The cvDSA package groups several routines for causal inference with point treatment data based on Marginal Structural Models (MSM). The routines are entirely written in R and can be used for MSM estimation with the Inverse Probability of Treatment Weighted, G-computation and Double Robust estimators (data-adaptive estimation with cross-validation and the D/S/A algorithm, check of the Experimental Treatment Assignment (ETA) assumption, etc). A GUI interface is available for easy use of the routines along with complete documentation (library(help=cvDSA)). Version 0.5-3-1 was updated by Erin Hartman and Jasjeet Sekhon and can be installed on any R platform (i.e. Windows, Mac, *nix). Version 0.5-3-2 was updated by Susan Gruber.
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References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Haight, Thaddeus J.; Wang, Yue; van der Laan, Mark J.; Tager, Ira B.: A cross-validation deletion-substitution-addition model selection algorithm: application to marginal structural models (2010)
- van Aelst, Stefan (ed.); Welsch, Roy (ed.); Zamar, Ruben H. (ed.): Special issue on variable selection and robust procedures (2010)
- Wang, Yue; Bembom, Oliver; van der Laan, Mark J.: Data-adaptive estimation of the treatment-specific mean (2007)