Written in an informal and non-technical style, this book first explains the theory behind logistic regression and then shows how to implement it using the SAS System. Allison includes several detailed, real-world examples of the social sciences to provide readers with a better understanding of the material. He also explores the differences and similarities among the many generalizations of the logistic regression model.
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Paul D. Allison is a Professor of Sociology and Epidemiology at the University of Pennsylvania where he teaches graduate courses in survival analysis and categorical data analysis. Every summer he teaches a five-day workshop about logistic regression that is attended by researchers from around the United States and Canada. Besides his numerous statistical papers, he has also published extensively on the subject of scientists' careers.
The book treats logistic regression as the next topic in the regression methodology, so one is expected to have learned regression analysis already. Consistent with the author's social-science background, he begins with models for dichotomous responses. The logic model is treated as the solution to the problems one would encounter with using linear regression for binary response data. Both PROC LOGISTIC and PROC GENMOD are introduced. PROC REG is cleverly included, though, as a diagnostic for collinearity. The excellent binary data diagnostics in PROC LOGISTIC and PROC GENMOD are covered extensively. The probit model is also considered. --Eric Ziegel, Technometrics, Book Review Editor
Users of other software and other books are probably tired of my hype for these inexpensive books that integrate applied statistics and SAS procedures. This is another great applied-statistics and SAS-application guidebook, which should be essential to the library of anyone who uses SAS. --Eric Ziegel, Technometrics, Book Review Editor
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