CovSelHigh: Model-Free Covariate Selection in High Dimensions

Model-free selection of covariates in high dimensions under unconfoundedness for situations where the parameter of interest is an average causal effect. This package is based on model-free backward elimination algorithms proposed in de Luna, Waernbaum and Richardson (2011) <DOI:10.1093/biomet/asr041> and VanderWeele and Shpitser (2011) <DOI:10.1111/j.1541-0420.2011.01619.x>. Confounder selection can be performed via either Markov/Bayesian networks, random forests or LASSO.

Install the latest version of this package by entering the following in R:
install.packages("CovSelHigh")
AuthorJenny Häggström
Date of publication2016-04-26 08:44:06
MaintainerJenny Häggström <jenny.haggstrom@umu.se>
LicenseGPL-3
Version1.0.0

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