Mediation, Moderation, and Conditional Process Analysis
A 2-Day Seminar Taught by Andrew Hayes, Ph.D.
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
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 seminar meets Friday, October 28 and Saturday, October 29 at the Manhattan Beach Marriott, 1400 Parkview Avenue Manhattan Beach, California 90266.
The class will meet from 9 to 5 each day with a 1-hour lunch break.
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.
Although not essential for the seminar, you can purchase Andrew Hayes’s book, “Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach,” by clicking here. Use code 2E for a 20% discount and free shipping.
Registration and lodging
The fee of $995.00 includes all seminar materials.
Lodging Reservation Instructions
A block of rooms has been reserved at the Manhattan Beach Marriott, 1400 Parkview Avenue Manhattan Beach, California 90266 at a special rate of $169 per night. In order to guarantee rate and availability, make your reservations by calling Marriott Reservation 1 (888) 236 2427 or1 (310) 546-7511 no later than, Thursday, October 6, 2016 and identify yourself as part of the Statistical Horizons Meeting group.
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)
“Dr. Hayes is a walking encyclopedia of statistical knowledge and he has done an immense amount of work developing tools to make his work accessible to researchers. He is able to communicate his statistical knowledge in a clear manner. His course is essential for researchers (at all levels of training) who plan to implement MMCPA in their own research. I have sincere gratitude for Dr. Hayes for taking time away from his own research in order to translate his knowledge to others.”
Rebecca L. Silton, Loyola University Chicago
“No matter if you are a beginner or an expert, you’ll learn great things from this course. Andy not only teaches the process but he describes the foundations of mediation/moderation. Highly recommended if you want to learn more on med/mod analysis and also want to learn tips and tricks of PROCESS macro.”
Hamed Aghakhani, Dalhousie University
“If you want a course that teaches you mediation, moderation and complex combinations from a ground floor to the 110th floor – this is it. I believe this course holds something for everyone. You will learn quite a bit even if you come to it with just a regression background. This course is tough but rewarding. You can’t get something from nothing and the course delivers. You will leave with new ideas about what to do with your data and even how to think anew about relationships between variables.”
“Very useful course. Highly recommended.”
Lifeng Yang, University of Mississippi
“This is a great way to keep current on mediation and moderation without having to learn MPlus. Everything is done in both SPSS and SAS.”
Dennis Fisher, California State University
“Even though I have been using these techniques in practice, I learned so much from this course that will be applicable to data analysis right away.”
Sarah Martindale, W.G. Hefner VA Medical Center
“Dr. Hayes is extremely knowledgeable, yet explains the material in a way that is easy to comprehend. He uses real data, real examples, and provides all needed materials for the course. The course is applied giving you hands-on experience to practice analyzing data and then goes through the interpretation. I would highly recommend.”
Jennifer Sánchez, University of Texas
“This course was incredibly useful in furthering my understanding of basic regression principles, in addition to Mediation, Moderation and the Conditional Process approach. Dr. Hayes’ ability to make seemingly daunting concepts seem manageable has showed me how PROCESS can help me answer my research questions without feeling like I will misinterpret the data. The use of concrete examples was exceptionally helpful.”
Jamie Cohen, University of Pittsburgh