So sánh phương pháp

	Phân tích Kaplan-Meier Hồi cứu	Phân tích Kaplan-Meier
Lĩnh vực	Dịch tễ học	Dịch tễ học
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1958 (method); retrospective application standard in clinical research since 1970s–1980s)	1958
Người khởi xướng	Edward L. Kaplan and Paul Meier	Edward L. Kaplan and Paul Meier
Loại	Non-parametric survival analysis applied to historical data	Nonparametric survival estimator
Công trình gốc	Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481.	Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481.
Tên gọi khác	retrospective KM analysis, retrospective survival curve estimation, historical Kaplan-Meier, retrospective KM estimator	KM analysis, KM estimator, product-limit estimator, Kaplan-Meier curve
Liên quan	5	5
Tóm tắt	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.	Kaplan-Meier (KM) analysis is a nonparametric method for estimating the survival function from time-to-event data. Introduced by Kaplan and Meier in 1958, it produces the classic step-function survival curve that shows the probability of surviving beyond each observed event time, correctly accounting for censored observations — participants who left the study or had not yet experienced the event by the end of follow-up. It is one of the most widely used techniques in clinical and epidemiological research.