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
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.
*Our books are also available in print and e-book formats
from your local bookstore or favorite online bookseller.
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.
*Our books are also available in print and e-book formats
from your local bookstore or favorite online bookseller.
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.
*This book is out of print.
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.
Featured Authors
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Terisa Roberts is a director and Global Solution lead for Risk Modeling and Decisioning at SAS. She has extensive experience in quantitative risk management, regulatory compliance, and model governance and validation. She has worked in financial services, telecommunications, government, energy, and retail sectors.
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Todd Case has been working in the pharmaceutical industry as a statistical programmer for over 20 years. He completed his MS in Epidemiology from Columbia University and has worked at Forest Laboratories (now Allergan), Genentech, Bristol-Myers Squibb, and Biogen. He currently works at Vertex Pharmaceuticals.
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Ron Klimberg, PhD, is a professor at the Haub School of Business at Saint Joseph's University in Philadelphia, PA.
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Robert N. Rodriguez retired from SAS in 2018 after serving as a senior director in research and development. Bob received a PhD in statistics from the University of North Carolina at Chapel Hill and was a research statistician at General Motors Research Laboratories before joining SAS.