Survival Analysis
Survival analysis is applied when the data set includes subjects that are tracked until an event happens (failure) or we lose them from the sample. We are interested in how long they stay in the sample (survival). We are also interested in their risk of failure (hazard rates). Examples include loan performance and default, firm survival and exit, and time to retirement.
Handouts, Programs, and Data
Survival Analysis Stata Program and Output
Survival Analysis R Program and Output
Survival Analysis SAS Program and Output
Survival analysis: topics covered
Survival analysis set up and features
Extensions of basic survival analysis
Survival, hazard, and cumulative hazard functions
Nonparametric analysis (Kaplan-Meier survival function)
Parametric models (Exponential, Weibull, Gompertz, and Log-logistic)
Semi-parametric models (Cox proportional hazard model)