CAST Seminar: Frank Harrell

Join us at the CANSSI Ontario STatistics Seminars (CAST) with

Frank E. Harrell, Jr.

Professor, Department of Biostatistics, Vanderbilt University School of Medicine
Expert Biostatistics Advisor, US FDA Center for Drug Evaluation and Research

Free Virtual Event | Registration Required

Talk Title

Ordinal State Transition Models as a Unifying Risk Prediction Framework

Abstract

In this talk I will present a case for the use of discrete time Markov ordinal longitudinal state transition models as a unifying approach to modeling a variety of outcomes for the purpose of estimating risk and expected time in a given state, and for comparing treatments in clinical trials. This model structure can be used to analyze time until a single terminating event, longitudinal binary events, recurrent events, continuous longitudinal data, and longitudinal ordinal responses including multiple events. Partial information can be formally incorporated using standard likelihood approaches without the need for imputation. The model also provides a formal way to assess evidence for consistency of a treatment effect over different outcomes.

Speaker Profile

Dr. Harrell received his PhD in Biostatistics from UNC in 1979. Since 2003 he has been Professor of Biostatistics, Vanderbilt University School of Medicine, and was the department chairman from 2003-2017. He is Expert Biostatistics Advisor to FDA CDER and was Expert Biostatistics Advisor for the Office of Biostatistics for FDA CDER from 2016- 2020. He is Associate Editor of Statistics in Medicine. He is a Fellow of the American Statistical Association and winner of the Association’s WJ Dixon Award for Excellence in Statistical Consulting for 2014. His specialties are development of accurate prognostic and diagnostic models, model validation, clinical trials, observational clinical research, cardiovascular research, technology evaluation, pharmaceutical safety, Bayesian methods, quantifying predictive accuracy, missing data imputation, and statistical graphics and reporting.