Survival Analysis Visualizer
Overview
The Survival Analysis Visualizer helps you create and analyze time-to-event data using Kaplan-Meier survival curves. Survival analysis is crucial in medical research, reliability engineering, and any field where you need to analyze the time until an event occurs while accounting for censored observations (subjects who haven’t experienced the event yet). This interactive tool generates survival curves, compares groups, calculates median survival times, and displays hazard ratios.
Tips
- Survival analysis handles censored data (subjects still alive/functioning at study end)
- Kaplan-Meier curves show probability of survival over time with step-wise decreases at events
- The curve drops at each event time, with drop size = 1/(number at risk)
- Censored observations (marked with +) contribute to risk set but don’t cause drops
- Median survival time: time point where survival probability = 0.5
- Log-rank test compares survival curves between groups (p < 0.05 = significant difference)
- Hazard ratio: relative rate of events between groups (HR > 1 means increased hazard)
- Number at risk table shows how many subjects remain under observation at each time
- Wide confidence intervals indicate uncertainty (small sample size or few events)
- Censoring should be independent of survival (non-informative censoring assumption)