Targeted ANCOVA Estimator in RCTs

Abstract

In many randomized experiments the primary goal is to estimate the average treatment effect, defined as the difference in expected responses between subjects assigned to a treatment group and subjects assigned to a control group. Linear regression is often recommended for use in RCTs as an attempt to increase precision when estimating an average treatment effect on a (nonbinary) outcome by exploiting baseline covariates. The coefficient in front of the treatment variable is then reported as the estimate of the average treatment effect, assuming that no interactions between treatment and covariates were included in the linear regression model.