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Student RAs Get Hands-on Experience with Data Analysis in Program and Policy Evaluation

One of the best ways for students to polish their research skills is by assisting a faculty member. In summer 2017, three W&M undergrads worked as research assistants to different faculty, all sponsored by the Schroeder Center for Health Policy. Each student got hands-on experience working with the types of data needed to evaluate programs and public policies. 

For Meredith Passero, this meant digesting a large volume of survey data on SHIP, or the School Health Initiative Program. Meredith (Government/Economics, '18) worked with the Schroeder Center’s annual survey of elementary school teachers in the Williamsburg-James City County Public Schools.  Each year’s survey asks hundreds of local teachers about their experiences and observations related to student physical activity and nutrition. The analysis of the survey data helps to guide programming decisions by the School Health Initiative Program (SHIP), such as how to direct scarce teacher supports to the grades and schools that need help the most. Meredith gained experience conducting statistical analysis with Stata software as she analyzed reams of survey data. She also learned how to make the statistical output accessible to a non-academic audience, and summarized her work in writing and in Powerpoint slide presentations for staff from SHIP and the Williamsburg Health Foundation

Similarly, Jake Leonard (Psychology, '18) helped collect data that will be used for research and program evaluation. Jake assisted Psychology Professor Danielle Dallaire as part of the evaluation of a program that supports pregnant incarcerated women at a local jail facility. Beyond assisting with data collection and entry for the project, Jake also gathered and provided resources and materials to the women on how to prepare for a healthy pregnancy, and helped update program instructional materials.

Finally, Atticus Bolyard (Mathematics, '19) assisted Economics Professor Peter Savelyev. He learned state-of-the-art data analysis techniques as part of a project that seeks to establish the causal effect of education on health.  Using data on a large sample of individuals who were part of the Minnesota Twins Registry, Atticus learned how to use sophisticated econometric techniques to separate correlation from causality. These techniques help determine whether more educated people live longer because they have some other trait correlated with both better health and more education, or because more education directly improves their longevity. Distinguishing between the two explanations is crucial for policymakers who need to know the benefits of public programs like government-funded schooling, but is a complex task for social science researchers, who seldom can conduct randomized controlled trials. 

On behalf of all the faculty mentors, thanks to Meredith, Jake, and Atticus for jobs well-done!