Võrdle meetodeid
Vaata valitud meetodeid kõrvuti; erinevad read on esile tõstetud.
| Inverse Probability Weighting in Education Research× | Instrumentaalmuutujate (IV) meetod kausaalse järelduse tegemiseks× | |
|---|---|---|
| Valdkond≠ | Põhjuslik järeldamine | Terviseökonoomika |
| Perekond≠ | Regression model | Process / pipeline |
| Tekkeaasta≠ | 1983–2003 | 1990s (modern applications) |
| Looja≠ | Rosenbaum & Rubin (propensity score, 1983); Hirano, Imbens & Ridder (efficient IPW, 2003) | Angrist & Pischke (applied econometrics); rooted in econometric theory |
| Tüüp≠ | Causal weighting estimator | Method |
| Algallikas≠ | Hirano, K., Imbens, G. W., & Ridder, G. (2003). Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score. Econometrica, 71(4), 1161-1189. DOI ↗ | Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press. link ↗ |
| Rööpnimetused | IPW in education, propensity-weighted analysis, IPTW education, inverse probability treatment weighting | IV, two-stage least squares, TSLS, causal estimation |
| Seotud≠ | 6 | 3 |
| Kokkuvõte≠ | Inverse Probability Weighting (IPW) is a causal inference technique that reweights observational education data to mimic a randomised experiment. Each student or school is assigned a weight equal to the inverse of the probability they received the treatment — thereby creating a pseudo-population in which programme participation is independent of measured background characteristics. The method is widely used in education research to evaluate school programmes, interventions, and policies from administrative or survey data. | Instrumental variables (IV) is an econometric method to estimate causal effects when treatment or exposure is not randomly assigned and confounding is severe or unmeasured. IV relies on a third variable (instrument) that influences treatment but does not directly affect the outcome, allowing researchers to isolate the causal effect from the noise of confounding. Developed extensively in econometrics (Angrist & Pischke, 1990s–2000s), IV methods are increasingly used in health economics and health services research to leverage natural experiments and policy changes. |
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