পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| ডাইনামিক এনট্রপি ব্যালান্সিং× | প্রোপেনসিটি স্কোর ওয়েটিং (PSW / IPW)× | |
|---|---|---|
| ক্ষেত্র | কার্যকারণ অনুমান | কার্যকারণ অনুমান |
| পরিবার | Regression model | Regression model |
| উদ্ভবের বছর≠ | 2012-2018 | 1983 (propensity score); 2003 (efficient IPW estimator) |
| প্রবর্তক≠ | Hainmueller (2012) for static entropy balancing; extended to dynamic settings by Blackwell and Glynn (2018) and subsequent methodologists | Rosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting) |
| ধরন≠ | Causal inference / weighting estimator | Causal inference / reweighting |
| মৌলিক উৎস≠ | Hainmueller, J. (2012). Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies. Political Analysis, 20(1), 25-46. 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 ↗ |
| অপর নাম | DEB, longitudinal entropy balancing, entropy balancing with time-varying treatment, sequential entropy balancing | PSW, inverse probability weighting, IPW, propensity-based weighting |
| সম্পর্কিত | 6 | 6 |
| সারসংক্ষেপ≠ | Dynamic Entropy Balancing extends the entropy balancing reweighting approach to settings with time-varying treatments in panel or longitudinal data. It constructs unit weights at each time period such that the covariate distributions of treated and comparison units are balanced on specified moments, adjusting sequentially for prior treatment history and time-varying confounders to estimate the causal effect of treatment sequences on outcomes. | Propensity score weighting is a causal-inference method that reweights observations so that the covariate distributions of treated and untreated units look exchangeable, enabling unbiased estimation of average treatment effects from observational data. Each unit receives a weight that is the inverse of its probability of receiving the treatment it actually received — a strategy formalised by Rosenbaum and Rubin (1983) and given its efficient semiparametric form by Hirano, Imbens and Ridder (2003). |
| ScholarGateডেটাসেট ↗ |
|
|