1999•Unpublished venueRequires access

Logistic Regression Using SAS: Theory and Application

Paul D. Allison

Open publisher page 824 citations

Abstract

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, this book 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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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, this book 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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Available abstract

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, this book 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

Key concepts: Multinomial logistic regression, Logistic regression, Logit, Statistics, Econometrics, Regression diagnostic, Contingency table, Regression analysis

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