Social and Behavioral Sciences Commons^™

Evaluating The Performance Of Propensity Scores To Address Selection Bias In A Multilevel Context: A Monte Carlo Simulation Study And Application Using A National Dataset, Jeremy Andrew Lingle

Educational Policy Studies Dissertations

When researchers are unable to randomly assign students to treatment conditions, selection bias is introduced into the estimates of treatment effects. Random assignment to treatment conditions, which has historically been the scientific benchmark for causal inference, is often impossible or unethical to implement in educational systems. For example, researchers cannot deny services to those who stand to gain from participation in an academic program. Additionally, students select into a particular treatment group through processes that are impossible to control, such as those that result in a child dropping-out of high school or attending a resource-starved school. Propensity score methods provide …