So sánh phương pháp

	Ghép cặp điểm xu hướng	Phân tích Hồi quy Đa biến
Lĩnh vực	Thống kê nghiên cứu	Thống kê nghiên cứu
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1983	1801
Người khởi xướng	Paul Rosenbaum and Donald Rubin	Carl Friedrich Gauss
Loại	Method	Method
Công trình gốc	Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55.	Draper, N. R., & Smith, H. (1966). Applied Regression Analysis. John Wiley & Sons.
Tên gọi khác	PSM, propensity score weighting, covariate balance	MLR, multivariate regression, linear regression
Liên quan	3	4
Tóm tắt	Propensity score matching (PSM) is a method for reducing confounding bias in observational studies by balancing baseline characteristics between treatment groups, simulating randomization. Developed by Rosenbaum and Rubin (1983), it estimates the probability of receiving treatment given observed covariates, then matches or weights treated and control individuals with similar treatment probabilities. Widely used in medicine, epidemiology, and policy evaluation when randomized trials are infeasible or unethical, enabling estimation of treatment effects while controlling for selection bias.	Multiple regression analysis is a statistical method for modeling the relationship between a continuous dependent variable and two or more independent variables (predictors). Originating from Gauss's early 19th-century work and formalized by Draper and Smith (1966), it estimates linear equations predicting outcomes from multiple predictors while accounting for confounding relationships, making it indispensable in epidemiology, economics, psychology, and clinical research.