পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| Bayesian Matching Estimator× | ম্যাচিং এস্টিমেটর× | |
|---|---|---|
| ক্ষেত্র | কার্যকারণ অনুমান | কার্যকারণ অনুমান |
| পরিবার | Regression model | Regression model |
| উদ্ভবের বছর≠ | 1978–1998 | 1973 |
| প্রবর্তক≠ | Donald B. Rubin (Bayesian causal framework); extended by Heckman, Ichimura & Todd (matching estimator formalization) | Rubin (1973); large-sample theory by Abadie & Imbens (2006) |
| ধরন≠ | Bayesian causal inference / nonparametric matching | Nonparametric matching / causal inference |
| মৌলিক উৎস≠ | Rubin, D. B. (1978). Bayesian inference for causal effects: The role of randomization. The Annals of Statistics, 6(1), 34-58. DOI ↗ | Abadie, A., & Imbens, G. W. (2006). Large Sample Properties of Matching Estimators for Average Treatment Effects. Econometrica, 74(1), 235-267. DOI ↗ |
| অপর নাম | Bayesian matching, Bayesian nonparametric matching, Bayes-ATE matching, posterior matching estimator | nearest-neighbor matching, NNM, matching on covariates, covariate matching |
| সম্পর্কিত | 6 | 6 |
| সারসংক্ষেপ≠ | The Bayesian Matching Estimator estimates average treatment effects in observational studies by combining classical nearest-neighbour or kernel matching with a Bayesian posterior over the treatment effect. It inherits matching's covariate-balancing logic while propagating uncertainty through a full posterior distribution rather than relying on asymptotic standard errors, yielding credible intervals that reflect both sampling variability and prior knowledge. | The matching estimator identifies the causal effect of a treatment by pairing each treated unit with one or more untreated units that have similar observed characteristics. Formalised by Rubin (1973) and given rigorous large-sample theory by Abadie and Imbens (2006), it constructs a credible control group from observational data without requiring a parametric model for the outcome. |
| ScholarGateডেটাসেট ↗ |
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