ISBN-10:
1461413524
ISBN-13:
9781461413523
Pub. Date:
09/01/2011
Publisher:
Springer New York
Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models / Edition 2

Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models / Edition 2

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Overview

Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models / Edition 2

This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes.

Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way.

The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided.

Product Details

ISBN-13: 9781461413523
Publisher: Springer New York
Publication date: 09/01/2011
Series: Statistics for Biology and Health
Edition description: 2nd ed. 2012
Pages: 512
Sales rank: 270,419
Product dimensions: 6.30(w) x 9.40(h) x 1.40(d)

About the Author

The authors are on the faculty in the Division of Biostatistics, Department of Epidemiology and Biostatistics, University of California, San Francisco, and are authors or co-authors of more than 200 methodological as well as applied papers in the biological and biomedical sciences. The senior author, Charles E. McCulloch, is head of the Division and author of Generalized Linear Mixed Models (2003), Generalized, Linear, and Mixed Models (2000), and Variance Components (1992).

Table of Contents

Introduction.- Exploratory and Descriptive Methods.- Basic Statistical Methods.- Linear Regression.- Logistic Regression.- Survival Analysis.- Repeated Measures Analysis.- Generalized Linear Models.- Strengthening Casual Inference.- Predictor Selection.- Complex Surveys.- Summary.

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