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Event History Analysis
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Event History Analysis
Regression for Longitudinal Event Data



88 pages | SAGE Publications, Inc
Drawing on recent 'event history' analytical methods from biostatistics, engineering, and sociology, this clear and comprehensive monograph explains how longitudinal data can be used to study the causes of deaths, crimes, wars, and many other human events. Allison shows why ordinary multiple regression is not suited to analyze event history data, and demonstrates how innovative regression-like methods can overcome this problem. He then discusses the particular new methods that social scientists should find useful.
 
Introduction
 
A Discrete-Time Method
 
Parametric Methods for Continuous-Time Data
 
Proportional Hazards and Partial Likelihood
 
Multiple Kinds of Events
 
Repeated Events
 
Change of States
 
Conclusion

Paul D. Allison

Paul D. Allison, Ph.D., is Professor of Sociology at the University of Pennsylvania where he teaches graduate courses in methods and statistics. He is also the founder and president of Statistical Horizons LLC which offers short courses on a wide variety of statistical topics.After completing his doctorate in sociology at the University of Wisconsin, he did postdoctoral study in statistics at the University of Chicago and the University of Pennsylvania. He has published eight books and more than 60 articles on topics that include linear regression, log-linear analysis, logistic regression, structural equation models, inequality measures,... More About Author

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