Paul Allison

Paul Allison
Professor, University of Pennsylvania

Paul D. Allison is Professor of Sociology at the University of Pennsylvania and President of Statistical Horizons LLC. He is the author of Logistic Regression Using SAS®: Theory and Application, Survival Analysis Using SAS®: A Practical Guide, and Fixed Effects Regression Methods for Longitudinal Data Using SAS®. Paul has also written numerous statistical papers and published extensively on the subject of scientists’ careers. He frequently teaches public short courses on the methods described in his books. You can visit his website at www.statisticalhorizons.com.

By This Author

Logistic Regression Using SAS®: Theory and Application, Second Edition

Logistic Regression Using SAS®: Theory and Application, Second Edition

By Paul Allison

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. Includes several real-world examples in full detail. 

Survival analysis using SAS

Survival Analysis Using SAS®: A Practical Guide, Second Edition

By Paul Allison

Biomedical and social science researchers who want to analyze survival data with SAS will find just what they need with this easy-to-read and comprehensive guide. Teaches many aspects of data input and manipulation. Numerous examples of SAS code and output make this an eminently practical book, completely updated for SAS®9. 

Fixed Effects Regression Methods for Longitudinal Data Using SAS®

Fixed Effects Regression Methods for Longitudinal Data Using SAS®

By Paul Allison

This straightforward text shows you how to estimate fixed effects models with several SAS procedures that are appropriate for different kinds of outcome variables. The theoretical background of each model is explained, and the models are illustrated with detailed examples using real data. 

Logistic Regression Using the SAS System: Theory and Application

Logistic Regression Using the SAS® System: Theory and Applications

By Paul Allison

Details the theory behind logistic regression and looks at the details involved in its implementation using SAS. Addresses binary logit analysis, logit analysis of contingency tables, multinomial logit analysis, ordered logit analysis, discrete-choice analysis with the PHREG procedure, and Poisson regression. 

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