Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Tathmini ya Athari ya Kinyume cha Ukweli kwa Kutumia Mbinu ya Bayesian× | Tathmini ya Athari ya Kinyume (CIE)× | |
|---|---|---|
| Nyanja | Uhitimisho wa Kisababishi | Uhitimisho wa Kisababishi |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 2015 (canonical implementation); Rubin potential outcomes: 1974-2005 | 1970s–2000s |
| Mwanzilishi≠ | Brodersen, Gallusser, Koehler, Remy & Scott; Rubin potential outcomes framework | Heckman, Imbens, Rubin, and the program evaluation literature |
| Aina≠ | Bayesian causal inference / counterfactual estimation | Causal inference / program evaluation |
| Chanzo asilia≠ | 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 ↗ |
| Majina mbadala | Bayesian CIE, Bayesian causal impact, Bayesian structural time-series causal inference, BSTS counterfactual evaluation | CIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluation |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | 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. |
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