Survival Analysis

Use this overview to decide when survival analysis is the right method family, choose between Kaplan-Meier and Cox approaches, and understand what belongs in a different methods category.

Use this section when your question is about time to an event and you need to account for censoring while comparing groups or estimating predictor effects.

This section is for time-to-event analysis with survival curves or hazard models, not for simple group-difference testing or general repeated-measures modeling. If your main question is whether groups differ on a measured outcome or how repeated observations change without an event-time endpoint, start with Group Comparison or Regression and Modeling instead.

Survival methods are useful when not every subject experiences the event during follow-up and you need estimates such as survival probabilities, median time to event, log-rank comparisons, or hazard ratios. Licklider helps you choose the leaf page that matches whether you need descriptive survival curves or covariate-adjusted hazard modeling.

Child pages

Start here

  1. Start with Kaplan-Meier Analysis when you need to describe survival curves, estimate time-to-event distributions, or compare groups with a log-rank style analysis.
  2. Start with Cox Proportional Hazards Regression when you need to estimate hazard ratios, adjust for covariates, or model how predictors relate to event timing.
  • Use related links below when your survival question also needs setup, checks, figures, or reporting guidance.