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تطابق امتیاز تمایل (Propensity Score Matching)×تحلیل رگرسیون چندگانه×
حوزهآمار پژوهشآمار پژوهش
خانوادهProcess / pipelineProcess / pipeline
سال پیدایش19831801
پدیدآورPaul Rosenbaum and Donald RubinCarl Friedrich Gauss
نوعMethodMethod
منبع بنیادینRosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. DOI ↗Draper, N. R., & Smith, H. (1966). Applied Regression Analysis. John Wiley & Sons. link ↗
نام‌های دیگرPSM, propensity score weighting, covariate balanceMLR, multivariate regression, linear regression
مرتبط34
خلاصهPropensity 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.
ScholarGateمجموعه‌داده
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  1. v1
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  3. PUBLISHED

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ScholarGateمقایسهٔ روش‌ها: Propensity Score Matching · Multiple Regression Analysis. بازیابی‌شده در 2026-06-17 از https://scholargate.app/fa/compare