In this article, we review four software packages for implementing propensity score analysis in R: "Matching, MatchIt, PSAgraphics," and "twang." After briefly discussing essential elements for propensity score analysis, we apply each package to a data set from the Early Childhood Longitudinal Study in order to estimate the…

Machine learning (ML) methods for causal inference have gained popularity due to their flexibility to predict the outcome model and the propensity score. In this article, we provide a within-group approach for ML-based causal inference methods in order to robustly estimate average treatment effects in multilevel studies when there is cluster-level…

A wide literature uses date of birth as an instrument to study the causal effects of educational attainment. This paper shows how parents delaying their children's initial enrollment in kindergarten, a practice known as redshirting, can make estimates obtained through this identification framework all but impossible to interpret. A latent index…