Joint Quantitative Brownbag


David MacKinnon

Dr. David MacKinnon
Department of Psychology
Arizona State University

David P. MacKinnon is a Foundation Professor in the Department of Psychology at Arizona State University. He has wide ranging interests in statistics and methodology but his primary interest is in the area of statistical methods to assess how prevention and treatment programs achieve their effects. He is affiliated with the Prevention Intervention Research Center and the Research in Prevention Laboratory. He came to ASU in 1990 from the University of Southern California’s Institute for Prevention Research, where he had been an assistant professor of research (1986-1990).

Professor MacKinnon teaches graduate analysis of variance, mediation analysis, and statistical methods in prevention research courses. He has given numerous workshops and invited presentations in the U.S. 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 review committees including a term on the Epidemiology and Prevention Research review committee and was a consulting editor for the journal, Prevention Science. Professor MacKinnon has been principal investigator on many federally funded grants and has had a National Institute on Drug Abuse grant to develop and evaluate methods to assess mediation since 1990. He recently received the MERIT award for this mediation analysis research. He is a Thomson-Reuters and Clarivate highly cited researcher. In 2017, he was elected president of the American Psychological Association’s Division on Quantitative and Qualitative Methods. He is president-elect of the Society for Multivariate Experimental Psychology.


How do we know that our statistical methods should work? Benchmarks, Plasmodes, and Statistical Mediation Analysis


This presentation describes a benchmark method to validate statistical methods from the analysis of data on a known or established empirical effect. There are aspects to benchmark validation that complement mathematical derivations and simulations. The method may be useful for evaluating the accuracy of causal conclusions from a statistical method. I apply the method to statistical mediation analysis of the process by which imagery increases recall of words. I discuss strengths and limitations of the method.

Background reading:

  • MacKinnon, D. P., Valente, M. J., & Wurpts, I. C. (2018). Benchmark validation of statistical mediation analysis: Application to imagery and memory theory. Psychological Methods, 23 (4), 854-671.