विधियों की तुलना करें

	बहु-अवधि द्वि-दृढ़ अनुमान	उपचार भारण की व्युत्क्रम प्रायिकता (IPW / IPTW)
क्षेत्र	कारणात्मक अनुमान	कारणात्मक अनुमान
परिवार	Regression model	Regression model
उद्भव वर्ष	1994-2021	2000
प्रवर्तक	Robins, Rotnitzky, and Zhao; extended by Bang & Robins (2005) and Callaway & Sant'Anna (2021)	Robins, Hernán & Brumback
प्रकार	Semiparametric causal estimator	Causal inference weighting estimator
मौलिक स्रोत	Bang, H., & Robins, J. M. (2005). Doubly robust estimation in missing data and causal inference models. Biometrics, 61(4), 962-973.	Robins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal Structural Models and Causal Inference in Epidemiology. Epidemiology, 11(5), 550-560.
उपनाम	longitudinal DR estimation, multi-period DR, multi-wave doubly robust, sequential doubly robust estimation	IPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting
संबंधित	6	5
सारांश	Multi-period doubly robust (DR) estimation extends the classic doubly robust approach to longitudinal settings with multiple treatment periods and time points. It combines an outcome regression model and a propensity score model for each period, retaining consistency of the causal effect estimate as long as at least one of the two models is correctly specified at every time point.	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.