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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.
Package details |
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Author | Jenny Häggström |
Maintainer | Jenny Häggström <jenny.haggstrom@umu.se> |
License | GPL-3 |
Version | 1.1.1 |
Package repository | View on CRAN |
Installation |
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