|Authors:||Jenny Häggström, Emma Persson, Ingeborg Waernbaum, Xavier de Luna|
|Title:||CovSel: An R Package for Covariate Selection When Estimating Average Causal Effects|
|Abstract:||We describe the R package CovSel, which reduces the dimension of the covariate vector for the purpose of estimating an average causal effect under the unconfoundedness assumption. Covariate selection algorithms developed in De Luna, Waernbaum, and Richardson (2011) are implemented using model-free backward elimination. We show how to use the package to select minimal sets of covariates. The package can be used with continuous and discrete covariates and the user can choose between marginal co-ordinate hypothesis tests and kernel-based smoothing as model-free dimension reduction techniques.|
Page views:: 1709. Submitted: 2013-10-09. Published: 2015-11-24.
CovSel: An R Package for Covariate Selection When Estimating Average Causal Effects
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.