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Regression Models as a Tool in Medical Research

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Author:
Werner Vach
Publisher: Chapman & Hall/CRC
Copyright: 2013
ISBN-13: 978-1-4665-17486
Pages: 473; hardcover
Price: $74.50
Supplements:Datasets and solutions to exercises

Comment from the Stata technical group

Regression Models as a Tool in Medical Research, by Werner Vach, is a practical guide to regression analysis for medical researchers. It describes the important aspects of regression models for continuous, binary, survival, and count outcomes—all commonly encountered in medical research. The regression models covered include linear regression, logistic regression, Cox regression, and Poisson regression. The book also discusses methods to handle different types of data structures such as matched case–control data and longitudinal data. The “hands-on” examples reinforce the concepts described in each chapter, and the “in-a-nutshell” summaries after each chapter provide a quick refresher of the topics covered.

The book has five parts. The first part covers the basic concepts of the linear, logistic, and Cox regressions commonly used to analyze medical data. The second part discusses more advanced topics such as modeling of nonlinear effects and analysis of longitudinal and clustered data, as well as sample-size and power considerations when designing a study. The third part concentrates on prediction, and the fourth part briefly covers some alternatives to regression modeling. Finally, the fifth part provides mathematical details behind the main regression concepts.

The numerical examples and graphs are produced with Stata; all datasets used in the examples and solutions to all exercises are available at www.imbi.uni-freiburg.de/RegModToolInMedRes.

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