Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uhakika maradufu wa makadirio katika utafiti wa elimu× | Uzito wa Alama ya Mwelekeo (PSW / IPW)× | |
|---|---|---|
| Nyanja | Uhitimisho wa Kisababishi | Uhitimisho wa Kisababishi |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 1994-2005 | 1983 (propensity score); 2003 (efficient IPW estimator) |
| Mwanzilishi≠ | Robins, Rotnitzky & Zhao (1994); Bang & Robins (2005) | Rosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting) |
| Aina≠ | Causal inference / semiparametric estimator | Causal inference / reweighting |
| Chanzo asilia≠ | Bang, H., & Robins, J. M. (2005). Doubly Robust Estimation in Missing Data and Causal Inference Models. Biometrics, 61(4), 962-973. 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 ↗ |
| Majina mbadala | DR estimator in education, AIPW in education, augmented IPW in education research, doubly robust causal estimation for educational outcomes | PSW, inverse probability weighting, IPW, propensity-based weighting |
| Zinazohusiana | 6 | 6 |
| Muhtasari≠ | Doubly robust estimation (DR) is a semiparametric causal inference approach that combines an outcome regression model with a propensity score model. In education research, it is used to estimate the causal effect of educational programs, interventions, or policies on student outcomes when treatment assignment is non-random but observed covariates can account for selection bias. The estimator is consistent if either — not necessarily both — of the two component models is correctly specified. | 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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