পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| Spatial Inverse Probability Weighting× | স্থানিক রিগ্রেশন (স্থানিক ল্যাগ এবং স্থানিক ত্রুটি মডেল)× | |
|---|---|---|
| ক্ষেত্র≠ | কার্যকারণ অনুমান | অর্থমিতি |
| পরিবার | Regression model | Regression model |
| উদ্ভবের বছর≠ | 2010s | 1988 |
| প্রবর্তক≠ | Extension of Rosenbaum & Rubin (1983) IPW to spatial settings; formal treatment by Papadogeorgou et al. (2019) | Luc Anselin |
| ধরন≠ | Quasi-experimental / causal inference | Spatial regression (cross-sectional) |
| মৌলিক উৎস≠ | Hirano, K., Imbens, G. W., & Ridder, G. (2003). Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score. Econometrica, 71(4), 1161-1189. DOI ↗ | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers. DOI ↗ |
| অপর নাম≠ | Spatial IPW, Geographic IPW, Spatially-weighted IPW, SIPW | spatial econometrics, spatial lag model, spatial error model, SAR / SEM |
| সম্পর্কিত≠ | 6 | 5 |
| সারসংক্ষেপ≠ | Spatial Inverse Probability Weighting extends the classical IPW estimator to settings where units are geo-referenced and spatial location is a confounding dimension. By incorporating geographic coordinates or spatial proximity into the propensity score model, it reweights the observed sample so that treatment and control groups are balanced not only on measured covariates but also on spatial structure, enabling credible causal inference from spatially indexed observational data. | Spatial regression is a family of regression models that build geographic neighbourhood relationships directly into the model, introduced by Luc Anselin in his 1988 treatment of spatial econometrics. It splits into a spatial lag model, where spatial dependence sits in the dependent variable, and a spatial error model, where the dependence sits in the error term. |
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