Mediation, Moderation, and Conditional Process Analysis:
A Second Course
A 4-Week On-Demand Seminar Taught by
Andrew Hayes, Ph.D.
To watch a short video about this course, click here.
Statistical mediation and moderation analyses are among the most widely used data analysis techniques. Mediation analysis is used to test various intervening mechanisms by which causal effects operate. Moderation analysis is used to examine and explore questions about the contingencies or conditions of an effect, also called “interaction.” Conditional process analysis is the integration of mediation and moderation analysis. It’s used when one seeks to understand the conditional nature of processes (i.e., “moderated mediation”)
In his best-selling book, Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach, Andrew Hayes describes the fundamentals of mediation, moderation, and conditional process analysis using ordinary least squares regression. He also explains how to use PROCESS, a freely-available and handy tool that he invented to bring modern approaches to mediation and moderation analysis within convenient reach.
Dr. Hayes has frequently taught an introductory seminar for Statistical Horizons that is based on the material in the first edition of his book. This new seminar– a second course –picks up where the introductory seminar leaves off. After a review of basic principles, it covers material in the second edition of the book, as well as entirely new material from Dr. Hayes’ recently published work. Topics include:
- serial mediation and serial moderated mediation
- mediation, moderation, and conditional process analysis with a multi-categorical cause or moderator
- three-way interaction
- partial, conditional, and moderated moderated mediation
- using PROCESS and the creation of custom models in PROCESS.
This online course takes place in a series of four weekly installments of videos and activities, and requires about 6-8 hours/week. You can participate at your own convenience; there are no set times when you are required to be online. The course can be accessed with any recent web browser on almost any platform, including iPhone, iPad, and Android devices. A discussion forum is available on the course portal for questions and discussion with Andrew Hayes and other participants in the course.
Computer applications will focus on the use of OLS regression and the PROCESS macro for SPSS, SAS, and R. Participants in this online seminar will get a copy of PROCESS for R (in beta form) before it is released to the general public toward the end of 2020. Because this is a hands-on course, participants are strongly encouraged to use their own laptop or desktop computer (Mac or Windows) with a recent version of SPSS Statistics (version 23 or later), SAS (release 9.2 or later, with PROC IML installed), or R (v3.6 or later; base R; no special packages are needed) installed. Participants can choose which statistics package they want to use while working through the course material.
WHO SHOULD Register?
This course will be helpful for researchers in any field—including psychology, sociology, education, business, human development, political science, public health, communication—and others who want to learn how to apply the latest methods in moderation and mediation analysis using readily-available software packages such as SPSS, SAS, and R. Because this is a second course, participants should either be familiar with the contents of the first edition of Introduction to Mediation, Moderation, and Conditional Process Analysis and the statistical procedures discussed therein, or should have taken the first course through Statistical Horizons or elsewhere. Participants should also have experience using syntax in SPSS, SAS or R and a good working knowledge of multiple linear regression. No knowledge of matrix algebra is required or assumed, nor is matrix algebra ever used in the course.
Topics covered in this course include:
- Review of the fundamentals of mediation, moderation, and conditional process analysis.
- Serial mediation
- Moderation of mediation in models with more than one mediator (serial and parallel)
- Differential dominance in conditional process models*
- Mediation analysis with a multi-categorical independent variable.
- Moderation analysis with a multi-categorical (3 or more groups) independent variable or moderator.
- Conditional process analysis with a multi-categorical independent variable.
- Additive multiple moderation and moderated moderation (three-way interaction).
- Partial, conditional, and moderated moderated mediation.
- Advanced uses of PROCESS, such as how to modify a numbered model or customize your own model.
We focus primarily on research designs that are experimental or cross-sectional in nature with continuous outcomes. We do not cover complex models involving dichotomous outcomes, latent variables, nested data (i.e., multilevel models), or the use of structural equation modeling.
*This topic was addressed in the first course offered by Statistical Horizons that was offered May 15-29, 2020.
reviews of the live version of Mediation, Moderation, and Conditional Process Analysis: A Second Course
“Not only do you have the opportunity to be instructed by an absolute expert in the field, but you are also given unique access to this expert’s latest research, materials, and information that you would not have otherwise. Dr. Hayes teaches in such a way that complex material is quickly grasped, and you leave the course with ability to teach it to others yourself.”
Ben McManus, University of Alabama at Birmingham
“Dr. Hayes is a talented instructor. This is my second course with him and he has changed the way I think about my research and use OLS regression to analyze my data. His cutting edge approaches to mediation, moderation and conditional process analysis are a gift to any quantitative researcher.”
Alan K. Goodboy, West Virginia University
“As a researcher and stats instructor, I learned a lot from Andrew’s organization of examples, perfect slides, the way he presents and communicates with the class, and above all, his knowledge and expertise in this area.”
Qiong (Joan) Fu, Lehigh University
“This course is wonderful and incredibly informative. The concepts covered will help greatly in the development of my dissertation and future research. I recommended this to all my colleagues already.”
Billy Caceres, New York University
“The course was extremely helpful for any social/personality psychology researcher. Not only did I come away with a better understanding of the many new capabilities of PROCESS but also with a better mastery of basic regression analyses and principles.”