The Kaplan-Meier Estimator is a non-parametric statistical technique used in survival analysis to estimate the probability of a subject surviving beyond a certain time point from a specified initial time, accounting for right-censored data where the event of interest has not occurred during the observation period. This method constructs an empirical cumulative distribution function (ECDF) by calculating the product-limit estimator as successive events occur within ordered follow-up intervals, thereby adjusting survival probabilities inversely to each observed failure while remaining constant between censoring and failure points. It serves as a foundational mechanism for handling incomplete longitudinal data in fields such as biostatistics, reliability engineering, and clinical epidemiology without assuming any specific underlying distribution of the time-to-event variable.
Prerequisite chain context: requires Log-Rank Test [Simply Explained].