Social scientists are interested in events and their causes. Although event histories are ideal for studying the causes of events, they typically possess two features—censoring and time-varying explanatory variables—that create major problems for standard statistical procedures. Several innovative approaches have been developed to accommodate these two peculiarities of event history data. This volume surveys these methods, concentrating on the approaches that are most useful to the social sciences. In particular, Paul D. Allison focuses on regression methods in which the occurrence of events is dependent on one or more explanatory variables. He gives attention to the statistical models that form the basis of event history analysis, and also to practical concerns such as data management, cost, and useful computer software.
The Second Edition is part of SAGE’s Quantitative Applications in the Social Sciences (QASS) series, which continues to serve countless students, instructors, and researchers in learning the most cutting-edge quantitative techniques.
Table des matières
Introduction
Discrete-Time Methods
Parametric Methods for Continuous-Time Data
Cox Regression
Multiple Kinds of Events
Repeated Events
Conclusion
A propos de l’auteur
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, missing data, and survival analysis.Much of his early research focused on career patterns of academic scientists. At present, his principal research is on methods for analyzing longitudinal data, especially those for determining the causes and consequences of events, and on methods for handling missing data.A former Guggenheim Fellow, Allison received the 2001 Lazarsfeld Award for distinguished contributions to sociological methodology. In 2010 he was named a Fellow of the American Statistical Association. He is also a two-time winner of the American Statistical Association’s award for “Excellence in Continuing Education.”
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