পদ্ধতির তুলনা করুন

	রোবাস্ট প্রোপেনসিটি স্কোর ম্যাচিং	প্রোপেনসিটি স্কোর ওয়েটিং (PSW / IPW)
ক্ষেত্র	কার্যকারণ অনুমান	কার্যকারণ অনুমান
পরিবার	Regression model	Regression model
উদ্ভবের বছর	2016 (robust variance correction); 1983 (PSM foundations)	1983 (propensity score); 2003 (efficient IPW estimator)
প্রবর্তক	Abadie & Imbens (2016) for matching-on-estimated-propensity-score with corrected variance; Rosenbaum & Rubin (1983) for PSM foundations	Rosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting)
ধরন	Quasi-experimental matching estimator with robust inference	Causal inference / reweighting
মৌলিক উৎস	Abadie, A., & Imbens, G. W. (2016). Matching on the Estimated Propensity Score. Econometrica, 84(2), 781-807.	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.
অপর নাম	robust PSM, PSM with robust variance, bias-corrected PSM, matching with robust inference	PSW, inverse probability weighting, IPW, propensity-based weighting
সম্পর্কিত	6	6
সারসংক্ষেপ	Robust Propensity Score Matching (robust PSM) is a quasi-experimental causal inference method that pairs treated and control units on their estimated probability of receiving treatment (the propensity score), then estimates the average treatment effect using variance estimators that account for the uncertainty introduced by estimating the propensity score itself. The correction, developed by Abadie and Imbens (2016), prevents misleading inference that standard bootstrap or analytic formulas produce when applied naively after matching.	Propensity score weighting is a causal-inference method that reweights observations so that the covariate distributions of treated and untreated units look exchangeable, enabling unbiased estimation of average treatment effects from observational data. Each unit receives a weight that is the inverse of its probability of receiving the treatment it actually received — a strategy formalised by Rosenbaum and Rubin (1983) and given its efficient semiparametric form by Hirano, Imbens and Ridder (2003).