Douglas E. Faries
Senior Research Advisor, Lilly USA
Douglas E. Faries is Senior Research Advisor at Lilly USA, where he oversees statistical design and analysis support for Health Outcomes Research, including retrospective claims data analyses and prospective observational studies. A SAS user for more than twenty years, he received his PhD in Statistics from Oklahoma State University and his MS in Mathematics from Western Illinois University. Dr. Faries is a member of the American Statistical Association and the International Society of Pharmacoeconomic and Outcomes Research.
By This Author
Real World Health Care Data Analysis: Causal Methods and Implementation Using SAS®
Real world health care data from observational studies, pragmatic trials, patient registries, and databases is common and growing in use. Real World Health Care Data Analysis: Causal Methods and Implementation in SAS® brings together best practices for causal-based comparative effectiveness analyses based on real world data in a single location. Example SAS code is provided to make the analyses relatively easy and efficient.
The book also presents several emerging topics of interest, including algorithms for personalized medicine, methods that address the complexities of time varying confounding, extensions of propensity scoring to comparisons between more than two interventions, sensitivity analyses for unmeasured confounding, and implementation of model averaging.
Analysis of Observational Health Care Data Using SAS®
*Replaced by a new edition, Real World Health Care Data Analysis: Causal Methods and Implementation Using SAS®