Megan Mathews is a senior statistical analyst at RAND. She has provided analytic input on health research projects related to pay-for-performance, quality of care, patient satisfaction, and the Medicare population. She utilizes survey methodology to design and implement sampling procedures as well as analyze complex data using techniques such as sampling weights, case-mix adjustment, non-response, and response rate analyses. She uses statistical techniques such as propensity scoring and matching, multi-level, mixed, and survival modeling methods, to draw inferences between process-outcome links and health disparities. She leads large-scale sampling and national scoring tasks and interprets quantitative results to compile findings in a meaningful way for dissemination.
Prior to her work at RAND, she was employed as a data research analyst in the workers' compensation insurance industry where she contributed through predictive analytics used for claims handling improvements as well as other network and operational program evaluations. She also worked at the Office of Immigration Statistics in the Department of Homeland Security evaluating the flow of nonimmigrant admissions. She was a graduate fellow at the National Institutes of Health working for the National Institute of Child Health and Development on methods of adjusted comparison of medians for interval type outcomes. She received her Master of Applied Statistics from Pennsylvania State University.
M.S. in applied statistics, Pennsylvania State University; B.S. in statistics, Pennsylvania State University
