Comment on Penalized Spline of Propensity Methods for Treatment Comparison by Zhou, Elliott, and Little
It is a pleasure to discuss the recent methodological contributions provided by Zhou, Elliott, and Little for application to causal inference in longitudinal studies. In their work, Zhou et al. embed features of existing causal approaches into a multiple imputation framework, the latter of which having historically been considered for use in general missing data problems. This discussion is divided into two sections. First, I will attempt to broadly characterize how this work methodologically compares to previously developed causal inference methods. Then, I will outline a few considerations and suggestions for future research that I believe will help further elucidate the relative strengths, bounds, and limitations of this approach in its application to real world data.