Regression Methods in Biostatistics Linear, Logistic, Survival, and Repeated Measures Models

ISBN-10: 0387202757
ISBN-13: 9780387202754
Edition: 2007
List price: $129.00
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Description: 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  More...

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Book details

List price: $129.00
Copyright year: 2007
Publisher: Springer
Binding: Hardcover
Pages: 344
Size: 6.00" wide x 7.25" long x 1.25" tall
Weight: 1.298
Language: English

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. For many students and researchers learning to use these methods, this one book may be all they need to conduct and interpret multipredictor regression analyses.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).

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

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