विधियों की तुलना करें

	उपचार भारण की व्युत्क्रम प्रायिकता (IPW / IPTW)	कारण मध्यस्थता विश्लेषण (प्राकृतिक प्रत्यक्ष और अप्रत्यक्ष प्रभाव)
क्षेत्र	कारणात्मक अनुमान	कारणात्मक अनुमान
परिवार	Regression model	Regression model
उद्भव वर्ष	2000	2010
प्रवर्तक	Robins, Hernán & Brumback	Pearl (2001); general framework by Imai, Keele & Tingley (2010)
प्रकार	Causal inference weighting estimator	Counterfactual causal decomposition
मौलिक स्रोत	Robins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal Structural Models and Causal Inference in Epidemiology. Epidemiology, 11(5), 550-560.	Pearl, J. (2001). Direct and Indirect Effects. In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI), 411-420.
उपनाम	IPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting	natural direct effect, natural indirect effect, NDE / NIE decomposition, counterfactual mediation
संबंधित	5	5
सारांश	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.	Causal mediation analysis is a counterfactual framework that splits a treatment's total effect into a Natural Direct Effect (NDE) and a Natural Indirect Effect (NIE) that runs through a mediator. The modern general approach was formalised by Pearl (2001) and Imai, Keele and Tingley (2010), giving the decomposition a precise causal interpretation.