Krahasoni metodat

	Pesha Inverse Probabilitare Hapësinore (Spatial IPW)	Pesha e Probabilitetit të Inversuar të Trajtimit (IPW / IPTW)
Fusha	Inferenca kauzale	Inferenca kauzale
Familja	Regression model	Regression model
Viti i origjinës	2010s	2000
Krijuesi	Extension of Rosenbaum & Rubin (1983) IPW to spatial settings; formal treatment by Papadogeorgou et al. (2019)	Robins, Hernán & Brumback
Lloji	Quasi-experimental / causal inference	Causal inference weighting estimator
Burimi themelues	Hirano, K., Imbens, G. W., & Ridder, G. (2003). Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score. Econometrica, 71(4), 1161-1189.	Robins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal Structural Models and Causal Inference in Epidemiology. Epidemiology, 11(5), 550-560.
Emërtime të tjera	Spatial IPW, Geographic IPW, Spatially-weighted IPW, SIPW	IPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting
Të lidhura	6	5
Përmbledhja	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.	Inverse Probability Weighting is a causal-inference method that assigns each observation a weight equal to the inverse of its probability of receiving the treatment it actually received. Introduced by Robins, Hernán and Brumback (2000) for marginal structural models, it builds a pseudo-population in which treatment is independent of measured confounders, balancing selection bias.