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Regression Modeling Strategies

With Applications to Linear Models, Logistic Regression, and Survival Analysis
BuchGebunden
582 Seiten
Englisch
Springererschienen am26.08.20152. Aufl.
Most of the methods in this text apply to all regression models, but special emphasis is given to multiple regression using generalised least squares for longitudinal data, the binary logistic model, models for ordinal responses, parametric survival regression models and the Cox semi parametric survival model.mehr
Verfügbare Formate
BuchGebunden
EUR128,39
BuchKartoniert, Paperback
EUR80,24
E-BookPDF1 - PDF WatermarkE-Book
EUR80,24

Produkt

KlappentextMost of the methods in this text apply to all regression models, but special emphasis is given to multiple regression using generalised least squares for longitudinal data, the binary logistic model, models for ordinal responses, parametric survival regression models and the Cox semi parametric survival model.
Details
ISBN/GTIN978-3-319-19424-0
ProduktartBuch
EinbandartGebunden
Verlag
Erscheinungsjahr2015
Erscheinungsdatum26.08.2015
Auflage2. Aufl.
ReiheSpringer Series in Statistics
Seiten582 Seiten
SpracheEnglisch
Gewicht1316 g
IllustrationenXXV, 582 p. 157 illus., 53 illus. in color.
Artikel-Nr.15575982

Inhalt/Kritik

Inhaltsverzeichnis
Introduction.- General Aspects of Fitting Regression Models.- Missing Data.- Multivariable Modeling Strategies.- Describing, Resampling, Validating and Simplifying the Model.- R Software.- Modeling Longitudinal Responses using Generalized Least Squares.- Case Study in Data Reduction.- Overview of Maximum Likelihood Estimation.- Binary Logistic Regression.- Binary Logistic Regression Case Study 1.- Logistic Model Case Study 2: Survival of Titanic Passengers.- Ordinal Logistic Regression.- Case Study in Ordinal Regression, Data Reduction and Penalization.- Regression Models for Continuous Y and Case Study in Ordinal Regression.- Transform-Both-Sides Regression.- Introduction to Survival Analysis.- Parametric Survival Models.- Case Study in Parametric Survival Modeling and Model Approximation.- Cox Proportional Hazards Regression Model.- Case Study in Cox Regression.- Appendix.mehr
Kritik
"The aim and scope of this edition to provide graduate students and professional and early career researchers with insights, understandings and working knowledge of regression modelling. ... . The book is sequentially organized and well structured and many chapters are self-contained. It includes many useful topics and techniques for graduate .students and researchers alike. This book can be used as a textbook and equally as a reference book." (Technometrics, Vol. 58 (2), February, 2016)mehr

Autor

Frank E. Harrell, Jr. is Professor of Biostatistics and Chair, Department of Biostatistics, Vanderbilt University School of Medicine, Nashville. He has developed numerous methods for predictive modeling, quantifying predictive accuracy and model validation and has published numerous predictive models and articles on applied statistics, medical research and clinical trials. He is on the editorial board for several biomedical and methodologic journals. He is a Fellow of the American Statistical Association (ASA) and a consultant to the U.S. Food and Drug Administration and to the pharmaceutical industry. He teaches a graduate course in regression modeling strategies and a course in biostatistics for medical researchers. In 2014 he was chosen to receive the WJ Dixon Award for Excellence in Statistical Consulting by the ASA.
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