Krahasoni metodat

	Estensioni të shumëllojtë të robustë të dyfishtë	Estimatimi i dyfishtë i qëndrueshëm (AIPW)
Fusha	Inferenca kauzale	Inferenca kauzale
Familja	Regression model	Regression model
Viti i origjinës	1994-2021	2005
Krijuesi	Robins, Rotnitzky, and Zhao; extended by Bang & Robins (2005) and Callaway & Sant'Anna (2021)	Robins & Rotnitzky; Bang & Robins
Lloji	Semiparametric causal estimator	Semiparametric causal estimator
Burimi themelues	Bang, H., & Robins, J. M. (2005). Doubly robust estimation in missing data and causal inference models. Biometrics, 61(4), 962-973.	Robins, J. M. & Rotnitzky, A. (1995). Semiparametric Efficiency in Multivariate Regression Models with Missing Data. Journal of the American Statistical Association, 90(429), 122-129.
Emërtime të tjera	longitudinal DR estimation, multi-period DR, multi-wave doubly robust, sequential doubly robust estimation	AIPW, augmented inverse probability weighting, doubly robust estimator, Çift Gürbüz Kestirici (Augmented IPW / AIPW)
Të lidhura	6	5
Përmbledhja	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.	Doubly Robust Estimation, also called Augmented Inverse Probability Weighting (AIPW), is a semiparametric method for estimating causal treatment effects that combines an outcome regression model with a propensity (treatment) model. Developed in the work of Robins & Rotnitzky (1995) and Bang & Robins (2005), it stays consistent as long as at least one of the two models is correctly specified.