cov.sel.high.sim.res: Summarize Simulation Results for CovSelHigh

In CovSelHigh: Model-Free Covariate Selection in High Dimensions

Description

Function used to summarize results from cov.sel.high when simulated data is used.

Usage

cov.sel.high.sim.res(object)
	

Arguments

object

A list returned from cov.sel.high.

Value

cov.sel.high.sim.res returns a list with the following content:

resmat	A matrix with the following columns (columns related to average causal effect estimation are only present when betahat=TRUE): XTuc Quc XYuc Zuc XTYuc SinXT SinQ SinXY SinZ SinXTY XTeqS QeqS XYeqS ZeqS XTYeqS cards betahatest_psm betahatse_psm betahat_cicov_psm ciL_psm ciU_psm betahatest_tmle betahatse_tmle betahat_cicov_tmle ciL_tmle ciU_tmle ciwidth_psm ciwidth_tmle
summary_resmat	A list with the following columns (columns related to average causal effect estimation are only present when betahat=TRUE): Subset_selection Median_cardinality Betahat_bias_psm Betahat_sd_psm Betahat_mse_psm Betahat_CI_coverage_psm Betahat_CI_width_psm Betahat_mean_lower_CI_psm Betahat_mean_upper_CI_psm Betahat_bias_psm Betahat_sd_psm Betahat_mse_psm Betahat_CI_coverage_psm Betahat_CI_width_psm Betahat_mean_lower_CI_psm Betahat_mean_upper_CI_psm
xtable1	LaTeX table summarizing the results.
xtable2	LaTeX table summarizing the results.

Author(s)

Jenny Häggström, <[e-mail]>

References

Häggström, J. (2017). Data-Driven Confounder Selection via Markov and Bayesian Networks. ArXiv e-prints.

CovSelHigh documentation built on May 2, 2019, 3:25 a.m.