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Dr. Michael Griswold

Biostatistics & Bioinformatics, UMMC

Brief Biography:

Dr. Griswold is the Director of the Center of Biostatistics & Bioinformatics and an associate professor at the University of Mississippi Medical Center. He also has adjunct associate professor appointments in the Departments of Biostatistics at the Johns Hopkins School of Public Health and the University of Alabama at Birmingham School of Public Health for which he develops curriculum and conducts courses on the analyses of multilevel and longitudinal data. Dr. Griswold serves as an Associate Editor for the Annals of Internal Medicine and previously directed the Johns Hopkins Biostatistics Center. He has extensive experience in leading the design, execution, and analysis of both observational and experimental studies and consults regularly for academic institutions, medical-journal editorial committees, government regulatory agencies, and industry research organizations on statistical issues. Dr. Griswold also serves as the Associate Director for Data Analyses and Chair of the Data Management Team for the Jackson Heart Study, a national research resource for studying minority health and healthcare disparities. Dr. Griswold has supervised the statistical planning and implementation of numerous clinical research consortia studies and related research education activities, and his efforts are targetted at connecting translational research teams across the laboratory, clinical and population science levels. His international collaborative and educational interests have led to his delivering instructional courses and consultations in Finland, Armenia, Bangladesh and Saudi Arabia. Dr. Griswold believes in the paradigm of reproducible research and infuses this into his own research and the groups which he leads.


Academic positions:

Director, Biostatistics & Bioinformatics

Associate Professor

University of MS Medical Center



Research interests:

Primary goals lie in the advancement of scientific discovery through the development, application and translation of statistical methodolgy. Research-based statistical collaboration acts a key interface between science and statistics, and it is here that reciprocal translation can greatly facilitate discovery. I promote collaborative and developmental consultations that enable synergistic relationships between substantive and statistical research.

My methodologic interests have concerned the modeling and interpretation of complex longitudinal data, where multifaceted associations, non-standard distributions, and informative censoring can all play a role. In these instances, multiple models and multiple model checking mechanisms are crucial for validating inferences.



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