# Mediation, Moderation, and Conditional Process Analysis II

**Description and prerequisites**

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. Participants should have a basic working knowledge of the principles and practice of multiple regression and elementary statistical inference. 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 GSERM or elsewhere. Participants should also have experience use syntax in SPSS, SAS or R, and it is assumed that participants will already have some experience using the PROCESS macro. No knowledge of matrix algebra is required or assumed, nor is matrix algebra ever used in the course.

**Course content**

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 and 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 (www.guilford.com/p/hayes3) Dr. 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 he invented that brings modern approaches to mediation and moderation analysis within convenient reach.

This seminar– a second course –picks up where the first edition of the book and the first course offered by GSERM leaves off. After a review of basic principles, it covers material in the second edition of the book as well as new material in neither edition, reflecting new work recently published by the instructor.

Topics covered include:

- Review of the fundamentals of mediation, moderation, and conditional process analysis.
- Testing whether an indirect effect is moderated and probing moderation of indirect effects.
- Partial and conditional moderated mediation.
- Mediation analysis with a multicategorical independent variable.
- Moderation analysis with a multicategorical (3 or more groups) independent variable or moderator.
- Conditional process analysis with a multicategorical independent variable
- Moderation of indirect effects in the serial mediation model.
- 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.

**Hardware and Software**

Computer applications will focus on the use of OLS regression and the PROCESS macro for SPSS, SAS and R developed by the instructor that makes the analyses described in this class much easier than they otherwise would be.

Students are strongly encouraged to bring their own laptops (Mac or Windows) with a recent version of SPSS Statistics (version 19 or later), SAS (release 9.2 or later) or R (3.6 or later) installed. SPSS users should ensure their installed copy is patched to its latest release. SAS users should ensure that the IML product is part of the installation. PROCESS for R has not yet been publicly released. Participants in this course will receive an advance "beta" release of PROCESS for R before it is released to the public later in the year. Students are also encouraged to bring your own data to apply what you’ve learned. STATA users can benefit from the course content, but PROCESS makes these analyses much easier and is not available for STATA.

**Structure**

The course will consist primarily of lectures, with hands-on demonstration and use of computing software. The course consists of various units of differing length, so no specific structure can be provided. The course progresses at a pace consistent with the needs of the students and the amount of interaction that occurs rather than by a predetermined schedule determined by the clock.

**Literature**

This course is a companion to the instructor’s book Introduction to Mediation, Moderation, and Conditional Process Analysis. The content of the course overlaps the book to some extent, but many of the examples are different, and this course includes material not in either edition of the book.

**Examination **

100% of assessment will be based on a written final examination at the end of the course. The exam will be a combination of multiple choice questions and short-answer/fill in the blank questions, along with some interpretation of computer output. Students will take the examination home on the last day of class and return it to the instructor within one week.

During the examination students will be allowed to use all course materials, such as PDFs of PowerPoint slides, student notes taken during class, and any other materials distributed or student-generated during class. Although the book mentioned in “Literature” is not a requirement of the course nor is it necessary to complete the exam, students may use the book if desired during the exam. A computer is not required during the exam, though students may use a computer if desired, for example as a storage and display device for class notes provided to them during class.

Among the topics of the exam may include how to quantify and interpret path analysis models, calculate direct, indirect, and total effects, and determine whether evidence of a mediation effect exists in a data set based on computer output provided or other information. Also covered will be the testing moderation of an effect, interpreting evidence of interaction, and probing interactions. Students will be asked to generate or interpret conditional indirect effects from computer output given to them and/or determine whether an indirect effect is moderated. Students may be asked to construct computer commands that will conduct certain analyses. All questions will come from the content listed in “Course Content” above.

No literature is required for the examination. Students may choose to use student-generated notes, copies of PowerPoint slides, or the book noted in “Literature” above. All these materials would be relevant to the exam, but they are not necessary to complete the exam.