The scientist’s investigation covers issues in Statistics, Logistic regression, Regression analysis, Goodness of fit and Econometrics. His biological study spans a wide range of topics, including Generalised logistic function, Calibration, Predictive value of tests, Factor regression model and Multinomial logistic regression. The concepts of his Factor regression model study are interwoven with issues in Binomial regression, Logistic model tree, Unit-weighted regression and Cross-sectional regression.
The Regression analysis study which covers Covariate that intersects with Data mining, Logistic distribution and Data science. In general Goodness of fit study, his work on Hosmer–Lemeshow test often relates to the realm of Context, thereby connecting several areas of interest. His Econometrics study deals with Public health intersecting with Physical therapy.
His primary areas of investigation include Statistics, Logistic regression, Econometrics, Goodness of fit and Regression analysis. His Logistic regression research includes elements of Cross-sectional regression, Multinomial logistic regression, Linear regression and Factor regression model. His Multinomial logistic regression course of study focuses on Generalised logistic function and Logistic model tree.
His study explores the link between Econometrics and topics such as Ordered logit that cross with problems in Ordinal data and Ordinal regression. His work in the fields of Goodness of fit, such as Hosmer–Lemeshow test, overlaps with other areas such as Lack-of-fit sum of squares. His work on Regression analysis is being expanded to include thematically relevant topics such as Missing data.
David W. Hosmer mainly focuses on Statistics, Econometrics, Logistic regression, Injury prevention and Multinomial logistic regression. His is doing research in Regression analysis, Ordinal data, Ordinal regression, Binomial regression and Survival data, both of which are found in Statistics. His research in Econometrics intersects with topics in Goodness of fit, Ordered logit and Proportional hazards model.
His work deals with themes such as Regression dilution, Cross-sectional regression and Factor regression model, which intersect with Logistic regression. His multidisciplinary approach integrates Multinomial logistic regression and Multinomial test in his work. He has researched Generalised logistic function in several fields, including Multiple logistic regression analysis, Segmented regression and Logistic model tree.
David W. Hosmer spends much of his time researching Statistics, Logistic regression, Multinomial logistic regression, Surgery and Econometrics. In his research, David W. Hosmer performs multidisciplinary study on Statistics and Injury prevention. His studies in Logistic regression integrate themes in fields like Regression analysis, Cross-sectional regression, Logit and Factor regression model.
His work carried out in the field of Factor regression model brings together such families of science as Multiple logistic regression analysis, Logistic model tree, Survival data and Regression dilution. His work in Multinomial logistic regression addresses subjects such as Binomial regression, which are connected to disciplines such as Regression diagnostic and Logistic distribution. David W. Hosmer combines subjects such as Goodness of fit, Hosmer–Lemeshow test and Ordered logit with his study of Econometrics.
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Applied Logistic Regression
David W. Hosmer;Stanley Lemeshow.
Applied Survival Analysis: Regression Modeling of Time-to-Event Data
David W. Hosmer;Stanley Lemeshow;Susanne May.
A population-based perspective of the hospital incidence and case-fatality rates of deep vein thrombosis and pulmonary embolism. The Worcester DVT Study
Frederick A. Anderson;H. Brownell Wheeler;Robert J. Goldberg;David W. Hosmer.
JAMA Internal Medicine (1991)
Purposeful selection of variables in logistic regression
Zoran Bursac;C Heath Gauss;David Keith Williams;David W Hosmer.
Source Code for Biology and Medicine (2008)
A REVIEW OF GOODNESS OF FIT STATISTICS FOR USE IN THE DEVELOPMENT OF LOGISTIC REGRESSION MODELS
Stanley Lemeshow;David W. Hosmer.
American Journal of Epidemiology (1982)
Goodness of fit tests for the multiple logistic regression model
David W. Hosmer;Stanley Lemesbow.
Communications in Statistics-theory and Methods (1980)
A comparison of goodness-of-fit tests for the logistic regression model.
D. W. Hosmer;T. Hosmer;S. Le Cessie;S. Lemeshow.
Statistics in Medicine (1997)
A meta-analysis of sex differences prevalence, incidence and severity of osteoarthritis
Velandai K. Srikanth;Jayne L. Fryer;Guangju Zhai;Tania M. Winzenberg.
Osteoarthritis and Cartilage (2005)
Applied Logistic Regression.
Steven L. Gortmaker;David W. Hosmer;Stanley Lemeshow.
Contemporary Sociology (1994)
Confidence interval estimation of interaction.
David W. Hosmer;Stanley Lemeshow.
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