Sander Greenland is Emeritus Professor of Epidemiology and Statistics at UCLA. He received honors Bachelor's and Master's degrees in Mathematics from the University of California Berkeley where he was Regent's and National Science Foundation Fellow in Mathematics, followed by Master's and Doctoral degrees in Epidemiology from UCLA where he was Regent's Fellow in Epidemiology. He became Professor of Epidemiology in the UCLA Fielding School of Public Health in 1989 and Professor of Statistics in the UCLA College of Letters and Science in 1999. He was made a Fellow of the Royal Statistical Society in 1993, a Fellow of the American Statistical Association in 1998, and was given an honorary doctorate by Aarhus University in 2013. He has published over 400 scientific papers and book chapters, and co-authored a leading advanced textbook on epidemiology. His many contributions to statistics and epidemiology include causal inference, bias analysis, and meta-analysis methods, with a focus on extensions, limitations, and misuses of statistics in nonexperimental studies, especially in postmarketing surveillance of drugs, vaccines, and medical devices.
UCLA FSPH (Pub Hlth) / Epidemiology
BOX 951772, 71-279A CHS
Los Angeles, CA 90095
Sander Greenland is Emeritus Professor of Epidemiology and Statistics at UCLA. He received honors Bachelor's and Master's degrees in Mathematics from the University of California Berkeley where he was Regent's and National Science Foundation Fellow in Mathematics, followed by Master's and Doctoral degrees in Epidemiology from UCLA where he was Regent's Fellow in Epidemiology. He became Professor of Epidemiology in the UCLA Fielding School of Public Health in 1989 and Professor of Statistics in the UCLA College of Letters and Science in 1999. He was made a Fellow of the Royal Statistical Society in 1993, a Fellow of the American Statistical Association in 1998, and was given an honorary doctorate by Aarhus University in 2013. He has published over 400 scientific papers and book chapters, and co-authored a leading advanced textbook on epidemiology. His many contributions to statistics and epidemiology include causal inference, bias analysis, and meta-analysis methods, with a focus on extensions, limitations, and misuses of statistics in nonexperimental studies, especially in postmarketing surveillance of drugs, vaccines, and medical devices. He has served as an associate editor for several statistics and epidemiology journals, as an advisor for the Food and Drug Administration, the Environmental Protection Agency, the Centers for Disease Control, the State of California, and the National Academy of Sciences, and has been an invited speaker at universities and conferences throughout the world.
Does this profile need updating? Contact Us