Mediation and Moderation

A 5-Day Seminar Taught by Andrew Hayes, Ph.D. 

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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 among the leading recent contributors to the literature on these methods. 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 underlying 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 by discussing how to estimate conditional indirect effects, determine whether an indirect effect is moderated (moderated mediation) and whether moderated effects are mediated (mediated moderation).

Computer applications will focus on the use of OLS regression and computational modeling tools for SPSS and SAS (including the PROCESS add on developed by Hayes).  When appropriate, some Mplus code will be provided for those interested, but structural equation modeling and Mplus will not be the emphasis of this seminar.

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 Monday, July 14 through Friday, July 18 at The Hub Commerce Square, 2001 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 $1695.00 includes all seminar materials. 

Lodging Reservation Instructions

Guests room blocks have been reserved at the following nearby hotels.

Sonesta, 1800 Market Street, Philadelphia.  Call 1-800-SONESTA (766-3782) by June 17 and mention Statistical Horizons for the $159 group rate.  Distance to seminar site – .2 miles walk/4 min.

Embassy Suites, 1776 Benjamin Franklin Parkway, Philadelphia. Call 1-800-EMBASSY (362-2779) by June 13 and mention Statistical Horizons for the $159 group rate. Distance to seminar site – .5 mile walk 10 min.

Club Quarters Hotel, 1628 Chestnut Street, Philadelphia. Call 203-905-2100 by June 13 and mention STA007 for the $121 group rate. Distance to seminar site – .6 mi/12 min.

Seminar outline

1.  Review of OLS regression principles.
2.  A Path analysis primer: Direct, indirect, and total effects in mediation models.
3.  Estimation and inference in single mediator models.
4.  Estimation and inference in multiple mediator models (parallel and serial).
5.  Mediation analysis with multicategorical independent variables.
6.  Effect size for indirect and direct effects.
7.  Moderation/interaction in OLS regression.
8.  Probing and visualizing interactions.
9.  The effects of variable scaling and model parameterization on interpretation.
10.  Moderation analysis in complex models with multiple and higher order interactions.
11.  Modeling conditional mechanisms—“Conditional Process Analysis.”
12.  Quantification of and inference about conditional indirect effects.
13. Testing a moderated mediation hypothesis and comparing conditional indirect effects.
14.  Mediated moderation: The concept and its problems.

Relative to the two-day version of this course offered on occasion by Statistical Horizons, this five day course will go into further depth with more examples and touch on a greater number of topics. 

Comments from recent participants

“As a doctoral student, I will definitely benefit from all the knowledge on mediation and moderation analysis, which is clearly documented in the manual. Andrew Hayes explains each effect with the use of clear visuals and answers to all relevant questions”
  Caroline De Bondt, Ghent University

“As a PhD student who has not yet planned my dissertation, I feel that this course has provided me with powerful tools and skills to more effectively design and analyze studies that will ultimately influence the trajectory of my career.”
  Jordan Clark, University of Nevada

“It has been a great experience coming under the critical but well delivered lectures on moderation and mediation. I can now confidently analyze, interpret and report data on moderation, mediation, mediated moderation as well as moderated mediation studies.”
  Sesan Mabekoje, Olabisi Onabanjo University, Nigeria

“This course combines a lot of very different, well explained examples, which make statistics less abstract and more fun.”
  Elke Huyghe, Ghent University

“The course on Mediation and Moderation 2013 was extremely helpful to me. I had a good background in statistics, but often felt insecure when analyzing my data. This clear course, taught by Andrew Hayes, has given me confidence and even enthusiasm, in statistical analysis.”
  Stefanie Baert, Ghent University

“It’s an excellent class for me to understand the mediation and moderation analysis with a new way of thinking. It’s a hands-on course so I can take home the techniques that can easily apply in my data analyses.”
  Ran Wu, Yale University

“The course really boosted my confidence and I did come away with tangible skills to apply to my data. I would recommend this to other doctoral students because the class was helpful and accessible and can give you a deeper sense of understanding of these concepts. Really great course.”
  Amanda Garcia-Williams 

“The course is beyond helpful!  Dr. Hayes’ lecture notes are easy to follow, his presentation of the material is clear, and he is extremely approachable. There is something in this course for individuals at various levels of familiarity with regression.”
  DeLeon Gray, North Carolina State University 

“Moderation and mediation tests by PROCESS are becoming the new norm in management research. Andy is more than helpful in explaining how to apply this technique and related methods in research. It’s a very intense week. But I promise you won’t regret it.”
  Dr. Zhi Tang, Rochester Institute of Technology

“This is truly an eye opening workshop about some of the cutting edge analysis that can be done using SPSS.”
  Ramayah, Universiti Sains Malaysia

“This is an outstanding course! I recommend it highly, particularly for researchers using experimental designs that also incorporate mediation or moderation by individual differences.”
  Brian Lickel, UMass, Amherst