Department of Statistics
Presents the
Robert W. Makuch Distinguished
Lecture in Biostatistics
Featuring
Joseph G. Ibrahim, PhD
Alumni Distinguished Professor
Department of Biostatistics
UNC Gillings School of Global Public Health
The Scale Transformed Power Prior for Use with Historical Data
from a Different Outcome Model
ABSTRACT
We develop the scale transformed power prior for settings where historical and current data involve different data types, such as binary and continuous data, respectively. This situation arises often in clinical trials, for example, when historical data involve binary responses and the current data involve time-to-event or some other type of continuous or discrete outcome. The power prior proposed by Ibrahim and Chen (2000) does not address the issue of different data types. Herein, we develop a current type of power prior, which we call the scale transformed power prior (straPP). The straPP is constructed by transforming the power prior for the historical data by rescaling the parameter using a function of the Fisher information matrices for the historical and current data models, thereby shifting the scale of the parameter vector from that of the historical to that of the current data. Examples are presented to motivate the need for a scale transformation and simulation studies are presented to illustrate the performance advantages of the straPP over the power prior and other informative and non-informative priors. A real dataset from a clinical trial undertaken to study a novel transitional care model for stroke survivors is used to illustrate the methodology.
DATE: Wednesday, March 31, 2021
TIME: 4:00 p.m. EST
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Joseph Ibrahim, Alumni Distinguished Professor of biostatistics, is principal investigator of two National Institutes of Health (NIH) grants for developing statistical methodology related to cancer and genomics research.
Dr. Ibrahim is also the Director of the Biostatistics Core at UNC’s Lineberger Comprehensive Cancer Center. Dr. Ibrahim is currently the biostatistical core leader for the NIH-funded Breast Cancer Specialized Programs of Research Excellence (SPORE) project. He is also co-PI of the statistical P01 grant titled “Statistical Methods in Cancer Clinical Trials.”
Dr. Ibrahim's areas of research focus are Bayesian inference, missing data problems, medical imaging analysis and genomics. He received a Doctor of Philosophy degree in statistics from the University of Minnesota in 1988. With more than 26 years of experience working in cancer clinical trials, Ibrahim directs the UNC Center for Innovative Clinical Trials -- one of eight Gillings Innovation Labs funded by a gift to the School from Dr. Dennis and Joan Gillings.
Dr. Ibrahim is also the director of graduate studies in the Department of Biostatistics at the Gillings School, as well as the program director of the cancer genomics training grant in the same department.
He has served on several national committees and study sections, including as the section chair of the Section on Bayesian Statistical Science of the American Statistical Association and the Biostatistical Methods and Research Design (BMRD) NIH Study Section. He has also served as the associate editor for several statistical journals, and was the editor of the Journal of the American Statistical Society (JASA) - Application and Case Studies from 2013 to 2015.
Dr. Ibrahim has published more than 340 research papers, mostly in the top statistical journals. He also has published two advanced graduate-level books on Bayesian survival analysis and Monte Carlo methods in Bayesian computation. He is an elected fellow of the International Society of Bayesian Analysis, American Statistical Association, Institute of Mathematical Statistics, Royal Statistical Society, and an elected member of the International Statistical Institute.
Robert Makuch is a Professor in the Department of Biostatistics at the Yale School of Public Health and Director of the Regulatory Affairs Track. A graduate of the University of Connecticut (BA), University of Washington (MA – mathematics), and Yale University (MPhil, PhD), Professor Makuch worked at the National Cancer Institute (NCI) and the World Health Organization’s International Agency for Research on Cancer early in his career. He also worked for six months at the National Cancer Research Center in Tokyo, Japan.
He also was heavily involved in HIV research from the mid 80's through the early-mid 90's. He participated on the data monitoring committee for the original AZT vs. placebo randomized clinical trial in AIDS patients, and served on numerous committees for the NCI and the National Institute of Allergy and Infectious Diseases. He also worked closely with the Food and Drug Administration (FDA), developing and implementing more than 200 HIV studies. He also served as a Special Government Employee (SGE) to the FDA. He returned to Yale in 1986, and has worked extensively on methodologic issues in clinical trials and large population-based studies since. Another area of current interest involves detection of rare adverse drug events, especially in the post-marketing environment.
These areas of methodologic research evolved as a result of his continued interest (since the mid 1980s) in regulatory affairs science. In addition, Makuch developed a regulatory affairs track at YSPH for graduate and post-doctoral level students, and over the past 10 years has been the leader of more than 25 training programs for senior delegations of the Chinese Food and Drug Administration. His areas of medical application include cancer, HIV, arthritis, and cardiovascular disease.
In 2003, Makuch received the American Statistical Association Fellow Award for his numerous contributions to the field. In 2008, Makuch was received a Distinguished Alumni Award from the University of Connecticut. In 2012, Makuch was nominated to serve on the University of Connecticut Dean's Advisory Board for the College of Liberal Arts and Sciences. He also has been a decades-long member of Phi Beta Kappa. He also developed a 5-year biostatistics training program in Japan, in collaboration with the Japanese government. His primary research interests continue to be methodologic issues in the design, conduct, analysis, and interpretation of clinical and large-population/epidemiologic studies. Design and sample size considerations for Phase IV studies is another active research area, in which a new class of hybrid designs has been proposed for scientific and regulatory purposes to detect rare adverse events.
For more information, contact: Tracy Burke at tracy.burke@uconn.edu