Process / pipelinetime-event-modeling

Survival Analysis

Survival analysis is a collection of statistical methods for modeling time from a defined starting point until an event of interest occurs (disease, recovery, death, equipment failure). Kaplan and Meier's nonparametric estimator (1958) and David Cox's proportional hazards model (1972) jointly enabled analysis of censored data—individuals whose event times are unknown because they left the study or were still event-free at follow-up. Indispensable in oncology, cardiology, infectious disease research, engineering reliability, and any field where time-to-event matters.

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Sources

  1. Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481. DOI: 10.1080/01621459.1958.10501452
  2. Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society, Series B, 34(2), 187–220. DOI: 10.1111/j.2517-6161.1972.tb00899.x

Related methods

Referenced by

ScholarGateSurvival Analysis (Time-to-Event Analysis). Retrieved 2026-06-04 from https://scholargate.app/tr/research-statistics/survival-analysis