Critical Analysis of Randomized Clinical Trials

Dr. Steven Goodman serves as Associate Dean of Clinical and Translational Research and Professor of Epidemiology and Population Health at Stanford University School of Medicine, where he has established himself as a leading authority in medical statistics and research methodology. After earning degrees from Harvard (AB in Biochemistry and Applied Math), NYU (MD), and Johns Hopkins (MHS in Biostatistics and PhD in Epidemiology), he has built an impressive career combining clinical expertise with statistical innovation. As founder and director of the Stanford Program on Research Rigor and Reproducibility (SPORR) and co-director of the Meta-research Innovation Center at Stanford (METRICS), he works to improve the reproducibility and efficiency of biomedical research. His research focuses on the proper measurement and synthesis of research evidence, with particular emphasis on Bayesian approaches and scientific inference. Dr. Goodman's contributions have earned him numerous honors, including the 2016 Spinoza Chair in Medicine from the University of Amsterdam, the 2019 Abraham Lilienfeld award from the American College of Epidemiology, and election to the National Academy of Medicine in 2020. Beyond his academic work, he maintains roles as senior statistical editor for Annals of Internal Medicine and scientific advisor for the Blue Cross-Blue Shield Technology Assessment Program, while continuing to shape the field through his teaching and research in clinical trial methodology, statistical inference, and research ethics.

Dr. Rita Popat serves as Associate Professor of Epidemiology and Population Health at Stanford University, where she has established herself as an accomplished educator and researcher in clinical epidemiology. Her diverse academic background includes a PhD in Epidemiology from Stanford University, an MS in Biostatistics from the University of Massachusetts, and an MS in Physical Therapy from MGH Institute of Health Professions. In her current roles, she serves as Co-Director of the Clinical Research Scholarly Concentration Program and the MS program in Clinical Research & Epidemiology, while also maintaining active involvement in Stanford Medicine's Teaching and Mentoring Academy. Her research focuses on the epidemiology of neurodegenerative disorders, particularly Parkinson's disease and amyotrophic lateral sclerosis, examining genetic and environmental factors in disease development. She has also made significant contributions to research methodology, including developing an expanded screening questionnaire for restless legs syndrome. Dr. Popat's excellence in teaching has been consistently recognized through multiple awards, including the Kaiser Foundation Award for Excellence in Preclinical Teaching and numerous Teaching Awards from the Division of Epidemiology. Her current work includes teaching essential courses in clinical trials design, epidemiologic research methods, and data management, while mentoring numerous graduate and undergraduate students in their research endeavors

Dr. Sarah Osmundson currently serves as an Associate Professor of Obstetrics & Gynecology in the Division of Maternal-Fetal Medicine at Vanderbilt University Medical Center, having previously held positions at Stanford University. She completed her medical degree at the University of Illinois Chicago in 2006, followed by a residency at Northwestern Memorial Hospital in 2010 and a fellowship at Stanford University Medical Center in 2014. Her research and clinical expertise focus on maternal health outcomes, particularly in gestational diabetes and advanced maternal age pregnancies. She has made significant contributions to understanding pregnancy complications and maternal care, with over 2,000 academic citations to her work. Her research portfolio includes influential studies on labor outcomes in advanced maternal age and the predictive value of first-trimester hemoglobin A1c testing for gestational diabetes. As an educator, Dr. Osmundson has contributed to training medical students and residents in health services research, focusing on quantitative analysis of healthcare issues. Originally from Chicago, she has established herself as a leading voice in maternal-fetal medicine, combining clinical practice with research to improve pregnancy outcomes and maternal care standards.

Raymond Deng is advancing healthcare research while pursuing his medical degree at Stanford School of Medicine, building on his strong foundation in health policy from Harvard School of Public Health. His research has made significant contributions to understanding opioid use patterns, particularly through his study of the Veterans Health Administration database where he analyzed opioid prescription data from 1.3 million veterans to identify predictors of opioid discontinuation. His findings showed that 65% of patients continued opioid use after one year, with notable patterns among patients with schizophrenia and dementia. Beyond his academic pursuits, Deng's interest in addiction medicine is driven by personal experience, motivating his focus on prescription drug abuse and its relationship to heroin use. His recent work includes developing machine learning models to predict buprenorphine-naloxone treatment retention, achieving prediction accuracy comparable to clinical experts. As a medical student, he has participated in Stanford's annual Medical Student Research Symposium, where he has presented his findings on addiction medicine and contributed to the scholarly discourse on opioid use patterns and treatment outcomes