This three-day workshop coverd the theory and practice of survival analysis, with an emphasis on Cox regression. Also known as event history analysis, these methods are designed for longitudinal data where the dependent variable is based on the occurrence and timing of events. Originally developed to model deaths, these regression methods are suitable for a wide variety of events in the social sciences, including births, marriages, divorces, job changes, promotions, bankruptcies, arrests, hospitalizations, etc. The methods were demonstrated with the SAS system (especially PROC PHREG) and participants got hands-on experience with the procedures. Participants had a good working knowledge of the principles and practice of multiple regression, and were familiar with basic principles of statistical inference.
- Fundamentals of Survival Analysis
- Types of Censoring
- Describing Distributions of Event Times
- Life Table Method
- Kaplan Meier Method
- Comparing Survival Curves
- Proportional Hazards Model
- Partial Likelihood Estimation
- Time Varying Explanatory Variables
- Competing Risks
- Baseline Hazard and Survivor Function
- Adequacy of Proportional Hazards Assumption
- Heterogeneity and Time Dependence
- Repeated Events
- Left Truncation
Allison, Paul D. (1984) Event History Analysis. Thousand Oaks, CA: Sage Publications. One of the "little green books," this provides a quick introduction to the various methods.
Allison, Paul D. (2004) Event history analysis. Alan E. Bryman and Melissa Hardy (eds.), Handbook of Data Analysis. Thousand Oaks, CA: Sage Publications. An even shorter introduction.
Allison, Paul D. (1995) Survival Analysis Using SAS: A Practical Guide. Cary, NC: The SAS Institute. Read this if you want to cover all the nuts and bolts.
Paul Allison is professor and chair of sociology at the University of Pennsylvania, where he teaches graduate methods and statistics. He is widely recognized as an extraordinarily effective teacher of statistical methods who can reach students with highly diverse backgrounds and expertise. Allison is the author of Missing Data (Sage 2001), Logistic Regression Using the SAS® System: Theory and Application (SAS Institute 1999), Multiple Regression: A Primer (Pine Forge 1999), Survival Analysis Using the SAS® System: A Practical Guide (SAS Institute 1995), Event History Analysis (Sage 1984), and numerous articles on regression analysis, log-linear analysis, logit analysis, latent variable models, missing data, and inequality measures. A former Guggenheim Fellow, he is also on the editorial board of Sociological Methods and Research. In 2001 he received the Paul Lazarsfeld Memorial Award for Distinguished Contributions to Sociological Methodology.