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| Lokaler durchschnittlicher Behandlungseffekt (LATE / CACE)× | Propensity Score Matching× | |
|---|---|---|
| Fachgebiet≠ | Kausale Inferenz | Forschungsstatistik |
| Familie≠ | Regression model | Process / pipeline |
| Entstehungsjahr≠ | 1994 | 1983 |
| Urheber≠ | Imbens & Angrist (1994); Angrist, Imbens & Rubin (1996) | Paul Rosenbaum and Donald Rubin |
| Typ≠ | Instrumental-variable causal estimand | Method |
| Wegweisende Quelle≠ | Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475. 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 ↗ |
| Aliasnamen≠ | LATE, CACE, complier average causal effect, Yerel Ortalama Tedavi Etkisi (LATE / CACE) | PSM, propensity score weighting, covariate balance |
| Verwandt≠ | 5 | 3 |
| Zusammenfassung≠ | The Local Average Treatment Effect is an instrumental-variable estimand, introduced by Imbens and Angrist (1994) and formalised with Rubin (1996), that recovers the average treatment effect for the subpopulation of compliers — units whose treatment status is actually moved by the instrument. It is closely tied to compliance analysis. | Propensity score matching (PSM) is a method for reducing confounding bias in observational studies by balancing baseline characteristics between treatment groups, simulating randomization. Developed by Rosenbaum and Rubin (1983), it estimates the probability of receiving treatment given observed covariates, then matches or weights treated and control individuals with similar treatment probabilities. Widely used in medicine, epidemiology, and policy evaluation when randomized trials are infeasible or unethical, enabling estimation of treatment effects while controlling for selection bias. |
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