SELECT * FROM sessions where years='2017' and sequence=125
December 4-8, 2017 at Atlantic City, New Jersey
The 73rd Deming Conference on Applied Statistics
Sponsored by Metropolitan Section, ASQ and Biopharmaceutical Section, ASA
   
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Meta-Analysis and Network Meta-Analysis in Clinical Trials

Speaker(s): Dr. Joseph C. Cappelleri, Pfizer Inc
Prof. Ding-Geng (Din) Chen, University of North Carolina at Chapel Hill
Moderator: Walter R. Young
 

Dr. Joseph C. Cappelleri earned his M.S. in statistics from the City University of New York, Ph.D. in psychometrics from Cornell University, and M.P.H. in epidemiology from Harvard University. In June 1996, he joined Pfizer Inc as a statistical scientist collaborating with Outcomes Research and is a senior director of biostatistics at Pfizer. He has also served on the adjunct faculties of Brown University, Tufts Medical Center, and the University of Connecticut. Dr. Cappelleri has delivered numerous conference presentations and has published extensively (approximately 400 publications) on clinical and methodological topics, including regression-discontinuity designs, health measurement scales, and meta-analysis. He was a member of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Task Force on Indirect Treatment Comparisons Good Research Practices. Dr. Cappelleri is an associate editor for the journal Research Synthesis Methods. Dr. Cappelleri is a Fellow of the American Statistical Association.



Dr. Din Chen is the Wallace Kuralt Distinguished Professor at the University of North Carolina-Chapel Hill. Dr. Chen is a fellow of American Statistical Association and a senior expert consultant for biopharmaceuticals and government agencies with extensive expertise in clinical trial biostatistics. Dr. Chen has more than 160 referred professional publications and co-authored/co-edited twelve books on clinical trials, interval-censored survival data analysis, meta-analysis, public health statistics, statistical causal inferences, statistical methods in big-data sciences and Monte-Carlo simulation-based statistical modeling.


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