logistic regression model is often a concern, which is sometimes determined from variable selection methods. We explore how … forward, backward, and stepwise confounding variable selection estimate the ATE compared to spike-and-slab Bayesian variable … package is also described to implement variable selection on the confounding variables only and provide estimates of the ATE …

logistic regression model is often a concern, which is sometimes determined from variable selection methods. We explore how … forward, backward, and stepwise confounding variable selection estimate the ATE compared to spike-and-slab Bayesian variable … package is also described to implement variable selection on the confounding variables only and provide estimates of the ATE …

. First, variable selection is crucial in regression modeling, as it helps to identify an appropriate model with respect to … simultaneous handling of variable selection and estimation in combination with handling of missing values in covariate data. The … net, and is shown to perform well in terms of estimation performance and variable selection accuracy. The simulation …