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Controversies in Modern Mediation Analysis

MacKinnon from CTBH on Vimeo.

April 24, 2015

David MacKinnon, PhD
Professor of Psychology and Director of the Research and Prevention Laboratory, Arizona State University

About the Presentation: The purpose of this presentation is to give an overview of modern mediation analysis with attention to solutions for some of the limitations of these methods. Mediating variables are important for theoretical and applied research in many research areas because they are used to investigate how two variables are related. Examples are the process by which an intervention changes behavior and how a risk factor leads to disease. Over the last decade there has been considerable development of new methods and wider substantive application of mediation analysis. The presentation will describe controversies and suggested solutions from recent work on causal inference, longitudinal models, and statistical testing.

About the Presenter: David P. MacKinnon, Ph.D., is a Foundation Professor in the Department of Psychology at Arizona State University. He received the Ph.D. in measurement and psychometrics from UCLA in 1986. He was an Assistant Professor of Research at the University of Southern California’s Institute for Prevention Research from 1986 to 1990. He has been at Arizona State University since 1990 and is affiliated with the Prevention Intervention Research Center and the Research in Prevention Laboratory. Dr. MacKinnon teaches graduate analysis of variance, mediation analysis, and statistical methods in prevention research. He has given numerous workshops in the United States and Europe. In 2011 he received the Nan Tobler Award from the Society for Prevention Research for his book on statistical mediation analysis. He has served on federal grant review committees and is a former consulting editor of the journal Prevention Science and is on the editorial board of Psychological Methods. Dr. MacKinnon has been principal investigator on several National Institute on Health grants and is a Fellow of the Association for Psychological Science, the Society for Prevention Research and American Psychological Association Measurement and Statistics Division. He is a Thomson-Reuters highly cited researcher. His primary interest is in the area of statistical methods to assess how prevention and treatment programs achieve their effects.