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His research interests are primarily in the areas of statistical models for rating competitors in games and sports, and in statistical methods applied to problems in health services research. Dr. Glickman's long-standing interest in methods for rating competitors in games and sports arose from his involvement in playing tournament chess, where he attained the title of U.S. national master in 1988. Dr. Glickman is known for having invented the Glicko and Glicko-2 rating systems, both of which have been adopted by many gaming organizations internationally. These models stemmed from his Harvard docotoral dissertation on foundational probability models for rating competitors with time-varying abilities, a topic on which he has since published a number of scholarly papers, including methods for pairing competitors in tournaments.
He has co-founded and co-organizes the New England Symposium on Statistics in Sports, a bi-annual conference on the research and practice of applying statistical methods in sports.
Much of Dr. Glickman's publications have been in the realm of health services research. In the mid-1990s, Dr. Glickman's work critiquing the resource-based relative value scale algorithm for the Medicare Fee Schedule had led to his consultation to government agencies in Ontario and Alberta to help develop a statistical approach for medical fee schedule construction. He has received NIH and VA grants to study the genetic predisposition to disease onset for various cardiovascular diseases. More recently, he has developed statistical models for the detection of differential item functioning in health surveys, and helped to develop Bayesian meta-analysis models for indirect comparison of medical treatments.
He has co-founded and co-organizes the New England Symposium on Statistics in Sports, a bi-annual conference on the research and practice of applying statistical methods in sports.
Much of Dr. Glickman's publications have been in the realm of health services research. In the mid-1990s, Dr. Glickman's work critiquing the resource-based relative value scale algorithm for the Medicare Fee Schedule had led to his consultation to government agencies in Ontario and Alberta to help develop a statistical approach for medical fee schedule construction. He has received NIH and VA grants to study the genetic predisposition to disease onset for various cardiovascular diseases. More recently, he has developed statistical models for the detection of differential item functioning in health surveys, and helped to develop Bayesian meta-analysis models for indirect comparison of medical treatments.
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论文共 187 篇作者统计合作学者相似作者
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American journal of respiratory and critical care medicineno. 2 (2024): 197-205
CoRR (2024)
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Jonathan Che,Mark Glickman
The Annals of Applied Statisticsno. 2 (2024)
Katy McKeough,Mark Glickman
JOURNAL OF QUANTITATIVE ANALYSIS IN SPORTSno. 1 (2024): 21-35
E. R. Nunez, S. Zhang,M. E. Glickman, S. X. Qian, J. H. Boudreau, P. K. Lindenauer, C. G. Slatore,D. R. Miller,T. J. Caverly, R. S. Wiener
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE (2023)
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Health Services and Outcomes Research Methodologyno. 4 (2022): 468-491
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E. R. Nunez,T. J. Caverly, S. Zhang,M. E. Glickman, S. X. Qian, J. H. Boudreau,D. R. Miller, C. G. Slatore,R. S. Wiener
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