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If you are a researcher or student with experience in multiple linear regression and want to learn about logistic regression, this book is for you! Informal and nontechnical, Paul Allison's Logistic Regression Using SAS: Theory and Application both explains the theory behind logistic regression and looks at all the practical details involved in its implementation using SAS. Several social science real-world examples are included in full detail. The book also explains the differences and similarities among the many generalizations of the logistic regression model. The following topics are covered: binary logit analysis, logit analysis of contingency tables, multinomial logit analysis, ordered logit analysis, discrete-choice analysis with the PHREG procedure, and Poisson regression. Other highlights include discussions of how to use the GENMOD procedure to do log-linear analysis and GEE estimation for longitudinal binary data. Only basic knowledge of the SAS DATA step is assumed.
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About the Author:
Paul D. Allison is a Professor of Sociology and Epidemiology at the University of Pennsylvaniawhere 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.
Review:
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
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
"About this title" may belong to another edition of this title.
- PublisherSas Inst
- Publication date1991
- ISBN 10 1580253520
- ISBN 13 9781580253529
- BindingPaperback
- Edition number1
- Number of pages288
- Rating
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Logistic Regression Using the SAS System : Theory and Application
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Logistic Regression Using the SAS System : Theory and Application
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