Skip to main content

Welcome, the Hub connects all projects


Rigorous Alternatives to RCTs -- Quasi-Experimental Designs with Equating


Download slides with notes and Q&A

If students in treatment and comparison groups are systematically different, differences in outcomes at the end of an intervention may be due in part to those differences instead the effects of the intervention itself. In some cases, the bias from these confounding factors can be reduced by first matching treatment and comparison students on key pre-intervention characteristics. After a brief practitioner’s overview of the theoretical background for matching (the need for matching and how matching can reduce bias), this webinar will present the steps for incorporating matching into the analysis of your program outcomes, including selecting covariates, matching strategies, and assessing balance. The process will be illustrated using a free add-on to SPSS.