Event History Modeling A Guide for Social Scientists

Here is an accessible, up-to-date guide to event history analysis for researchers and advanced students in the social sciences. The foundational principles of event history analysis are discussed and ample examples are estimated and interpreted using standard statistical packages, such as STATA and S-Plus. Recent and critical innovations in diagnostics are discussed, including testing the proportional hazards assumption, identifying outliers, and assessing model fit. The treatment of complicated events includes coverage of unobserved heterogeneity, repeated events, and competing risks models. The authors point out common problems in the analysis of time-to-event data in the social sciences and make recommendations regarding the implementation of duration modeling methods.

Event History Modeling, first published in 2004, provides an accessible guide to event history analysis for researchers and advanced students in the social sciences. The substantive focus of many social science research problems leads directly to the consideration of duration models, and many problems would be better analyzed by using these longitudinal methods to take into account not only whether the event happened, but when. The foundational principles of event history analysis are discussed and ample examples are estimated and interpreted using standard statistical packages, such as STATA and S-Plus. Critical innovations in diagnostics are discussed, including testing the proportional hazards assumption, identifying outliers, and assessing model fit. The treatment of complicated events includes coverage of unobserved heterogeneity, repeated events, and competing risks models. The authors point out common problems in the analysis of time-to-event data in the social sciences and make recommendations regarding the implementation of duration modeling methods.

List of figures; List of tables; Preface; 1. Event history and political analysis; 2. The logic of event history analysis; 3. Parametric models for single-spell duration data; 4. The Cox Proportional Hazards model; 5. Models for discrete data; 6. Issues in model selection; 7. Inclusion of time-varying covariates; 8. Diagnostic methods for the event history model; 9. Some modeling strategies for unobserved heterogeneity; 10. Models for multiple events; 11. Political analysis and event history; Appendix: software for event history analysis; References; Index.

This 2004 book provides a guide to event history analysis for researchers and advanced students in the social sciences. The authors explain the foundational principles of event-history analysis, and analyse numerous examples. They also discuss common problems encountered with time-to-event data, along with suggestions for implementing duration modeling methods.

Janet Box-Steffensmeier is Vernal Riffe Professor of Political Science at Ohio State University. Chair of the R. H. Durr Award Committee for the best paper applying quantitative methods to a substantive issue that was presented at the 2002 Annual Meeting of the Midwest Political Science Association, 2002–3. Vice President and member of the Executive Committee of the Political Methodology Section of the American Political Science Association, 2003–5.
Bradford S. Jones is an Associate Professor of Political Science at the University of Arizona. He has served as a Section Officer for the Society for Political Methodology as well as serving as a guest editor for a special issue of Political Analysis on causal inference. His research on methodology includes work on reliability analysis, duration modeling, and models for categorical data. Professor Jones received his Ph.D. from the State University of New York at Stony Brook. Apart from methodology, Professor Jones' research interests include racial and ethnic politics, public opinion, and representation.