Logistic Regression Using SAS: Theory and Application

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 the SAS System. Several social science real-world examples are included in full detail. This 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 on how to use the GENMOD procedure to do loglinear analysis and GEE estimation for longitudinal binary data. Only basic knowledge of the SAS DATA step is assumed.

Supports releases 6.12 and higher of SAS software.

Paul D. Allison

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.