Regression Modeling Strategies
With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis
Authors: Harrell, Frank
Free Preview- Fully revised new edition features new material and color figures
- Published with mature, supplementary R package: rms
- New chapters and sections on generalized least squares for analysis of serial response data, redundancy analysis, bootstrap confidence intervals for rankings of predictors, expanded material on multiple imputation and predictive mean matching and more
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- About this Textbook
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This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software. In keeping with the previous edition, this book is about the art and science of data analysis and predictive modelling, which entails choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasises problem solving strategies that address the many issues arising when developing multi-variable models using real data and not standard textbook examples.
Regression Modelling Strategies presents full-scale case studies of non-trivial data-sets instead of over-simplified illustrations of each method. These case studies use freely available R functions that make the multiple imputation, model building, validation and interpretation tasks described in the book relatively easy to do. 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. A new emphasis is given to the robust analysis of continuous dependent variables using ordinal regression.
As in the first edition, this text is intended for Masters' or PhD. level graduate students who have had a general introductory probability and statistics course and who are well versed in ordinary multiple regression and intermediate algebra. The book will also serve as a reference for data analysts and statistical methodologists, as it contains an up-to-date survey and bibliography of modern statistical modelling techniques. - About the authors
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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.
- Reviews
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“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)
- Table of contents (21 chapters)
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Introduction
Pages 1-11
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General Aspects of Fitting Regression Models
Pages 13-44
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Missing Data
Pages 45-61
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Multivariable Modeling Strategies
Pages 63-102
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Describing, Resampling, Validating, and Simplifying the Model
Pages 103-126
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Table of contents (21 chapters)
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Regression Modeling Strategies
- Book Subtitle
- With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis
- Authors
-
- Frank Harrell
- Series Title
- Springer Series in Statistics
- Copyright
- 2015
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer Nature Switzerland AG
- eBook ISBN
- 978-3-319-19425-7
- DOI
- 10.1007/978-3-319-19425-7
- Hardcover ISBN
- 978-3-319-19424-0
- Softcover ISBN
- 978-3-319-33039-6
- Series ISSN
- 0172-7397
- Edition Number
- 2
- Number of Pages
- XXV, 582
- Number of Illustrations
- 104 b/w illustrations, 53 illustrations in colour
- Topics
