报告题目：Analysis of Prescription Drug Utilization with Beta Regression Models
报 告 人：Guojun Gan Associate Professor University of Connecticut
报告地点：腾讯会议 ID：336 503 520
报告摘要：The healthcare sector in the U.S. is complex and is also a large sector that generates about 20% of the country's gross domestic product. Healthcare analytics has been used by researchers and practitioners to better understand the industry. In this talk, I will present our recent work about the use of Beta regression models to understand the variability of brand name drug utilization across different areas with the U.S. The models are fitted to public datasets obtained from the Medicare & Medicaid Services and the Internal Revenue Service. Integrated Nested Laplace Approximation (INLA) is used to perform the inference. Some numerical results showing the performance of Beta regression models will also be presented.
报告人简介：Guojun Gan is an Associate Professor in the Department of Mathematics at the University of Connecticut, where he has been since August 2014. Prior to that, he worked at a large life insurance company in Toronto, Canada for six years and a hedge fund in Oakville, Canada for one year. He received a BS degree from Jilin University, Changchun, China, in 2001 and MS and PhD degrees from York University, Toronto, Canada, in 2003 and 2007, respectively. He is also a Fellow of the Society of Actuaries (FSA). His research interests are in the interdisciplinary areas of actuarial science and data science. He has published several books and papers on a variety of topics, including data clustering, variable annuity, applied statistics, programming, and mathematical finance. He has received several research grants from the Society of Actuaries and has been invited to give talks at several universities and conferences around the world. According to Google Scholar, his work has been cited more than 2,900 times.