قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| المطابقة الدقيقة المُقَسَّمة مكانيًا (Spatial CEM)× | مطابقة درجة الميل المكانية× | |
|---|---|---|
| المجال | الاستدلال السببي | الاستدلال السببي |
| العائلة | Regression model | Regression model |
| سنة النشأة≠ | 2012 (CEM foundation); spatial extension in applied literature 2015-present | 2000s |
| صاحب الطريقة≠ | Iacus, King & Porro (CEM foundation, 2012); extended to spatial contexts by applied spatial econometricians | Extension of Rosenbaum & Rubin (1983) PSM to spatial settings; spatial adaptation developed in applied econometrics and epidemiology literature from the 2000s onward |
| النوع≠ | Quasi-experimental matching estimator with spatial covariates | Quasi-experimental matching estimator |
| المصدر التأسيسي≠ | Iacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24. 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 ↗ |
| الأسماء البديلة | Spatial CEM, Geographic CEM, Spatial exact matching, CEM with spatial covariates | Spatial PSM, Geospatial PSM, Spatially-adjusted propensity score matching, Geographic propensity score matching |
| ذات صلة | 6 | 6 |
| الملخص≠ | Spatial Coarsened Exact Matching applies the Coarsened Exact Matching framework to study designs involving geographic units — neighbourhoods, census tracts, municipalities, or grid cells. Covariates are coarsened into discrete bins and units are matched exactly on those bins, with spatial attributes (location, adjacency, geographic characteristics) incorporated as matching dimensions to control for spatial confounding. | Spatial Propensity Score Matching (Spatial PSM) extends the classic propensity score matching framework to settings where units are embedded in geographic space and treatment assignment or outcomes may be spatially correlated. By incorporating spatial covariates and adjacency structure into the propensity model and matching procedure, it produces causal estimates that account for geographic confounding and spillover effects. |
| ScholarGateمجموعة البيانات ↗ |
|
|