قارن الطرق

	مطابقة درجات الميل	تحليل الانحدار المتعدد
المجال	إحصاء البحث	إحصاء البحث
العائلة	Process / pipeline	Process / pipeline
سنة النشأة	1983	1801
صاحب الطريقة	Paul Rosenbaum and Donald Rubin	Carl Friedrich Gauss
النوع	Method	Method
المصدر التأسيسي	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.
الأسماء البديلة	PSM, propensity score weighting, covariate balance	MLR, multivariate regression, linear regression
ذات صلة	3	4
الملخص	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.