Accurately forecasting course enrollment rates in higher education is of great concern in order to minimize unnecessary administrative costs as well as burden to both students and faculty. This research aimed to first recreate course enrollment predictions based on a conditional probability analysis using student data from San Diego State…

Propensity score methods account for selection bias in observational studies. However, the consistency of the propensity score estimators strongly depends on a correct specification of the propensity score model. Logistic regression and, with increasing popularity, machine learning tools are used to estimate propensity scores. We introduce a…