Mediation and Moderation

A 2-Day Seminar Taught by Andrew Hayes, Ph.D. 

Read reviews of this course


This seminar focuses on two topics in causal analysis that are closely related and often confused. Suppose we have three variables, X, M and Y. We say that M is a mediator of the effect of X on Y if X carries its influence on Y at least partly by influencing M, which then influences Y. This is also known as an indirect effect of X on Y through M. On the other hand, we say that M moderates the effect of X on Y if that effect varies in size, sign, or strength as a function of M. This is also known as interaction

Although these concepts are fairly simple, the statistical issues that arise in estimating and testing mediation and moderation effects turn out to be rather complex and subtle. Andrew Hayes has been one of the leading contributors to the literature on these methods. Working with Kristopher Preacher, he has developed powerful new methods for estimating mediation and moderation effects and special software tools that can be used with SAS or SPSS.   

In this seminar, you will learn about the underling principles and the practical applications of these methods. The seminar is divided roughly into three parts:

1. Partitioning effects into direct and indirect components, and how to quantify and test hypotheses about indirect effects.

2. Estimating, testing, probing, and visualizing interactions in linear models.

3. Integrating moderation and mediation analysis by discussing how to test whether a mechanism (an indirect effect) is moderated.

Computer applications will focus on the use of OLS regression and the PROCESS macro for SPSS and SAS.

Because this is a hands-on course, participants are strongly encouraged to bring their own laptops (Mac or Windows) with a recent version of SPSS Statistics (version 19 or later) or SAS (release 9.2 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. You should have good familiarity with the basics of ordinary least squares regression (although an overview of OLS will be the first topic of the course), as well as the use of SPSS or SAS. You are also encouraged to bring your own data to apply what you’ve learned.


Who should attend? 

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 and SAS. Participants should have a basic working knowledge of the principles and practice of multiple regression and elementary statistical inference. No knowledge of matrix algebra is required or assumed.


Location and Materials 

The course meets 9 a.m. to 5 p.m. on Friday, September 19 and Saturday, September 20 at Temple University Center City, 1515 Market Street, Philadelphia, PA.

Participants receive a bound manual containing detailed lecture notes (with equations and graphics), examples of computer printout, and many other useful features. This book frees participants from the distracting task of note taking. 


Registration and lodging

The fee of $895.00 includes all seminar materials. 

Lodging Reservation Instructions

A block of guest rooms has been reserved at the Club Quarters Hotel, 1628 Chestnut Street, Philadelphia, PA at a special rate of $142 per night for a Standard room. This location is about a 5 minute walk to the seminar location. In order to make reservations, call 203-905-2100 during business hours and identify yourself by using group code STA918.  For guaranteed rate and availability, you must reserve your room no later than August 18, 2014. There is a shortage of hotel rooms in Philadelphia for these dates so please make your reservation as early as possible.


Seminar outline

1.  Overview of linear modeling principles
2.  A Path analysis primer: Direct, indirect, and total effects
3.  Estimation and inference in single mediator models
4.  Estimation and inference in parallel and serial multiple mediator models
5.  Moderation/interaction in OLS regression
6.  Probing and visualizing interactions
7.  Conditional Process Analysis (Moderated mediation)


Comments from recent participants

“This course was efficient and extremely well taught. The combination of excellent instruction, user friendly resources (e.g. code, handouts, reading, manual etc.) made this course very successful. It will be very easy to apply these methods into my work. As a doctoral student, it was rewarding to take this class with the professor, as I learned significantly from my peers. I highly recommend this class.”
  Katherine Muldoon, University of British Columbia

“Dr. Hayes is a gifted statistician and social scientist. His ability to communicate highly complex information in a clear and practical manner is unparalleled. He seems to have found the right balance between statistical theory, math and practical application. His passion for statistics, willingness to share his materials and his general approachability are truly inspirational. Not only did I learn new ‘stuff’ but I also came away with helpful strategies for how to teach statistics to graduate students.”
  Shelley Brown, Carleton University 

“Excellent course. Many people who are good at statistics are not good at explaining statistics, or so I have found. This is not the case with Professor Hayes! Professor Hayes moves at a pace that is neither too fast nor too slow, explaining concepts in a simple, straightforward manner. By providing students with data sets, he allows them to learn by doing. I was able to immediately apply what I learned in his class by revising a manuscript I had been working on and submitting it for publication the very night the conference ended.”
  Karyn Riddle, University of Wisconsin

“A great course for getting solid grounding in mediation and moderation. Cleared up a number of misunderstandings and misconceptions. I would highly recommend this course to beginners looking to learn these techniques or regular users looking to refine their skill set.”
  Larry Hearld, University of Alabama at Birmingham 

“I currently teach a year-long statistics course sequence for first year PhD students. I benefitted from this course in several ways. 1. New ways of thinking about and teaching constructs. 2. Learned how to use PROCESS and will incorporate into courses. 3. Felt like some information was ‘cutting edge’ (i.e., not in print yet). I benefitted from the course and I believe my students will too.”
  Philip Osteen, University of Maryland