Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Локальний середній ефект лікування (LATE / CACE)× | Зіставлення за показником схильності× | |
|---|---|---|
| Галузь≠ | Причинно-наслідковий висновок | Статистика досліджень |
| Родина≠ | Regression model | Process / pipeline |
| Рік появи≠ | 1994 | 1983 |
| Автор методу≠ | Imbens & Angrist (1994); Angrist, Imbens & Rubin (1996) | Paul Rosenbaum and Donald Rubin |
| Тип≠ | Instrumental-variable causal estimand | Method |
| Основоположне джерело≠ | 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 ↗ |
| Інші назви≠ | LATE, CACE, complier average causal effect, Yerel Ortalama Tedavi Etkisi (LATE / CACE) | PSM, propensity score weighting, covariate balance |
| Пов'язані≠ | 5 | 3 |
| Підсумок≠ | 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. |
| ScholarGateНабір даних ↗ |
|
|