Educational researchers are often interested in studying longitudinal processes such as college completion, student dropout, or teacher promotion. Survival analysis is a method of statistical modeling that allows researchers to analyze longitudinal data where the outcome is the time to an event of interest (e.g., time to graduation, time to dropout, and time to promotion). Two distinguishing features of survival analysis that separate it from traditional logistic regression analysis are the ability to naturally incorporate time into the model and the ability to handle incomplete data (i.e., censored data). Survival models can accommodate time measured continuously (continuous-time survival analysis) or time measured discretely (discrete-time survival analysis); however, in educational research, time is typically measured discretely (i.e., per semester, per academic year). For that reason, discrete-time ...