পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| প্যানেল ডেটা ইনভার্স প্রোবাবিলিটি ওয়েটিং× | প্রোপেনসিটি স্কোর ওয়েটিং (PSW / IPW)× | |
|---|---|---|
| ক্ষেত্র | কার্যকারণ অনুমান | কার্যকারণ অনুমান |
| পরিবার | Regression model | Regression model |
| উদ্ভবের বছর≠ | 2000 | 1983 (propensity score); 2003 (efficient IPW estimator) |
| প্রবর্তক≠ | Robins, Hernan & Brumback | Rosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting) |
| ধরন≠ | Reweighting / causal inference | Causal inference / reweighting |
| মৌলিক উৎস≠ | Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560. 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 | panel IPW, longitudinal IPW, time-varying IPW, panel IPTW | PSW, inverse probability weighting, IPW, propensity-based weighting |
| সম্পর্কিত≠ | 5 | 6 |
| সারসংক্ষেপ≠ | Panel Data Inverse Probability Weighting (panel IPW) estimates the causal effect of a time-varying treatment by reweighting observed units to create a pseudo-population in which treatment is independent of measured confounders at each time point. It extends the cross-sectional IPW framework to longitudinal settings where treatment status and confounders both evolve across multiple periods. | 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 ↗ |
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