BIO

for Professor Carl N. Morris



Dr. Carl N. Morris (Ph.D. Statistics, Stanford, 1966; B.S. Statistics, California Institute of Technology, 1960) is Professor at the Harvard Faculty of Arts and Sciences, Department of Statistics. Dr. Morris joined Harvard in 1990 with Professorships evenly split between the Statistics Department (Arts and Sciences), and the Department of Health Care Policy (Harvard Medical School), but that changed in 1995, when Chairing the Department of Statistics required his full-time attention. Dr. Morris' career includes Editorships of two leading statistics journals, Editor of Journal of the American Statistical Association (1983-1985), and Executive Editor of Statistical Science (1989-1991). He is a Fellow of the ASA, IMS, and Royal Statistical Society; an elected member of ISI; and a member of the Biometric Society.

During his career, Dr. Morris has sought out interdisciplinary and novel applications that implement and challenge new statistical theory. His research in the interface of statistical theory and scientific application has been aided by appointments in departments of statistics, mathematics, economics, health policy, and of behavioral sciences. Dr. Morris is best known for his contributions to the theory of hierarchical models and of empirical Bayes methods with applications to many fields, particularly including health care policy. Over the years this work has been supported by grants from the National Science Foundation, the Agency for Health Care Policy Research, the Veterans Administration, the U.S. Census Bureau, the Environmental Protection Agency, and the National Aeronautics and Space Administration. These grants also have supported his continuing work on natural exponential families with quadratic variance functions (NEF-QVF), which was recognized as a breakthrough (Volume III on Breakthrough in Statistics, Springer, 1997).

Hierarchical modeling applications of particular continuing relevance in health services research concern evaluating the quality of medical units. With collaborators and students at Harvard, and with Veterans Affairs researchers involved in profiling VA hospitals, Dr. Morris continues this research on mental and physical health and on medical profiling. This work builds on his Agency for Health Care Policy Research grant that identified important medical and health services applications of hierarchical models. Earlier work in health policy research spanned medical profiling, experimental design, and public policy experiments. He is known for his earlier experimental design work in the RAND Health Insurance Experiment and in particular for the Finite Selection Model that he developed for creating optimally balanced experiments in the HIE. Dr. Morris has also done pioneering work in the theory of statistics as applied to sports and competition, especially in baseball and tennis.