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The Prevention and Treatment of Missing Data in Clinical Trials Appendix B Biographical Sketches of Panel Members and Staff RODERICK J.A. LITTLE (Chair) is Richard D. Remington collegiate professor of biostatistics in the School of Public Health at the University of Michigan. Previously, he held positions at the World Fertility Survey, as an American Statistical Association (ASA)/National Science Foundation fellow at the U.S. Census Bureau, and in the Department of Biomathematics at the University of California at Los Angeles. His areas of research focus on the analysis of data with missing values in many areas of application, including clinical contexts. He received the ASA’s Wilks’ Memorial Award in 2004, and he gave the president’s invited address at the Joint Statistical Meetings in 2005. He is an elected member of the International Statistical Institute and a fellow of ASA. He received a B.A. with honors in mathematics from Cambridge University and an M.S. in statistics and operational research and a Ph.D. in statistics from the Imperial College of Science and Technology of London University. MICHAEL L. COHEN (Study Director) is a senior program officer for the Committee on National Statistics where he directs studies involving statistical methodology, in particular on defense system testing and decennial census methodology. Formerly, he was a mathematical statistician at the Energy Information Administration, an assistant professor in the School of Public Affairs at the University of Maryland, and a visiting lecturer in the Department of Statistics at Princeton University. A fellow of ASA, he has a B.S. in mathematics from the University of Michigan, and M.S. and Ph.D. degrees in statistics from Stanford University.
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The Prevention and Treatment of Missing Data in Clinical Trials RALPH D’AGOSTINO is chair of the Mathematics and Statistics Department, professor of mathematics/statistics and public health, and director of the Statistics and Consulting Unit and the executive director of the M.A./Ph.D. program in biostatistics, all at Boston University. He has been affiliated with the Framingham Study since 1982, and is coprincipal investigator of the core contract and director of data management and statistical analysis for the study. His major fields of research are clinical trials, epidemiology, prognostics models, longitudinal analysis, multivariate analysis, robustness, and outcomes/effectiveness research. He is a fellow of ASA and the Cardiovascular Epidemiology Council of the American Heart Association. He has twice received the special citation of the commissioner of the U.S. Food and Drug Administration (FDA), and he was named statistician of the year by the Boston Chapter of ASA. He received A.B. and A.M. degrees in mathematics from Boston University and a Ph.D. in mathematical statistics from Harvard University. KAY DICKERSIN is director of the Center for Clinical Trials at the Bloomberg School of Public Health and professor in the Department of Epidemiology, both at Johns Hopkins School of Public Health. Previously, she served as the director of the Center for Clinical Trials and Evidence-based Health Care at Brown University and held faculty positions in the Department of Epidemiology and Preventive Medicine and the Department of Ophthalmology at the University of Maryland School of Medicine. Her areas of research include randomized clinical trials, trials registers, systematic reviews and meta-analysis, publication bias, peer review, and evidence-based health care. She has received a Howard Hughes Fellowship in medical research from Harvard Medical School, and she is an elected member of the Institute of Medicine. She received B.A. and M.A. degrees in zoology from the University of California at Berkeley and a Ph.D. in epidemiology from the School of Hygiene and Public Health of Johns Hopkins University. SCOTT S. EMERSON is professor of biostatistics in the Department of Biostatistics at the University of Washington. Previously, he held faculty positions at the Fred Hutchinson Cancer Research Center and the University of Arizona. His areas of research are clinical trials, sequential testing, survival analysis, categorical data, nonparametric Bayesian statistics, classification and regression trees, statistical consulting, and computer-intensive methods in statistics. He is a fellow of ASA. He received a B.A. in physics, an M.S. in computer science, and an M.D. from the University of Virginia, as well as a Ph.D. in biostatistics from the University of Washington.
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The Prevention and Treatment of Missing Data in Clinical Trials JOHN T. FARRAR is assistant professor of epidemiology in the Department of Biostatistics and Epidemiology at the University of Pennsylvania School of Medicine. Previously, he held positions at the Children’s Hospital of San Francisco, at the New York Hospital of Cornell Medical Center in New York, and in the Department of Neurology of Memorial Sloan Kettering Cancer Center. His areas of research include studies of pain and symptom management. Other interests include pharmaco-epidemiological studies using large databases, functional neuroimaging studies of the neurological manifestations of pain related disease, and novel methodologies in the design and execution of clinical trials. He received a Sc.B. from Brown University, an M.S. in clinical epidemiology from the University of Pennsylvania School of Medicine, an M.D. from the University of Rochester School of Medicine, and a Ph.D. in epidemiology and biostatistics from the University of Pennsylvania School of Medicine. CONSTANTINE FRANGAKIS is associate professor in the Department of Biostatistics in the Bloomberg School of Public Health at Johns Hopkins University. His areas of research include the development of designs and methods of analyses to evaluate treatments in medicine, public health and policy (causal inference), as well as new methods for studies that explore the factors that can be controlled. He is an elected fellow of the Center for Advanced Studies in the Behavioral Sciences, and the recipient of the H.C. Yang Memorial Faculty Award in Cancer Prevention from Johns Hopkins University. He received a B.Sc. in mathematics with statistics from Imperial College of the University of London and his A.M. and Ph.D. degrees in statistics from Harvard University. JOSEPH W. HOGAN is professor in the biostatistics section of the Program in Public Health and a faculty member in the Center for Statistical Sciences, both at Brown University. His research focuses on statistical methods for missing data, causal inference, and sensitivity analysis, including work on informative dropout and noncompliance. Recent topics of investigation include formulation of coherent sensitivity analyses for understanding the effects of missing data assumptions on statistical inferences, use of informative prior distributions to characterize assumptions about missing data mechanisms, and use of flexible models such as regression splines for analyzing incomplete longitudinal data. He is a fellow of ASA. He received a B.A. in mathematics from the University of Connecticut, an M.S. in statistics from the University of Southern California, and a Ph.D. in biostatistics from Harvard University.
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The Prevention and Treatment of Missing Data in Clinical Trials GEERT MOLENBERGHS is professor of biostatistics at Universiteit Hasselt and Katholieke Universiteit Leuven in Belgium. He was the founding director of the Center for Statistics at Universiteit Hasselt, and he is also the director of the Interuniversity Institute for Biostatistics and statistical bioinformatics. His research interests focus on surrogate markers in clinical trials, and on categorical, longitudinal, and incomplete data. He has served as president of the International Biometric Society, and he received the Guy Medal in Bronze from the Royal Statistical Society and the Myrto Lefkopoulou Award from the Harvard School of Public Health. He received a B.S. degree in mathematics and a Ph.D. in biostatistics (1993) from Universiteit Antwerpen. SUSAN A. MURPHY is H.E. Robbins professor of statistics in the Department of Statistics, research professor at the Institute for Social Research, and professor of psychiatry, all at the University of Michigan. Her primary interest is in causal inference and multistage decisions, sometimes called dynamic treatment regimes or adaptive treatment strategies. Prior to her current position, she held faculty positions in the Department of Statistics at the Pennsylvania State University. She is a fellow of ASA and the Institute of Mathematical Statistics, and she is an invited fellow at the Center for Advanced Study in the Behavioral Sciences. She received a B.S. in mathematics from Louisiana State University and a Ph.D. in statistics from the University of North Carolina at Chapel Hill. JAMES D. NEATON is professor of biostatistics in the Division of Biostatistics in the School of Public Health at the University of Minnesota. His areas of research include the design and conduct of clinical trials and the application of statistical models to the analysis of data arising from intervention studies. He has served as president of the Society for Clinical Trials, as editor in chief of Controlled Clinical Trials, and on numerous data and safety monitoring committees. He is a fellow of ASA. He received B.A. and M.S. degrees in biometry from the University of Minnesota and a Ph.D. in biometry from the University of Minnesota. ANDREA ROTNITZKY is a professor in the Departmento de Economia at the Universidad Torcuato Di Tella in Buenos Aires, Argentina. She is also a visiting professor in the Department of Biostatistics at the Harvard School of Public Health, where she previously held faculty positions. Her areas of research include inference with missing data, causal inference from observational studies with time dependent treatment and confounders, analysis of clinical trials with noncompliance, recovery of information from surrogate marker data in clinical trials, analysis of informatively censored data, and semiparametric efficiency theory. She received a B.S. in mathematics from
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The Prevention and Treatment of Missing Data in Clinical Trials the Universidad de Buenos Aires in Argentina, and M.A. and Ph.D. degrees in statistics from the University of California at Berkeley. DANIEL SCHARFSTEIN is a professor and director of the graduate program in the Department of Biostatistics in the Bloomberg School of Public Health at Johns Hopkins University. His research interests focus on inferences about population parameters when they are not estimable from observed data without the imposition of strong, untestable assumptions. He focuses on both frequentist and Bayesian approaches to evaluating the robustness of results to such assumptions as missing at random and no unmeasured confounding. He received a B.S. in economics and in applied science from the University of Pennsylvania, an M.S. in operations research from Georgia Tech, and M.S. and Ph.D. degrees in biostatistics from the Harvard School of Public Health. WEICHUNG (JOE) SHIH is professor and chair of the Department of Biostatistics at the University of Medicine and Dentistry of New Jersey, where he also holds appointments in the Cancer Institute of New Jersey and the Environmental and Occupational Health Sciences Institute. Previously, he was a senior investigator and director of scientific staff in the Department of Clinical Biostatistics and Research Data Systems at Merck. His research interests include statistical methods for handling missing data and adaptive designs of clinical trials. He is a fellow of ASA and is an elected member of the International Statistics Institute. He received the Excellence in Service Award for participating in the advisory board of FDA of the U.S. Department of Health and Human Services. He received a Ph.D. degree in statistics from the University of Minnesota. JAY P. SIEGEL is group president for biotechnology, immunology, and oncology research and development and worldwide regulatory affairs, quality assurance, and benefit risk management at Johnson & Johnson. He also serves as the president of Centocor Research and Development. In addition to previous positions at Johnson & Johnson, he served as the director of Office of Therapeutics Research and Review in the Center for Biologics Evaluation and Research at FDA, where he was also the founding director of the Division of Clinical Trial Design and Analysis. His areas of research include the development of new biotechnology pharmaceutical products, new uses for approved products, and new technologies for the efficient manufacture of such products. He has received numerous awards from the U.S. Department of Health and Human Services for his government work, including the Distinguished Service Medal, the highest honor awarded by the Public Health Service. He is a fellow of the American College of Physicians and of the Infectious Disease Society of America. He received a B.S. in biology from
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The Prevention and Treatment of Missing Data in Clinical Trials California Institute of Technology and an M.D. from the Stanford University School of Medicine. HAL STERN is professor and chair of the Department of Statistics at the University of California at Irvine. Previously, he held faculty positions at Harvard University and at Iowa State University, where he directed graduate studies and held the Laurence H. Baker chair in biological statistics. His interests are in the areas of Bayesian methods, model diagnostics, and statistical applications to biological and social sciences. He received a B.S. in mathematics from the Massachusetts Institute of Technology and M.S. and Ph.D. degrees in statistics from Stanford University.