So sánh phương pháp

	Phân tích sống còn ghép cặp	Cox proportional hazards
Lĩnh vực	Dịch tễ học	Dịch tễ học
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1983 (propensity-score matching); applied to survival outcomes throughout 1990s–2000s	1972
Người khởi xướng	Building on Kaplan & Meier (1958) and Cox (1972); matching framework formalised in observational study design literature (Rosenbaum & Rubin, 1983)	Sir David Roxbee Cox
Loại	Observational study analytic method	Semi-parametric regression model
Công trình gốc	Austin, P. C. (2014). Graphical assessments of the balance of propensity score matched samples: A SAS macro. Journal of Statistical Software, 58(7), 1-29. Also see Austin, P. C. (2017). A tutorial on multilevel survival analysis: Methods, models and applications. International Statistical Review, 85(2), 185-203.	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.
Tên gọi khác	matched time-to-event analysis, propensity-matched survival analysis, matched Kaplan-Meier analysis, paired survival analysis	Cox regression, Cox PH model, proportional hazards model, CPH
Liên quan	4	5
Tóm tắt	Matched survival analysis combines a matching design — typically propensity score matching or exact matching on key covariates — with time-to-event methods such as Kaplan-Meier estimation and the Cox proportional hazards model. By pairing treated and control subjects who are similar on observed confounders before estimating survival curves or hazard ratios, the approach reduces confounding bias in non-randomised studies and produces more credible comparisons of event-free survival between exposure groups.	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.