So sánh phương pháp

	Phân tích Kaplan-Meier thực dụng	Phân tích sống còn
Lĩnh vực	Dịch tễ học	Thống kê nghiên cứu
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1958 (estimator); pragmatic application formalized 1967 onward	1958
Người khởi xướng	Kaplan & Meier (estimator, 1958); Schwartz & Lellouch (pragmatic trial framework, 1967)	Edward L. Kaplan and Paul Meier
Loại	Non-parametric survival estimator within pragmatic study design	Method
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	pragmatic KM analysis, real-world Kaplan-Meier, pragmatic survival curve estimation, KM analysis in pragmatic trials	Kaplan-Meier analysis, Cox regression, TTE analysis
Liên quan	5	3
Tóm tắt	Pragmatic Kaplan-Meier analysis applies the non-parametric Kaplan-Meier product-limit estimator to time-to-event data collected under real-world or pragmatic conditions — diverse populations, routine clinical care, minimal exclusions, and standard-of-care comparators. Unlike explanatory trials designed to isolate a treatment effect under ideal conditions, pragmatic designs accept real-world heterogeneity, and the resulting survival curves reflect the effectiveness of an intervention as it actually performs in clinical practice.	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.