One weird trick for better inference in experimental designs

A long line of research debates the merits of statistical adjustment for baseline or pretreatment characteristics for random assignment designs (Fisher 1935; Freedman 2008a, 2008b; Lin 2013; Kallus 2018). A related literature explores better methods to conduct statistical adjustment for potential confounders in nonexperimental designs. This presentation presents the results of a simulation showing large potential improvements in inference for random assignment designs attainable using commands designed to adjust for potential confounders newly available in Stata 16.