We consider the challenges and implications of controlling for school contextual bias when modeling teacher preparation program effects. Because teachers are not randomly distributed across schools, failing to account for contextual factors in achievement models could bias preparation program...

Abstract: In this article, we carefully examine two important implementation issues when estimating propensity scores using generalized boosted models (GBM), a promising machine learning technique. First, we examine which of the following methods for tuning GBM lead to better covariate balance...

Young adults who had previously participated in a longitudinal survey of youth were sent a questionnaire. They were randomly assigned to receive a $20 prepayment, a $20 postpayment, or a $25 postpayment for participation in the latest survey. Those in the large incentive condition were 7...

In this study we reconsider the relationship between heavy and persistent marijuana use and high school dropout status using a unique prospective panel study of over 4500 7th grade students from South Dakota who are followed up through high school. Propensity score weighting is used to adjust...

In this study, we reconsider the relationship between heavy and persistent marijuana use and high school dropout status. Using a unique prospective panel study of over 4500 7th grade students from South Dakota who are followed through high school, we developed propensity score weights to adjust...