Christopher Coffey

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Portrait of Chris Coffey, professor of biostatistics and director of the Clinical Trials Statistical and Data Management Center at the University of Iowa College of Public Health.

Title(s): Professor, Director of the Clinical Trials Statistical and Data Management Center, Edwin B. Green Chair in Public Health
Department: Biostatistics
Office: N511 CPHB
Phone: (319) 384-4197

Dr. Coffey is a Professor of Biostatistics and Director of the Clinical Trials Statistical and Data Management Center (CTSDMC) in the University of Iowa College of Public Health. He received his Ph.D. in biostatistics from the University of North Carolina at Chapel Hill in 1999, and has over 20 years of experience providing data management and statistical support to large randomized clinical trials. He is currently the principal investigator of the Data Coordinating Centers for the NIH funded Network of Excellence in Neuroscience Clinical Trials (NeuroNEXT) and the Statistics Core for the Michael J. Fox Foundation funded Parkinson’s Progression Markers Initiative (PPMI). Dr. Coffey has served as the primary statistician for multi-site clinical trials and biomarker studies in cryptogenic sensory peripheral neuropathy, Fragile X syndrome, glioblastoma, GNE myopathy, Huntington’s disease, hypertension, multiple sclerosis, myasthenia gravis, NMDAR encephalitis, obesity, Parkinson’s disease, spinal muscular atrophy, stroke, and traumatic brain injury. Dr. Coffey is a Fellow of the American Statistical Association, Society for Clinical Trials, and American Academy of Neurology. Dr. Coffey is a current member of the FDA Gastrointestinal Diseases Advisory committee, and serves on a number of data and safety monitoring boards. His research interests lie in the area of novel trial designs, particularly the use of adaptive designs.


Courses Taught

  • Statistical Methods in Clinical Trials
  • Advanced Clinical Trials
  • Applied Survival and Cohort Data Analysis

Research Interests

  • Linear Models
  • Power Analyses
  • Sample Size Re-Estimation
  • Adaptive Designs
  • Comparative Effectiveness Trials

Background

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