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Andrew F. Hayes

Andrew F. Hayes, Ph.D., is Distinguished Research Professor in the Haskayne School of Business and Adjunct Professor in the Department of Psychology at the University of Calgary.

Professor Hayes’ research focuses on linear models, with an emphasis on resampling methods of inference. Specific areas of investigation and writing include statistical approaches to assessing mediation, moderation, and the contingencies of mechanisms.  He hold a Ph.D. in Psychology from Cornell University (1996) and a B.A. in Psychology from San Jose State University (1991).

Hayes invented the PROCESS macro for SPSS, SAS and R, widely used by researchers examining the mechanisms and contingencies of effects. Hayes’ methodology work is published in such locations as Psychological MethodsMultivariate Behavioral Research, Behavior Research Methods, Psychological Science, the British Journal of Mathematical and Statistical PsychologyBehaviour Research and TherapyAmerican Behavioral Scientist, and Communication Monographs.

He has written extensively on research methodology, including Introduction to Mediation, Moderation, and Conditional Process Analysis (2022), Regression Analysis and Linear Models (2017) and Statistical Methods for Communication Science (2005). His work in books and journal articles in methodology as well as various substantive areas has been cited well over 200,000 times according to Google Scholar, and he has been designated a Highly Cited Researcher by Clarivate Analytics in 2019, 2020, 2021, and 2022.

You can visit his personal webpage here.

Google Scholar Citation Page

Andrew's Seminars

PROCESS vs. Structural Equation Modeling

This seminar will compare and contrast the benefits and pitfalls of using a regression-based approach to mediation, moderation, and conditional process analysis compared to an SEM approach.

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