Statistical Research (United States)
ORCID: 0000-0002-0646-5242Publishes on Spatial and Panel Data Analysis, Statistical Methods and Inference, Statistical Methods and Bayesian Inference. 146 papers and 35.8k citations.
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About the Author Series Editor's Introduction 1. Introduction 2. Linear Fixed Effects Models: Basics 3. Fixed Effects Logistic Models 4. Fixed Effects Models for Count Data 5. Fixed Effects Models for Events History Data 6. Structural Equation Models With Fixed Effects Appendix 1 Appendix 2 References Author Index Subject Index
The history of an individual or group can always be characterized as a sequence of events. People finish school, enter the labor force, marry, give birth, get promoted, change employers, retire, and ultimately die. Formal organizations merge, adopt innovations, and go bankrupt. Nations experience wars, revolutions, and peaceful changes of government. It is surely the business of sociology to explain and predict the occurrence of such events. Why is it, for example, that some individuals try marijuana while others do not? Why do some people marry early while others marry late? Do educational
From the Publisher: 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. 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. Author Biography: 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.