Linganisha mbinu

	Uchambuzi Retrospective Kaplan-Meier	Mfumo wa Cox Proportional Hazards
Nyanja	Epidemiolojia	Epidemiolojia
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	1958 (method); retrospective application standard in clinical research since 1970s–1980s)	1972
Mwanzilishi	Edward L. Kaplan and Paul Meier	Sir David Roxbee Cox
Aina	Non-parametric survival analysis applied to historical data	Semi-parametric regression model
Chanzo asilia	Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481.	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.
Majina mbadala	retrospective KM analysis, retrospective survival curve estimation, historical Kaplan-Meier, retrospective KM estimator	Cox regression, Cox PH model, proportional hazards model, CPH
Zinazohusiana	5	5
Muhtasari	Retrospective Kaplan-Meier analysis applies the Kaplan-Meier product-limit estimator to time-to-event data drawn from existing records — medical charts, registries, or administrative databases — rather than from a prospectively followed cohort. The method estimates the probability of surviving (or remaining event-free) beyond any given time point while accounting for participants whose follow-up ended before the event occurred (censored observations). It is among the most commonly reported analyses in clinical oncology, cardiology, and surgery.	The Cox proportional hazards model is a semi-parametric regression method that estimates the effect of one or more covariates on the hazard — the instantaneous rate of an event such as death, relapse, or failure — while making no assumption about the shape of the baseline hazard function. Introduced by David Cox in 1972, it is the dominant tool for multivariable survival analysis in clinical and epidemiological research.