विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| नीति मूल्यांकन प्रपेंसिटी स्कोर मैचिंग× | प्रोपेंसिटी स्कोर वेटिंग (PSW / IPW)× | |
|---|---|---|
| क्षेत्र | कारणात्मक अनुमान | कारणात्मक अनुमान |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 1983; policy evaluation adaptation 1997 | 1983 (propensity score); 2003 (efficient IPW estimator) |
| प्रवर्तक≠ | Rosenbaum & Rubin (1983); Heckman, Ichimura & Todd (1997) for program/policy evaluation application | Rosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting) |
| प्रकार≠ | Quasi-experimental matching estimator | Causal inference / reweighting |
| मौलिक स्रोत | 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. DOI ↗ | 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. DOI ↗ |
| उपनाम | PSM policy evaluation, policy PSM, propensity matching for program evaluation, PSM treatment evaluation | PSW, inverse probability weighting, IPW, propensity-based weighting |
| संबंधित | 6 | 6 |
| सारांश≠ | Policy evaluation propensity score matching applies the propensity score framework — originally developed by Rosenbaum and Rubin (1983) and operationalized for program evaluation by Heckman et al. (1997) — to estimate the causal effect of a policy intervention. It constructs a credible comparison group from non-participants by matching them to participants on their estimated probability of receiving the treatment, enabling unbiased effect estimation without random assignment. | 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). |
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