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. As part of the NSF-funded TEAMS project, RMC Research presented a webinar on matching that explained the logic behind matching, as well as steps for incorporating matching into the analysis of program outcomes (selecting covariates, matching strategies, and assessing balance). The webinar also demonstrated how to implement matching with a free extension for SPSS. Take a look at the archived webinar for more information.