পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| স্থানিক প্রবণতা স্কোর ওয়েটিং× | ভূগোলিকভাবে ভারযুক্ত রিগ্রেশন (GWR)× | |
|---|---|---|
| ক্ষেত্র≠ | কার্যকারণ অনুমান | স্থানিক বিশ্লেষণ |
| পরিবার | Regression model | Regression model |
| উদ্ভবের বছর≠ | 2000s–2010s | 2002 |
| প্রবর্তক≠ | Extended from Hirano, Imbens & Ridder (2003) IPTW with spatial adaptations by Keele, Titiunik and others in geographically structured causal designs | Fotheringham, Brunsdon & Charlton |
| ধরন≠ | Quasi-experimental / causal inference | Local spatial regression |
| মৌলিক উৎস≠ | Keele, L., & Titiunik, R. (2015). Geographic Boundaries as Regression Discontinuities. Political Analysis, 23(1), 127-155. DOI ↗ | Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168 |
| অপর নাম | spatial PSW, geographically weighted propensity score weighting, spatial IPTW, spatially adjusted inverse probability weighting | GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR) |
| সম্পর্কিত≠ | 6 | 5 |
| সারসংক্ষেপ≠ | Spatial propensity score weighting extends inverse probability of treatment weighting (IPTW) to settings where units are geographically located and treatment assignment may depend on spatial factors such as location, neighborhood characteristics, or spatial clustering. By incorporating spatial covariates into the propensity score model and adjusting standard errors for spatial autocorrelation, it produces more credible causal estimates from observational geographic data. | Geographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships. |
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