Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Байєсівська оцінка впливу контрфактичних даних× | Контрфактуативна оцінка впливу (КОВ)× | |
|---|---|---|
| Галузь | Причинно-наслідковий висновок | Причинно-наслідковий висновок |
| Родина | Regression model | Regression model |
| Рік появи≠ | 2015 (canonical implementation); Rubin potential outcomes: 1974-2005 | 1970s–2000s |
| Автор методу≠ | Brodersen, Gallusser, Koehler, Remy & Scott; Rubin potential outcomes framework | Heckman, Imbens, Rubin, and the program evaluation literature |
| Тип≠ | Bayesian causal inference / counterfactual estimation | Causal inference / program evaluation |
| Основоположне джерело≠ | Brodersen, K. H., Gallusser, F., Koehler, J., Remy, N., & Scott, S. L. (2015). Inferring causal impact using Bayesian structural time-series models. Annals of Applied Statistics, 9(1), 247-274. DOI ↗ | Heckman, J. J., & Vytlacil, E. J. (2007). Econometric evaluation of social programs, Part I: Causal models, structural models and econometric policy evaluation. Handbook of Econometrics, 6B, 4779-4874. DOI ↗ |
| Інші назви | Bayesian CIE, Bayesian causal impact, Bayesian structural time-series causal inference, BSTS counterfactual evaluation | CIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluation |
| Пов'язані | 5 | 5 |
| Підсумок≠ | Bayesian Counterfactual Impact Evaluation estimates the causal effect of an intervention by constructing a Bayesian posterior distribution over the counterfactual outcome — what would have happened without treatment. The method, popularized by Brodersen et al. (2015) through the CausalImpact framework, uses Bayesian structural time-series models fitted on the pre-intervention period to predict the counterfactual trajectory, then compares observed post-intervention outcomes to that prediction. | Counterfactual Impact Evaluation is a family of causal methods that estimates the effect of an intervention by comparing what actually happened to participants with what would have happened had the intervention not taken place. Formalised in the Rubin Causal Model and extended by Heckman, Imbens and others, CIE underlies most modern program and policy evaluation practice. |
| ScholarGateНабір даних ↗ |
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