We introduce a new method to measure Doppler shifts more accurately and extend the dynamic range of Doppler optical coherence tomography (OCT). The two-point estimate of the conventional Doppler method is replaced with a regression that is applied to high-density B-scans in polar coordinates. We built a high-speed OCT system using a 1.68-MHz Fourier domain mode locked laser to acquire high-density B-scans (16,000 A-lines) at high enough frame rates (˜100 fps) to accurately capture the dynamics of the beating embryonic heart. Flow phantom experiments confirm that the complex regression lowers the minimum detectable velocity from 12.25 mm / s to 374 μm / s, whereas the maximum velocity of 400 mm / s is measured without phase wrapping. Complex regression Doppler OCT also demonstrates higher accuracy and precision compared with the conventional method, particularly when signal-to-noise ratio is low. The extended dynamic range allows monitoring of blood flow over several stages of development in embryos without adjusting the imaging parameters. In addition, applying complex averaging recovers hidden features in structural images.

  14. Satellite rainfall retrieval by logistic regression

    Science.gov (United States)

    Chiu, Long S.

    1986-01-01

    The potential use of logistic regression in rainfall estimation from satellite measurements is investigated. Satellite measurements provide covariate information in terms of radiances from different remote sensors.The logistic regression technique can effectively accommodate many covariates and test their significance in the estimation. The outcome from the logistical model is the probability that the rainrate of a satellite pixel is above a certain threshold. By varying the thresholds, a rainrate histogram can be obtained, from which the mean and the variant can be estimated. A logistical model is developed and applied to rainfall data collected during GATE, using as covariates the fractional rain area and a radiance measurement which is deduced from a microwave temperature-rainrate relation. It is demonstrated that the fractional rain area is an important covariate in the model, consistent with the use of the so-called Area Time Integral in estimating total rain volume in other studies. To calibrate the logistical model, simulated rain fields generated by rainfield models with prescribed parameters are needed. A stringent test of the logistical model is its ability to recover the prescribed parameters of simulated rain fields. A rain field simulation model which preserves the fractional rain area and lognormality of rainrates as found in GATE is developed. A stochastic regression model of branching and immigration whose solutions are lognormally distributed in some asymptotic limits has also been developed.

  15. Bayesian Inference of a Multivariate Regression Model

    Directory of Open Access Journals (Sweden)

    Marick S. Sinay

    2014-01-01

    Full Text Available We explore Bayesian inference of a multivariate linear regression model with use of a flexible prior for the covariance structure. The commonly adopted Bayesian setup involves the conjugate prior, multivariate normal distribution for the regression coefficients and inverse Wishart specification for the covariance matrix. Here we depart from this approach and propose a novel Bayesian estimator for the covariance. A multivariate normal prior for the unique elements of the matrix logarithm of the covariance matrix is considered. Such structure allows for a richer class of prior distributions for the covariance, with respect to strength of beliefs in prior location hyperparameters, as well as the added ability, to model potential correlation amongst the covariance structure. The posterior moments of all relevant parameters of interest are calculated based upon numerical results via a Markov chain Monte Carlo procedure. The Metropolis-Hastings-within-Gibbs algorithm is invoked to account for the construction of a proposal density that closely matches the shape of the target posterior distribution. As an application of the proposed technique, we investigate a multiple regression based upon the 1980 High School and Beyond Survey.

  16. Modeling oil production based on symbolic regression

    International Nuclear Information System (INIS)

    Yang, Guangfei; Li, Xianneng; Wang, Jianliang; Lian, Lian; Ma, Tieju

    2015-01-01

    Numerous models have been proposed to forecast the future trends of oil production and almost all of them are based on some predefined assumptions with various uncertainties. In this study, we propose a novel data-driven approach that uses symbolic regression to model oil production. We validate our approach on both synthetic and real data, and the results prove that symbolic regression could effectively identify the true models beneath the oil production data and also make reliable predictions. Symbolic regression indicates that world oil production will peak in 2021, which broadly agrees with other techniques used by researchers. Our results also show that the rate of decline after the peak is almost half the rate of increase before the peak, and it takes nearly 12 years to drop 4% from the peak. These predictions are more optimistic than those in several other reports, and the smoother decline will provide the world, especially the developing countries, with more time to orchestrate mitigation plans. -- Highlights: •A data-driven approach has been shown to be effective at modeling the oil production. •The Hubbert model could be discovered automatically from data. •The peak of world oil production is predicted to appear in 2021. •The decline rate after peak is half of the increase rate before peak. •Oil production projected to decline 4% post-peak

  17. Face Alignment via Regressing Local Binary Features.

    Science.gov (United States)

    Ren, Shaoqing; Cao, Xudong; Wei, Yichen; Sun, Jian

    2016-03-01

    This paper presents a highly efficient and accurate regression approach for face alignment. Our approach has two novel components: 1) a set of local binary features and 2) a locality principle for learning those features. The locality principle guides us to learn a set of highly discriminative local binary features for each facial landmark independently. The obtained local binary features are used to jointly learn a linear regression for the final output. This approach achieves the state-of-the-art results when tested on the most challenging benchmarks to date. Furthermore, because extracting and regressing local binary features are computationally very cheap, our system is much faster than previous methods. It achieves over 3000 frames per second (FPS) on a desktop or 300 FPS on a mobile phone for locating a few dozens of landmarks. We also study a key issue that is important but has received little attention in the previous research, which is the face detector used to initialize alignment. We investigate several face detectors and perform quantitative evaluation on how they affect alignment accuracy. We find that an alignment friendly detector can further greatly boost the accuracy of our alignment method, reducing the error up to 16% relatively. To facilitate practical usage of face detection/alignment methods, we also propose a convenient metric to measure how good a detector is for alignment initialization.

  18. 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.

  19. Mixed-effects regression models in linguistics

    CERN Document Server

    Heylen, Kris; Geeraerts, Dirk

    2018-01-01

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

  20. On logistic regression analysis of dichotomized responses.

    Science.gov (United States)

    Lu, Kaifeng

    2017-01-01

    We study the properties of treatment effect estimate in terms of odds ratio at the study end point from logistic regression model adjusting for the baseline value when the underlying continuous repeated measurements follow a multivariate normal distribution. Compared with the analysis that does not adjust for the baseline value, the adjusted analysis produces a larger treatment effect as well as a larger standard error. However, the increase in standard error is more than offset by the increase in treatment effect so that the adjusted analysis is more powerful than the unadjusted analysis for detecting the treatment effect. On the other hand, the true adjusted odds ratio implied by the normal distribution of the underlying continuous variable is a function of the baseline value and hence is unlikely to be able to be adequately represented by a single value of adjusted odds ratio from the logistic regression model. In contrast, the risk difference function derived from the logistic regression model provides a reasonable approximation to the true risk difference function implied by the normal distribution of the underlying continuous variable over the range of the baseline distribution. We show that different metrics of treatment effect have similar statistical power when evaluated at the baseline mean. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  1. General regression and representation model for classification.

    Directory of Open Access Journals (Sweden)

    Jianjun Qian

    Full Text Available Recently, the regularized coding-based classification methods (e.g. SRC and CRC show a great potential for pattern classification. However, most existing coding methods assume that the representation residuals are uncorrelated. In real-world applications, this assumption does not hold. In this paper, we take account of the correlations of the representation residuals and develop a general regression and representation model (GRR for classification. GRR not only has advantages of CRC, but also takes full use of the prior information (e.g. the correlations between representation residuals and representation coefficients and the specific information (weight matrix of image pixels to enhance the classification performance. GRR uses the generalized Tikhonov regularization and K Nearest Neighbors to learn the prior information from the training data. Meanwhile, the specific information is obtained by using an iterative algorithm to update the feature (or image pixel weights of the test sample. With the proposed model as a platform, we design two classifiers: basic general regression and representation classifier (B-GRR and robust general regression and representation classifier (R-GRR. The experimental results demonstrate the performance advantages of proposed methods over state-of-the-art algorithms.

  2. Image superresolution using support vector regression.

    Science.gov (United States)

    Ni, Karl S; Nguyen, Truong Q

    2007-06-01

    A thorough investigation of the application of support vector regression (SVR) to the superresolution problem is conducted through various frameworks. Prior to the study, the SVR problem is enhanced by finding the optimal kernel. This is done by formulating the kernel learning problem in SVR form as a convex optimization problem, specifically a semi-definite programming (SDP) problem. An additional constraint is added to reduce the SDP to a quadratically constrained quadratic programming (QCQP) problem. After this optimization, investigation of the relevancy of SVR to superresolution proceeds with the possibility of using a single and general support vector regression for all image content, and the results are impressive for small training sets. This idea is improved upon by observing structural properties in the discrete cosine transform (DCT) domain to aid in learning the regression. Further improvement involves a combination of classification and SVR-based techniques, extending works in resolution synthesis. This method, termed kernel resolution synthesis, uses specific regressors for isolated image content to describe the domain through a partitioned look of the vector space, thereby yielding good results.

  3. Evaluation of Female Breast Cancer Risk Among the Betel Quid Chewer: A Bio-Statistical Assessment in Assam, India.

    Science.gov (United States)

    Rajbongshi, Nijara; Mahanta, Lipi B; Nath, Dilip C

    2015-06-01

    Breast cancer is the most commonly diagnosed cancer among the female population of Assam, India. Chewing of betel quid with or without tobacco is common practice among female population of this region. Moreoverthe method of preparing the betel quid is different from other parts of the country.So matched case control study is conducted to analyse whetherbetel quid chewing plays a significant role in the high incidence of breast cancer occurrences in Assam. Here, controls are matched to the cases by age at diagnosis (±5 years), family income and place of residence with matching ratio 1:1. Conditional logistic regression models and odd ratios (OR) was used to draw conclusions. It is observed that cases are more habituated to chewing habits than the controls.Further the conditional logistic regression analysis reveals that betel quid chewer faces 2.353 times more risk having breast cancer than the non-chewer with p value 0.0003 (95% CI 1.334-4.150). Though the female population in Assam usually does not smoke, the addictive habits typical to this region have equal effect on the occurrence of breast cancer.

  4. Use of multiple linear regression and logistic regression models to investigate changes in birthweight for term singleton infants in Scotland.

    Science.gov (United States)

    Bonellie, Sandra R

    2012-10-01

    To illustrate the use of regression and logistic regression models to investigate changes over time in size of babies particularly in relation to social deprivation, age of the mother and smoking. Mean birthweight has been found to be increasing in many countries in recent years, but there are still a group of babies who are born with low birthweights. Population-based retrospective cohort study. Multiple linear regression and logistic regression models are used to analyse data on term 'singleton births' from Scottish hospitals between 1994-2003. Mothers who smoke are shown to give birth to lighter babies on average, a difference of approximately 0.57 Standard deviations lower (95% confidence interval. 0.55-0.58) when adjusted for sex and parity. These mothers are also more likely to have babies that are low birthweight (odds ratio 3.46, 95% confidence interval 3.30-3.63) compared with non-smokers. Low birthweight is 30% more likely where the mother lives in the most deprived areas compared with the least deprived, (odds ratio 1.30, 95% confidence interval 1.21-1.40). Smoking during pregnancy is shown to have a detrimental effect on the size of infants at birth. This effect explains some, though not all, of the observed socioeconomic birthweight. It also explains much of the observed birthweight differences by the age of the mother.   Identifying mothers at greater risk of having a low birthweight baby as important implications for the care and advice this group receives. © 2012 Blackwell Publishing Ltd.

  5. 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)

  6. AMS analyses at ANSTO

    Energy Technology Data Exchange (ETDEWEB)

    Lawson, E.M. [Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW (Australia). Physics Division

    1998-03-01

    The major use of ANTARES is Accelerator Mass Spectrometry (AMS) with {sup 14}C being the most commonly analysed radioisotope - presently about 35 % of the available beam time on ANTARES is used for {sup 14}C measurements. The accelerator measurements are supported by, and dependent on, a strong sample preparation section. The ANTARES AMS facility supports a wide range of investigations into fields such as global climate change, ice cores, oceanography, dendrochronology, anthropology, and classical and Australian archaeology. Described here are some examples of the ways in which AMS has been applied to support research into the archaeology, prehistory and culture of this continent`s indigenous Aboriginal peoples. (author)

  7. AMS analyses at ANSTO

    International Nuclear Information System (INIS)

    Lawson, E.M.

    1998-01-01

    The major use of ANTARES is Accelerator Mass Spectrometry (AMS) with 14 C being the most commonly analysed radioisotope - presently about 35 % of the available beam time on ANTARES is used for 14 C measurements. The accelerator measurements are supported by, and dependent on, a strong sample preparation section. The ANTARES AMS facility supports a wide range of investigations into fields such as global climate change, ice cores, oceanography, dendrochronology, anthropology, and classical and Australian archaeology. Described here are some examples of the ways in which AMS has been applied to support research into the archaeology, prehistory and culture of this continent's indigenous Aboriginal peoples. (author)

  8. Econometric analysis of realised covariation: high frequency covariance, regression and correlation in financial economics

    OpenAIRE

    Ole E. Barndorff-Nielsen; Neil Shephard

    2002-01-01

    This paper analyses multivariate high frequency financial data using realised covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis and covariance. It will be based on a fixed interval of time (e.g. a day or week), allowing the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions and covariances change through time. In particular w...

  9. Analyses of MHD instabilities

    International Nuclear Information System (INIS)

    Takeda, Tatsuoki

    1985-01-01

    In this article analyses of the MHD stabilities which govern the global behavior of a fusion plasma are described from the viewpoint of the numerical computation. First, we describe the high accuracy calculation of the MHD equilibrium and then the analysis of the linear MHD instability. The former is the basis of the stability analysis and the latter is closely related to the limiting beta value which is a very important theoretical issue of the tokamak research. To attain a stable tokamak plasma with good confinement property it is necessary to control or suppress disruptive instabilities. We, next, describe the nonlinear MHD instabilities which relate with the disruption phenomena. Lastly, we describe vectorization of the MHD codes. The above MHD codes for fusion plasma analyses are relatively simple though very time-consuming and parts of the codes which need a lot of CPU time concentrate on a small portion of the codes, moreover, the codes are usually used by the developers of the codes themselves, which make it comparatively easy to attain a high performance ratio on the vector processor. (author)

  10. National female literacy, individual socio-economic status, and maternal health care use in sub-Saharan Africa.

    Science.gov (United States)

    McTavish, Sarah; Moore, Spencer; Harper, Sam; Lynch, John

    2010-12-01

    The United Nations Millennium Development Goals have identified improving women's access to maternal health care as a key target in reducing maternal mortality in sub-Saharan Africa (sSA). Although individual factors such as income and urban residence can affect maternal health care use, little is known about national-level factors associated with use. Yet, such knowledge may highlight the importance of global and national policies in improving use. This study examines the importance of national female literacy on women's maternal health care use in continental sSA. Data that come from the 2002-2003 World Health Survey. Multilevel logistic regression was used to examine the association between national female literacy and individual's non-use of maternal health care, while adjusting for individual-level factors and national economic development. Analyses also assessed effect modification of the association between income and non-use by female literacy. Effect modification was evaluated with the likelihood ratio test (G(2)). We found that within countries, individual age, education, urban residence and household income were associated with lack of maternal health care. National female literacy modified the association of household income with lack of maternal health care use. The strength of the association between income and lack of maternal health care was weaker in countries with higher female literacy. We conclude therefore that higher national levels of female literacy may reduce income-related inequalities in use through a range of possible mechanisms, including women's increased labour participation and higher status in society. National policies that are able to address female literacy and women's status in sub-Saharan Africa may help reduce income-related inequalities in maternal health care use. Copyright © 2010 Elsevier Ltd. All rights reserved.

  11. Female Sexual Arousal Disorders

    DEFF Research Database (Denmark)

    Giraldi, Annamaria; Rellini, Alessandra H; Pfaus, James

    2012-01-01

    Introduction.  Definitions and terminology for female sexual arousal disorder (FSAD) are currently being debated. While some authors have suggested that FSAD is more a subjective response rather than a genital response, others have suggested that desire and arousal disorders should be combined...... and psychological disorders, as well as to discuss different medical and psychological assessment and treatment modalities. Methods.  The experts of the International Society for Sexual Medicine's Standard Committee convened to provide a survey using relevant databases, journal articles, and own clinical experience....... Results.  Female Arousal Disorders have been defined in several ways with focus on the genital or subjective response or a combination of both. The prevalence varies and increases with increasing age, especially at the time of menopause, while distress decreases with age. Arousal disorders are often...

  12. [Hypertension in females].

    Science.gov (United States)

    Cífková, Renata

    2015-05-01

    Hypertension is the most common cardiovascular disorder affecting more males in younger age groups; in the age group of 45-64, it is equally frequent in both genders, it is more common in elderly females. Blood pressure increases more in females around the menopause. Use of hormonal replacement therapy is not associated with an BP increase but, because of increased risk of coronary events, stroke, and thromboembolic events, HRT is not re-commended in CVD prevention. There is a similar decrease in BP by antihypertensive drugs in both genders as well as benefit from antihypertensive treatment. Women report about a double rate of adverse events of antihypertensive drugs. Oral contraception use is associated with a mild BP increase in most women and development of overt hypertension in about 5 %. Pre-eclampsia is associated with increased risk of developing CVD later in life (more frequent development of hypertension, myocardial infarction, and stroke).

  13. Uncertainty Analyses and Strategy

    International Nuclear Information System (INIS)

    Kevin Coppersmith

    2001-01-01

    The DOE identified a variety of uncertainties, arising from different sources, during its assessment of the performance of a potential geologic repository at the Yucca Mountain site. In general, the number and detail of process models developed for the Yucca Mountain site, and the complex coupling among those models, make the direct incorporation of all uncertainties difficult. The DOE has addressed these issues in a number of ways using an approach to uncertainties that is focused on producing a defensible evaluation of the performance of a potential repository. The treatment of uncertainties oriented toward defensible assessments has led to analyses and models with so-called ''conservative'' assumptions and parameter bounds, where conservative implies lower performance than might be demonstrated with a more realistic representation. The varying maturity of the analyses and models, and uneven level of data availability, result in total system level analyses with a mix of realistic and conservative estimates (for both probabilistic representations and single values). That is, some inputs have realistically represented uncertainties, and others are conservatively estimated or bounded. However, this approach is consistent with the ''reasonable assurance'' approach to compliance demonstration, which was called for in the U.S. Nuclear Regulatory Commission's (NRC) proposed 10 CFR Part 63 regulation (64 FR 8640 [DIRS 101680]). A risk analysis that includes conservatism in the inputs will result in conservative risk estimates. Therefore, the approach taken for the Total System Performance Assessment for the Site Recommendation (TSPA-SR) provides a reasonable representation of processes and conservatism for purposes of site recommendation. However, mixing unknown degrees of conservatism in models and parameter representations reduces the transparency of the analysis and makes the development of coherent and consistent probability statements about projected repository

  14. Resuscitation outcomes of reproductive-age females who experienced out-of-hospital cardiac arrest.

    Science.gov (United States)

    Hagihara, Akihito; Onozuka, Daisuke; Hasegawa, Manabu; Nagata, Takashi; Abe, Takeru; Nabeshima, Yoshihiro

    2017-03-01

    Although some studies have shown that women in their reproductive years have better resuscitation outcomes of out-of-hospital cardiac arrest (OHCA), conflicting results and methodological problems have also been noted. Thus, we evaluated the resuscitation outcomes of OHCA of females by age. This was a prospective observational study using registry data from all OHCA cases between 2005 and 2012 in Japan. The subjects were females aged 18-110 years who suffered an out-of-hospital cardiac arrest. Logistic regression analyses were performed using total and propensity-matched patients. There were 381,123 OHCA cases that met the inclusion criteria. Among propensity-matched patients, females aged 18-49 and 50-60 years of age had similar rates of return of spontaneous circulation before hospital arrival and 1-month survival (all p>0.60). In contrast, females aged 18-49 years of age had significantly lower rates of 1-month survival with minimal neurological impairment than did females aged 50-60 years of age (after adjusting for selected variables: Cerebral Performance Category scale 1 or 2 (CPC (1, 2)), OR=0.45, p=0.020; Overall Performance Category scale 1 or 2 (OPC (1, 2)): OR=0.42, p= 0.014; after adjustment for all variables: CPC (1, 2), OR=0.27, p= 0.008; OPC (1, 2), OR=0.29, p=0.009). Women of reproductive age did not show improved resuscitation outcomes in OHCA. Additionally, women in their reproductive years showed worse neurological outcomes one month after the event, which may be explained by the negative effects of estrogen. These findings need to be verified in further studies.

  15. Geodesic least squares regression for scaling studies in magnetic confinement fusion

    International Nuclear Information System (INIS)

    Verdoolaege, Geert

    2015-01-01

    In regression analyses for deriving scaling laws that occur in various scientific disciplines, usually standard regression methods have been applied, of which ordinary least squares (OLS) is the most popular. However, concerns have been raised with respect to several assumptions underlying OLS in its application to scaling laws. We here discuss a new regression method that is robust in the presence of significant uncertainty on both the data and the regression model. The method, which we call geodesic least squares regression (GLS), is based on minimization of the Rao geodesic distance on a probabilistic manifold. We demonstrate the superiority of the method using synthetic data and we present an application to the scaling law for the power threshold for the transition to the high confinement regime in magnetic confinement fusion devices

  16. female collegiate athletes

    Directory of Open Access Journals (Sweden)

    JL Ayers

    2016-08-01

    Full Text Available Olympic weightlifting movements and their variations are believed to be among the most effective ways to improve power, strength, and speed in athletes. This study investigated the effects of two Olympic weightlifting variations (hang cleans and hang snatches, on power (vertical jump height, strength (1RM back squat, and speed (40-yard sprint in female collegiate athletes. 23 NCAA Division I female athletes were randomly assigned to either a hang clean group or hang snatch group. Athletes participated in two workout sessions a week for six weeks, performing either hang cleans or hang snatches for five sets of three repetitions with a load of 80-85% 1RM, concurrent with their existing, season-specific, resistance training program. Vertical jump height, 1RM back squat, and 40-yard sprint all had a significant, positive improvement from pre-training to post-training in both groups (p≤0.01. However, when comparing the gain scores between groups, there was no significant difference between the hang clean and hang snatch groups for any of the three dependent variables (i.e., vertical jump height, p=0.46; 1RM back squat, p=0.20; and 40-yard sprint, p=0.46. Short-term training emphasizing hang cleans or hang snatches produced similar improvements in power, strength, and speed in female collegiate athletes. This provides strength and conditioning professionals with two viable programmatic options in athletic-based exercises to improve power, strength, and speed.

  17. Married women's negotiation for safer sexual intercourse in Kenya: Does experience of female genital mutilation matter?

    Science.gov (United States)

    Chai, Xiangnan; Sano, Yujiro; Kansanga, Moses; Baada, Jemima; Antabe, Roger

    2017-12-01

    Married women's ability to negotiate for safer sex is important for HIV prevention in sub-Saharan Africa, including Kenya. Yet, its relationship to female genital mutilation is rarely explored, although female genital mutilation has been described as a social norm and marker of womanhood that can control women's sexuality. Drawing on the social normative influence theory, this study addressed this void in the literature. We analysed data from the 2014 Kenya Demographic and Health Survey using logistic regression. Our sample included 8,602 married women. Two indicators of safer sex, namely the ability to refuse sex and the ability to ask for condom use, were explored. We found that women who had undergone genital mutilation were significantly less likely to report that they can refuse sex (OR=0.87; p<.05) and that they can ask for condom use during sexual intercourse (OR=0.62; p<.001) than their counterparts who had not undergone genital mutilation, while controlling for theoretically relevant variables. Our findings indicate that the experience of female genital mutilation may influence married women's ability to negotiate for safer sex through gendered socialization and expectations. Based on these findings, several policy implications are suggested. For instance, culturally sensitive programmes are needed that target both married women who have undergone genital mutilation and their husbands to understand the importance of safer sexual practices within marriage. Copyright © 2017. Published by Elsevier B.V.

  18. Associations between Bisphenol A Exposure and Reproductive Hormones among Female Workers

    Directory of Open Access Journals (Sweden)

    Maohua Miao

    2015-10-01

    Full Text Available The associations between Bisphenol-A (BPA exposure and reproductive hormone levels among women are unclear. A cross-sectional study was conducted among female workers from BPA-exposed and unexposed factories in China. Women’s blood samples were collected for assay of follicle-stimulating hormone (FSH, luteinizing hormone (LH, 17β-Estradiol (E2, prolactin (PRL, and progesterone (PROG. Their urine samples were collected for BPA measurement. In the exposed group, time weighted average exposure to BPA for an 8-h shift (TWA8, a measure incorporating historic exposure level, was generated based on personal air sampling. Multiple linear regression analyses were used to examine linear associations between urine BPA concentration and reproductive hormones after controlling for potential confounders. A total of 106 exposed and 250 unexposed female workers were included in this study. A significant positive association between increased urine BPA concentration and higher PRL and PROG levels were observed. Similar associations were observed after the analysis was carried out separately among the exposed and unexposed workers. In addition, a positive association between urine BPA and E2 was observed among exposed workers with borderline significance, while a statistically significant inverse association between urine BPA and FSH was observed among unexposed group. The results suggest that BPA exposure may lead to alterations in female reproductive hormone levels.

  19. Associations between Bisphenol A Exposure and Reproductive Hormones among Female Workers.

    Science.gov (United States)

    Miao, Maohua; Yuan, Wei; Yang, Fen; Liang, Hong; Zhou, Zhijun; Li, Runsheng; Gao, Ersheng; Li, De-Kun

    2015-10-22

    The associations between Bisphenol-A (BPA) exposure and reproductive hormone levels among women are unclear. A cross-sectional study was conducted among female workers from BPA-exposed and unexposed factories in China. Women's blood samples were collected for assay of follicle-stimulating hormone (FSH), luteinizing hormone (LH), 17β-Estradiol (E2), prolactin (PRL), and progesterone (PROG). Their urine samples were collected for BPA measurement. In the exposed group, time weighted average exposure to BPA for an 8-h shift (TWA8), a measure incorporating historic exposure level, was generated based on personal air sampling. Multiple linear regression analyses were used to examine linear associations between urine BPA concentration and reproductive hormones after controlling for potential confounders. A total of 106 exposed and 250 unexposed female workers were included in this study. A significant positive association between increased urine BPA concentration and higher PRL and PROG levels were observed. Similar associations were observed after the analysis was carried out separately among the exposed and unexposed workers. In addition, a positive association between urine BPA and E2 was observed among exposed workers with borderline significance, while a statistically significant inverse association between urine BPA and FSH was observed among unexposed group. The results suggest that BPA exposure may lead to alterations in female reproductive hormone levels.

  20. Association between adverse life events and addictive behaviors among male and female adolescents.

    Science.gov (United States)

    Lee, Grace P; Storr, Carla L; Ialongo, Nicholas S; Martins, Silvia S

    2012-01-01

    Adverse life events have been associated with gambling and substance use as they can serve as forms of escapism. Involvement in gambling and substance use can also place individuals in adversely stressful situations. To explore potential male-female differences in the association between addictive behavior and adverse life events among an urban cohort of adolescents. The study sample comprised of 515 adolescent participants in a randomized prevention trial. With self-reported data, four addictive behavior groups were created: nonsubstance users and nongamblers, substance users only, gamblers only, and substance users and gamblers. Multinomial logistic regression analyses with interaction terms of sex and adverse life events were conducted. Adverse life events and engaging in at least one addictive behavior were common for both sexes. Substance users and gamblers had more than twice the likelihood of nonsubstance users and nongamblers to experience any event as well as events of various domains (ie, relationship, violence, and instability). Neither relationship nor instability events' associations with the co-occurrence of substance use and gambling significantly differed between sexes. Conversely, females exposed to violence events were significantly more likely than similarly exposed males to report the co-occurrence of substance use and gambling. Findings from the current study prompt future studies to devote more attention to the development of effective programs that teach adaptive coping strategies to adolescents, particularly to females upon exposure to violence. Copyright © American Academy of Addiction Psychiatry.

  1. The Application of Classical and Neural Regression Models for the Valuation of Residential Real Estate

    Directory of Open Access Journals (Sweden)

    Mach Łukasz

    2017-06-01

    Full Text Available The research process aimed at building regression models, which helps to valuate residential real estate, is presented in the following article. Two widely used computational tools i.e. the classical multiple regression and regression models of artificial neural networks were used in order to build models. An attempt to define the utilitarian usefulness of the above-mentioned tools and comparative analysis of them is the aim of the conducted research. Data used for conducting analyses refers to the secondary transactional residential real estate market.

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

    Science.gov (United States)

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

    2007-09-01

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

  3. Sexual satisfaction in females with premenstrual symptoms.

    Science.gov (United States)

    Nowosielski, Krzysztof; Drosdzol, Agnieszka; Skrzypulec, Violetta; Plinta, Ryszard

    2010-11-01

    The impact of premenstrual symptoms, such as the premenstrual syndrome (PMS) and the premenstrual dysphoric disorder (PMDD), on sexual satisfaction, sexual distress, and sexual behaviors has not yet been established. To assess the correlates and risk factors of sexual satisfaction and to evaluate sexual behaviors among Polish women with premenstrual symptoms. 2,500 females, aged 18 to 45 years, from the Upper Silesian region of Poland were eligible for the questionnaire-based, prospective population study. All the inclusion criteria were met by 1,540 women who constituted the final study group. The participants were further divided into two subgroups: PMS+ (749 females) and PMS- (791 healthy subjects). Two additional subgroups were created: PMDD+ encompassing 32 subjects diagnosed with PMDD, and PMDD- comprising 32 healthy women, matched to the PMDD+ females for age, marital status, education level, employment status, place of living, and body mass index. A multiple logistic regression analysis was performed to evaluate the influence of PMS on sexual satisfaction and adjust for potential confounders. To evaluate risk factors for sexual dissatisfaction in a population of Polish females of reproductive age, diagnosed with PMS and PMDD. Women from the PMS+ group were less sexually satisfied than PMS- (77.73% vs. 88.66%, P=0.001) and reported more sexual distress (28.65% vs. 15.24%, P=0.001). There were no significant differences in sexual satisfaction between PMDD- and PMDD+. Sexual satisfaction correlated positively with a higher frequency of sexual intercourses and a higher level of education. The presence of PMS correlated negatively with sexual satisfaction, even after adjusting for potential confounders in the multivariate logistic regression model (odds ratio=0.48; confidence interval: 0.26-0.89; P=0.02). The presence of PMS is a risk factor for sexual dissatisfaction in Polish women of reproductive age. © 2010 International Society for Sexual Medicine.

  4. A method for nonlinear exponential regression analysis

    Science.gov (United States)

    Junkin, B. G.

    1971-01-01

    A computer-oriented technique is presented for performing a nonlinear exponential regression analysis on decay-type experimental data. The technique involves the least squares procedure wherein the nonlinear problem is linearized by expansion in a Taylor series. A linear curve fitting procedure for determining the initial nominal estimates for the unknown exponential model parameters is included as an integral part of the technique. A correction matrix was derived and then applied to the nominal estimate to produce an improved set of model parameters. The solution cycle is repeated until some predetermined criterion is satisfied.

  5. Multinomial logistic regression in workers' health

    Science.gov (United States)

    Grilo, Luís M.; Grilo, Helena L.; Gonçalves, Sónia P.; Junça, Ana

    2017-11-01

    In European countries, namely in Portugal, it is common to hear some people mentioning that they are exposed to excessive and continuous psychosocial stressors at work. This is increasing in diverse activity sectors, such as, the Services sector. A representative sample was collected from a Portuguese Services' organization, by applying a survey (internationally validated), which variables were measured in five ordered categories in Likert-type scale. A multinomial logistic regression model is used to estimate the probability of each category of the dependent variable general health perception where, among other independent variables, burnout appear as statistically significant.

  6. Three Contributions to Robust Regression Diagnostics

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2015-01-01

    Roč. 11, č. 2 (2015), s. 69-78 ISSN 1336-9180 Grant - others:GA ČR(CZ) GA13-01930S; Nadační fond na podporu vědy(CZ) Neuron Institutional support: RVO:67985807 Keywords : robust regression * robust econometrics * hypothesis test ing Subject RIV: BA - General Mathematics http://www.degruyter.com/view/j/jamsi.2015.11.issue-2/jamsi-2015-0013/jamsi-2015-0013.xml?format=INT

  7. SDE based regression for random PDEs

    KAUST Repository

    Bayer, Christian

    2016-01-01

    A simulation based method for the numerical solution of PDE with random coefficients is presented. By the Feynman-Kac formula, the solution can be represented as conditional expectation of a functional of a corresponding stochastic differential equation driven by independent noise. A time discretization of the SDE for a set of points in the domain and a subsequent Monte Carlo regression lead to an approximation of the global solution of the random PDE. We provide an initial error and complexity analysis of the proposed method along with numerical examples illustrating its behaviour.

  8. Bayesian regression of piecewise homogeneous Poisson processes

    Directory of Open Access Journals (Sweden)

    Diego Sevilla

    2015-12-01

    Full Text Available In this paper, a Bayesian method for piecewise regression is adapted to handle counting processes data distributed as Poisson. A numerical code in Mathematica is developed and tested analyzing simulated data. The resulting method is valuable for detecting breaking points in the count rate of time series for Poisson processes. Received: 2 November 2015, Accepted: 27 November 2015; Edited by: R. Dickman; Reviewed by: M. Hutter, Australian National University, Canberra, Australia.; DOI: http://dx.doi.org/10.4279/PIP.070018 Cite as: D J R Sevilla, Papers in Physics 7, 070018 (2015

  9. Selecting a Regression Saturated by Indicators

    DEFF Research Database (Denmark)

    Hendry, David F.; Johansen, Søren; Santos, Carlos

    We consider selecting a regression model, using a variant of Gets, when there are more variables than observations, in the special case that the variables are impulse dummies (indicators) for every observation. We show that the setting is unproblematic if tackled appropriately, and obtain the fin...... the finite-sample distribution of estimators of the mean and variance in a simple location-scale model under the null that no impulses matter. A Monte Carlo simulation confirms the null distribution, and shows power against an alternative of interest....

  10. Selecting a Regression Saturated by Indicators

    DEFF Research Database (Denmark)

    Hendry, David F.; Johansen, Søren; Santos, Carlos

    We consider selecting a regression model, using a variant of Gets, when there are more variables than observations, in the special case that the variables are impulse dummies (indicators) for every observation. We show that the setting is unproblematic if tackled appropriately, and obtain the fin...... the finite-sample distribution of estimators of the mean and variance in a simple location-scale model under the null that no impulses matter. A Monte Carlo simulation confirms the null distribution, and shows power against an alternative of interest...

  11. 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

  12. Fixed kernel regression for voltammogram feature extraction

    International Nuclear Information System (INIS)

    Acevedo Rodriguez, F J; López-Sastre, R J; Gil-Jiménez, P; Maldonado Bascón, S; Ruiz-Reyes, N

    2009-01-01

    Cyclic voltammetry is an electroanalytical technique for obtaining information about substances under analysis without the need for complex flow systems. However, classifying the information in voltammograms obtained using this technique is difficult. In this paper, we propose the use of fixed kernel regression as a method for extracting features from these voltammograms, reducing the information to a few coefficients. The proposed approach has been applied to a wine classification problem with accuracy rates of over 98%. Although the method is described here for extracting voltammogram information, it can be used for other types of signals

  13. Regression analysis for the social sciences

    CERN Document Server

    Gordon, Rachel A

    2010-01-01

    The book provides graduate students in the social sciences with the basic skills that they need to estimate, interpret, present, and publish basic regression models using contemporary standards. Key features of the book include: interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature. thorough integration of teaching statistical theory with teaching data processing and analysis. teaching of both SAS and Stata "side-by-side" and use of chapter exercises in which students practice programming and interpretation on the same data set and course exercises in which students can choose their own research questions and data set.

  14. SDE based regression for random PDEs

    KAUST Repository

    Bayer, Christian

    2016-01-06

    A simulation based method for the numerical solution of PDE with random coefficients is presented. By the Feynman-Kac formula, the solution can be represented as conditional expectation of a functional of a corresponding stochastic differential equation driven by independent noise. A time discretization of the SDE for a set of points in the domain and a subsequent Monte Carlo regression lead to an approximation of the global solution of the random PDE. We provide an initial error and complexity analysis of the proposed method along with numerical examples illustrating its behaviour.

  15. Neutrosophic Correlation and Simple Linear Regression

    Directory of Open Access Journals (Sweden)

    A. A. Salama

    2014-09-01

    Full Text Available Since the world is full of indeterminacy, the neutrosophics found their place into contemporary research. The fundamental concepts of neutrosophic set, introduced by Smarandache. Recently, Salama et al., introduced the concept of correlation coefficient of neutrosophic data. In this paper, we introduce and study the concepts of correlation and correlation coefficient of neutrosophic data in probability spaces and study some of their properties. Also, we introduce and study the neutrosophic simple linear regression model. Possible applications to data processing are touched upon.

  16. Spectral density regression for bivariate extremes

    KAUST Repository

    Castro Camilo, Daniela

    2016-05-11

    We introduce a density regression model for the spectral density of a bivariate extreme value distribution, that allows us to assess how extremal dependence can change over a covariate. Inference is performed through a double kernel estimator, which can be seen as an extension of the Nadaraya–Watson estimator where the usual scalar responses are replaced by mean constrained densities on the unit interval. Numerical experiments with the methods illustrate their resilience in a variety of contexts of practical interest. An extreme temperature dataset is used to illustrate our methods. © 2016 Springer-Verlag Berlin Heidelberg

  17. SPE dose prediction using locally weighted regression

    International Nuclear Information System (INIS)

    Hines, J. W.; Townsend, L. W.; Nichols, T. F.

    2005-01-01

    When astronauts are outside earth's protective magnetosphere, they are subject to large radiation doses resulting from solar particle events (SPEs). The total dose received from a major SPE in deep space could cause severe radiation poisoning. The dose is usually received over a 20-40 h time interval but the event's effects may be mitigated with an early warning system. This paper presents a method to predict the total dose early in the event. It uses a locally weighted regression model, which is easier to train and provides predictions as accurate as neural network models previously used. (authors)

  18. 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

  19. SPE dose prediction using locally weighted regression

    International Nuclear Information System (INIS)

    Hines, J. W.; Townsend, L. W.; Nichols, T. F.

    2005-01-01

    When astronauts are outside Earth's protective magnetosphere, they are subject to large radiation doses resulting from solar particle events. The total dose received from a major solar particle event in deep space could cause severe radiation poisoning. The dose is usually received over a 20-40 h time interval but the event's effects may be reduced with an early warning system. This paper presents a method to predict the total dose early in the event. It uses a locally weighted regression model, which is easier to train, and provides predictions as accurate as the neural network models that were used previously. (authors)

  20. AIRLINE ACTIVITY FORECASTING BY REGRESSION MODELS

    Directory of Open Access Journals (Sweden)

    Н. Білак

    2012-04-01

    Full Text Available Proposed linear and nonlinear regression models, which take into account the equation of trend and seasonality indices for the analysis and restore the volume of passenger traffic over the past period of time and its prediction for future years, as well as the algorithm of formation of these models based on statistical analysis over the years. The desired model is the first step for the synthesis of more complex models, which will enable forecasting of passenger (income level airline with the highest accuracy and time urgency.

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

    OpenAIRE

    Guns, M.; Vanacker, Veerle

    2012-01-01

    Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logisti...

  2. Borderline Personality Disorder as a Female Phenotypic Expression of Psychopathy?

    Science.gov (United States)

    Sprague, Jenessa; Javdani, Shabnam; Sadeh, Naomi; Newman, Joseph P.; Verona, Edelyn

    2011-01-01

    Evidence suggests that the combination of the interpersonal-affective (F1) and impulsive-antisocial (F2) features of psychopathy may be associated with borderline personality disorder (BPD), specifically among women (e.g., Coid, 1993; Hicks, Vaidyana-than, & Patrick, 2010). However, empirical research explicitly examining gendered relationships between BPD and psychopathy factors is lacking. To further inform this area of research, we investigated the hypothesis that the interplay between the two psychopathy factors is associated with BPD among women across two studies. Study 1 consisted of a college sample of 318 adults (51% women), and Study 2 consisted of a large sample of 488 female prisoners. The interpersonal-affective (F1) and impulsiveantisocial psychopathy (F2) scores, measured with self-report and clinician-rated indices, respectively, were entered as explanatory variables in regression analyses to investigate their unique contributions to BPD traits. Across two independent samples, results indicated that the interaction of high F1 and F2 psychopathy scores was associated with BPD in women. This association was found to be specific to women in Study 1. These results suggest that BPD and psychopathy, at least as they are measured by current instruments, overlap in women and, accordingly, may reflect gender-differentiated phenotypic expressions of similar dispositional vulnerabilities. PMID:22452756

  3. A simple beam analyser

    International Nuclear Information System (INIS)

    Lemarchand, G.

    1977-01-01

    (ee'p) experiments allow to measure the missing energy distribution as well as the momentum distribution of the extracted proton in the nucleus versus the missing energy. Such experiments are presently conducted on SACLAY's A.L.S. 300 Linac. Electrons and protons are respectively analysed by two spectrometers and detected in their focal planes. Counting rates are usually low and include time coincidences and accidentals. Signal-to-noise ratio is dependent on the physics of the experiment and the resolution of the coincidence, therefore it is mandatory to get a beam current distribution as flat as possible. Using new technologies has allowed to monitor in real time the behavior of the beam pulse and determine when the duty cycle can be considered as being good with respect to a numerical basis

  4. EEG analyses with SOBI.

    Energy Technology Data Exchange (ETDEWEB)

    Glickman, Matthew R.; Tang, Akaysha (University of New Mexico, Albuquerque, NM)

    2009-02-01

    The motivating vision behind Sandia's MENTOR/PAL LDRD project has been that of systems which use real-time psychophysiological data to support and enhance human performance, both individually and of groups. Relevant and significant psychophysiological data being a necessary prerequisite to such systems, this LDRD has focused on identifying and refining such signals. The project has focused in particular on EEG (electroencephalogram) data as a promising candidate signal because it (potentially) provides a broad window on brain activity with relatively low cost and logistical constraints. We report here on two analyses performed on EEG data collected in this project using the SOBI (Second Order Blind Identification) algorithm to identify two independent sources of brain activity: one in the frontal lobe and one in the occipital. The first study looks at directional influences between the two components, while the second study looks at inferring gender based upon the frontal component.

  5. Pathway-based analyses.

    Science.gov (United States)

    Kent, Jack W

    2016-02-03

    New technologies for acquisition of genomic data, while offering unprecedented opportunities for genetic discovery, also impose severe burdens of interpretation and penalties for multiple testing. The Pathway-based Analyses Group of the Genetic Analysis Workshop 19 (GAW19) sought reduction of multiple-testing burden through various approaches to aggregation of highdimensional data in pathways informed by prior biological knowledge. Experimental methods testedincluded the use of "synthetic pathways" (random sets of genes) to estimate power and false-positive error rate of methods applied to simulated data; data reduction via independent components analysis, single-nucleotide polymorphism (SNP)-SNP interaction, and use of gene sets to estimate genetic similarity; and general assessment of the efficacy of prior biological knowledge to reduce the dimensionality of complex genomic data. The work of this group explored several promising approaches to managing high-dimensional data, with the caveat that these methods are necessarily constrained by the quality of external bioinformatic annotation.

  6. Analysing Access Control Specifications

    DEFF Research Database (Denmark)

    Probst, Christian W.; Hansen, René Rydhof

    2009-01-01

    When prosecuting crimes, the main question to answer is often who had a motive and the possibility to commit the crime. When investigating cyber crimes, the question of possibility is often hard to answer, as in a networked system almost any location can be accessed from almost anywhere. The most...... common tool to answer this question, analysis of log files, faces the problem that the amount of logged data may be overwhelming. This problems gets even worse in the case of insider attacks, where the attacker’s actions usually will be logged as permissible, standard actions—if they are logged at all....... Recent events have revealed intimate knowledge of surveillance and control systems on the side of the attacker, making it often impossible to deduce the identity of an inside attacker from logged data. In this work we present an approach that analyses the access control configuration to identify the set...

  7. Network class superposition analyses.

    Directory of Open Access Journals (Sweden)

    Carl A B Pearson

    Full Text Available Networks are often used to understand a whole system by modeling the interactions among its pieces. Examples include biomolecules in a cell interacting to provide some primary function, or species in an environment forming a stable community. However, these interactions are often unknown; instead, the pieces' dynamic states are known, and network structure must be inferred. Because observed function may be explained by many different networks (e.g., ≈ 10(30 for the yeast cell cycle process, considering dynamics beyond this primary function means picking a single network or suitable sample: measuring over all networks exhibiting the primary function is computationally infeasible. We circumvent that obstacle by calculating the network class ensemble. We represent the ensemble by a stochastic matrix T, which is a transition-by-transition superposition of the system dynamics for each member of the class. We present concrete results for T derived from boolean time series dynamics on networks obeying the Strong Inhibition rule, by applying T to several traditional questions about network dynamics. We show that the distribution of the number of point attractors can be accurately estimated with T. We show how to generate Derrida plots based on T. We show that T-based Shannon entropy outperforms other methods at selecting experiments to further narrow the network structure. We also outline an experimental test of predictions based on T. We motivate all of these results in terms of a popular molecular biology boolean network model for the yeast cell cycle, but the methods and analyses we introduce are general. We conclude with open questions for T, for example, application to other models, computational considerations when scaling up to larger systems, and other potential analyses.

  8. 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.

  9. Love, Trust, and HIV Risk Among Female Sex Workers and Their Intimate Male Partners.

    Science.gov (United States)

    Syvertsen, Jennifer L; Bazzi, Angela Robertson; Martinez, Gustavo; Rangel, M Gudelia; Ulibarri, Monica D; Fergus, Kirkpatrick B; Amaro, Hortensia; Strathdee, Steffanie A

    2015-08-01

    We examined correlates of love and trust among female sex workers and their noncommercial male partners along the Mexico-US border. From 2011 to 2012, 322 partners in Tijuana and Ciudad Juárez, Mexico, completed assessments of love and trust. Cross-sectional dyadic regression analyses identified associations of relationship characteristics and HIV risk behaviors with love and trust. Within 161 couples, love and trust scores were moderately high (median 70/95 and 29/40 points, respectively) and correlated with relationship satisfaction. In regression analyses of HIV risk factors, men and women who used methamphetamine reported lower love scores, whereas women who used heroin reported slightly higher love. In an alternate model, men with concurrent sexual partners had lower love scores. For both partners, relationship conflict was associated with lower trust. Love and trust are associated with relationship quality, sexual risk, and drug use patterns that shape intimate partners' HIV risk. HIV interventions should consider the emotional quality of sex workers' intimate relationships.

  10. Bayesian nonlinear regression for large small problems

    KAUST Repository

    Chakraborty, Sounak; Ghosh, Malay; Mallick, Bani K.

    2012-01-01

    Statistical modeling and inference problems with sample sizes substantially smaller than the number of available covariates are challenging. This is known as large p small n problem. Furthermore, the problem is more complicated when we have multiple correlated responses. We develop multivariate nonlinear regression models in this setup for accurate prediction. In this paper, we introduce a full Bayesian support vector regression model with Vapnik's ε-insensitive loss function, based on reproducing kernel Hilbert spaces (RKHS) under the multivariate correlated response setup. This provides a full probabilistic description of support vector machine (SVM) rather than an algorithm for fitting purposes. We have also introduced a multivariate version of the relevance vector machine (RVM). Instead of the original treatment of the RVM relying on the use of type II maximum likelihood estimates of the hyper-parameters, we put a prior on the hyper-parameters and use Markov chain Monte Carlo technique for computation. We have also proposed an empirical Bayes method for our RVM and SVM. Our methods are illustrated with a prediction problem in the near-infrared (NIR) spectroscopy. A simulation study is also undertaken to check the prediction accuracy of our models. © 2012 Elsevier Inc.

  11. Regression testing in the TOTEM DCS

    International Nuclear Information System (INIS)

    Rodríguez, F Lucas; Atanassov, I; Burkimsher, P; Frost, O; Taskinen, J; Tulimaki, V

    2012-01-01

    The Detector Control System of the TOTEM experiment at the LHC is built with the industrial product WinCC OA (PVSS). The TOTEM system is generated automatically through scripts using as input the detector Product Breakdown Structure (PBS) structure and its pinout connectivity, archiving and alarm metainformation, and some other heuristics based on the naming conventions. When those initial parameters and automation code are modified to include new features, the resulting PVSS system can also introduce side-effects. On a daily basis, a custom developed regression testing tool takes the most recent code from a Subversion (SVN) repository and builds a new control system from scratch. This system is exported in plain text format using the PVSS export tool, and compared with a system previously validated by a human. A report is sent to the developers with any differences highlighted, in readiness for validation and acceptance as a new stable version. This regression approach is not dependent on any development framework or methodology. This process has been satisfactory during several months, proving to be a very valuable tool before deploying new versions in the production systems.

  12. Supporting Regularized Logistic Regression Privately and Efficiently

    Science.gov (United States)

    Li, Wenfa; Liu, Hongzhe; Yang, Peng; Xie, Wei

    2016-01-01

    As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc. PMID:27271738

  13. Structural Break Tests Robust to Regression Misspecification

    Directory of Open Access Journals (Sweden)

    Alaa Abi Morshed

    2018-05-01

    Full Text Available Structural break tests for regression models are sensitive to model misspecification. We show—analytically and through simulations—that the sup Wald test for breaks in the conditional mean and variance of a time series process exhibits severe size distortions when the conditional mean dynamics are misspecified. We also show that the sup Wald test for breaks in the unconditional mean and variance does not have the same size distortions, yet benefits from similar power to its conditional counterpart in correctly specified models. Hence, we propose using it as an alternative and complementary test for breaks. We apply the unconditional and conditional mean and variance tests to three US series: unemployment, industrial production growth and interest rates. Both the unconditional and the conditional mean tests detect a break in the mean of interest rates. However, for the other two series, the unconditional mean test does not detect a break, while the conditional mean tests based on dynamic regression models occasionally detect a break, with the implied break-point estimator varying across different dynamic specifications. For all series, the unconditional variance does not detect a break while most tests for the conditional variance do detect a break which also varies across specifications.

  14. Supporting Regularized Logistic Regression Privately and Efficiently.

    Science.gov (United States)

    Li, Wenfa; Liu, Hongzhe; Yang, Peng; Xie, Wei

    2016-01-01

    As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc.

  15. Bayesian nonlinear regression for large small problems

    KAUST Repository

    Chakraborty, Sounak

    2012-07-01

    Statistical modeling and inference problems with sample sizes substantially smaller than the number of available covariates are challenging. This is known as large p small n problem. Furthermore, the problem is more complicated when we have multiple correlated responses. We develop multivariate nonlinear regression models in this setup for accurate prediction. In this paper, we introduce a full Bayesian support vector regression model with Vapnik\\'s ε-insensitive loss function, based on reproducing kernel Hilbert spaces (RKHS) under the multivariate correlated response setup. This provides a full probabilistic description of support vector machine (SVM) rather than an algorithm for fitting purposes. We have also introduced a multivariate version of the relevance vector machine (RVM). Instead of the original treatment of the RVM relying on the use of type II maximum likelihood estimates of the hyper-parameters, we put a prior on the hyper-parameters and use Markov chain Monte Carlo technique for computation. We have also proposed an empirical Bayes method for our RVM and SVM. Our methods are illustrated with a prediction problem in the near-infrared (NIR) spectroscopy. A simulation study is also undertaken to check the prediction accuracy of our models. © 2012 Elsevier Inc.

  16. Hyperspectral Unmixing with Robust Collaborative Sparse Regression

    Directory of Open Access Journals (Sweden)

    Chang Li

    2016-07-01

    Full Text Available Recently, sparse unmixing (SU of hyperspectral data has received particular attention for analyzing remote sensing images. However, most SU methods are based on the commonly admitted linear mixing model (LMM, which ignores the possible nonlinear effects (i.e., nonlinearity. In this paper, we propose a new method named robust collaborative sparse regression (RCSR based on the robust LMM (rLMM for hyperspectral unmixing. The rLMM takes the nonlinearity into consideration, and the nonlinearity is merely treated as outlier, which has the underlying sparse property. The RCSR simultaneously takes the collaborative sparse property of the abundance and sparsely distributed additive property of the outlier into consideration, which can be formed as a robust joint sparse regression problem. The inexact augmented Lagrangian method (IALM is used to optimize the proposed RCSR. The qualitative and quantitative experiments on synthetic datasets and real hyperspectral images demonstrate that the proposed RCSR is efficient for solving the hyperspectral SU problem compared with the other four state-of-the-art algorithms.

  17. Supporting Regularized Logistic Regression Privately and Efficiently.

    Directory of Open Access Journals (Sweden)

    Wenfa Li

    Full Text Available As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc.

  18. Casual Attributions of Adolescent Females in a Masculine Domain.

    Science.gov (United States)

    Krauser, Barbara Z.; Ballif, Bonnie L.

    Achievement attributions of adolescent females in the masculine domain of mathematics were investigated in relation to self-schemas for gender, expectancy of success, and mathematics achievement. The most important findings revealed by multiple regression analysis were that mathematics achievement and the self-schema for masculinity predicted…

  19. Sexual initiation and contraceptive use among female adolescents ...

    African Journals Online (AJOL)

    kemrilib

    regression model to quantify the effects of a set of factors on female .... based on a weighing of benefits (such as school fees, .... urban areas are exposed to a more diverse life style .... received money or gift or favours in return for sex.

  20. Competing Risks Quantile Regression at Work

    DEFF Research Database (Denmark)

    Dlugosz, Stephan; Lo, Simon M. S.; Wilke, Ralf

    2017-01-01

    large-scale maternity duration data with multiple competing risks derived from German linked social security records to analyse how public policies are related to the length of economic inactivity of young mothers after giving birth. Our results show that the model delivers detailed insights...