Krahasoni metodat

	Pesha e Inversit të Probabilitetit të Efektit të Trajtimit Heterogjen (HTE-IPW)	Pesha e Vlerësimit të Propensitetit (PSW / IPW)
Fusha	Inferenca kauzale	Inferenca kauzale
Familja	Regression model	Regression model
Viti i origjinës	2003–2015	1983 (propensity score); 2003 (efficient IPW estimator)
Krijuesi	Hirano, Imbens & Ridder; further developed by Abrevaya, Hsu & Lieli	Rosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting)
Lloji	Causal inference / weighted regression	Causal inference / reweighting
Burimi themelues	Hirano, K., Imbens, G. W., & Ridder, G. (2003). Efficient estimation of average treatment effects using the estimated propensity score. Econometrica, 71(4), 1161-1189.	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.
Emërtime të tjera	HTE-IPW, CATE-IPW, heterogeneous IPW, conditional effect IPW	PSW, inverse probability weighting, IPW, propensity-based weighting
Të lidhura	5	6
Përmbledhja	HTE-IPW extends standard inverse probability weighting to recover how causal effects vary across subgroups or covariate values. By reweighting each observation by the inverse of its estimated treatment probability, the method creates a pseudo-population in which treatment is independent of background characteristics, and then estimates conditional average treatment effects (CATEs) as a function of those characteristics.	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).