Education
Event Title
Reproducibility in Medicine and Science
University of California, San Francisco-Stanford University CERSI
Webcast Lecture
Thursday, May 11, 2017
Presented by:
Steven Goodman, MD, MHS, PhD
Associate Dean, Clinical and Translational Research
Professor, Medicine and Health Research and Policy
Stanford University
About the Presentation
Dr. Goodman discussed the problem of research reproducibility from several perspectives. He began by presenting on the varied meanings of the technical term “reproducible.” This term has been applied to everything from computations to methods, results and conclusions. Dr. Goodman then discussed how the concept relates to traditional notions of statistical significance. It was argued that the term “reproducibility,” when used as a surrogate for scientific truth, is confusing and often misleading, and that we should instead be focused on cumulative evidence. A number of factors that are distorting the evidence base in clinical and laboratory research was also discussed.
About the Presenter
Steven Goodman, MD, MHS, PhD is Associate Dean of Clinical and Translational Research and Professor of Medicine (General Medical Disciplines) and of Health Research & Policy (Epidemiology). He directs Stanford's CTSA/Spectrum training programs in medical research methods and serves as chief of the Division of Epidemiology in HRP. He is co-founder and co-director of the Meta-research innovation Center at Stanford (METRICS), a group dedicated to examining and improving the reproducibility and efficiency of biomedical research. He is Vice-chair of the Methodology Committee of the Patient Centered Outcomes Research Institute (PCORI), where he leads their open science and data sharing efforts, and is scientific advisor for the national Blue Cross–Blue Shield Technology Assessment Program. Since 1987, he has also been a senior statistical editor of Annals of Internal Medicine.
Dr. Goodman’s research concerns the proper measurement, conceptualization and synthesis of research evidence, with particular emphasis on Bayesian approaches to quantitation, and qualitative approaches arising from the philosophy of science. Additionally, he has a strong interest in developing curricula and new models for teaching the foundations of good scientific practice, from question development to proper study design, conduct, analysis and inference.
FOR QUESTIONS:
Please contact Amal Manseur at [email protected]