Episode 13 | Survival Analysis: Making Sense of Time-to-Event Data

In this episode, we introduce the core ideas behind analyzing time-to-event data—situations where the outcome isn’t just “what happened,” but when it happened. A key challenge is that some participants haven’t experienced the event yet by the end of follow-up (or they drop out), so the data are only partially observed.We build the intuition for describing how risk changes over time, then walk through three practical tools: how to estimate a survival curve from one group, how to compare two groups fairly over the whole follow-up, and how to study the role of multiple predictors while keeping the time dimension front and center.