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MHRI-GHUCCTS Statistical Seminar: Bayesian Analysis - Alternative to Frequentist Analysis

Date Fri, Feb 19
Time 12: 00 PM - 1: 00 PM
Location Zoom

This month's MHRI-GHUCCTS Monthly Statistical Seminar Series features Dr. Paul Kolm, Associate Director in the Department of Biostatistics and Biomedical Informatics at MedStar Health Research Institute. Dr. Kolm will discuss Bayesian analysis.

ABSTRACT: So far we have looked at statistical methods from the frequentist perspective. At this webinar, we will look at statistical methods from the Bayesian perspective. The Bayesian perspective has been around for over 300 years, but not until the advent of high-speed computing has it become useful for more complex research designs. We will compare frequentist and Bayesian perspectives, and then provide some examples of the application of Bayesian statistics.

Dr. Kolm is Associate Director, Department of Biostatistics and Biomedical Informatics at MedStar Health Research Institute. He has over 30 years of experience in consulting with principal investigators in the design and analysis of clinical trials, retrospective and observational studies, and large patient registries. He has served as Statistical Editor of JACC-Interventions, served on the Scientific and Clinical Support Committee of the American College of Cardiology National Cardiovascular Data Registry (NCDR), and the American Heart Association Epidemiology, Prevention, Outcomes, and Behavioral study section. While at Emory University, he was the lead biostatistician for the Grady Hospital General Clinical Research Center (GCRC) and a member of the GCRC Advisory Committee, which reviewed Emory and Grady research protocols for scientific merit. He is currently the lead biostatistician for several NIH and industry-funded studies. Dr. Kolm’s statistical areas of interest include cost-effectiveness analyses, multiple imputation methods for missing data, analysis of sparse outcomes, and multivariable regression models where the number of variables is greater than the number of participants.