Mediation and Moderation
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 and Kristopher Preacher have been among the leading recent contributors to the literature on these methods. They have
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 15 through Friday, July 19 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
A block of guest rooms has been reserved at the Club Quarters Hotel, 1628 Chestnut Street, Philadelphia, PA at a special rate of $116 per night for a Standard room. This location is about a 8 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 STA714. For guaranteed rate and availability, you must reserve your room no later than June 15, 2013.
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.
“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 for 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
“The course presented a broad overview of statistical approaches to moderation and mediation, using primarily OLS methods. The material was clearly presented and offered great resources for application.”
Molly Magill, Brown University
“I would advise individuals not to be intimidated by the course. All levels of statistical knowledge can benefit from the course. Questions are welcomed and the people attending the workshop are very willing to help. The course can teach you things you have never heard of or can just clarify questions you may have.”
Rachael Looney, University of Kentucky
“I think the course is a great supplement to other statistics courses taught in graduate school. All graduate students should take this course to become more competent in mediating and moderating variables.”
Charlene Harris, University of Kentucky
“This is one of the most informative workshops I’ve been to. I’ve learned a lot about the mediation and moderation models and how to analyze and interpret the data. The instructor is extremely knowledgeable about the topic. People from different backgrounds and at different levels may all benefit from this workshop. The process tools provided by the instructor are easy to use. Excellent information! Excellent instructor! Excellent workshop!”
Cathy Qi, University of New Mexico
“I teach multivariable statistics so I was unsure how much benefit I would derive from the course. The course was excellent, ensuring understanding for people new to thinking about these analytical approaches while extending understanding of those intimately familiar with these techniques. The Johnson-Neyman results are an amazing tool for probing interactions (much easier than the hand or SPSS computations I used to do). If you understand PROCESS then you can extend its capabilities to go beyond those models listed in the documentation. Great course, super tools.”
Stan Gully, Rutgers University
“The course helped to revisit the fundamentals of moderation and mediation in the context of how the latest improved methods can be applied to conduct tests exploring the “why” and “when” questions in research. Dr. Hayes did a great job in responding to questions which helped to further clarify confusion on those topics. Also, I appreciated the distribution of relevant materials such as article and data files and the PROCESS software.”
Rajash Ghosh, Drexel Univeristy
“This course covers all of the latest methods for mediation and moderation. Best part was specific instructions on how to use Dr. Hayes’ PROCESS program. A lot of information packed into two days. Very worthwhile! Taught by leader in the field.”
Cindy Smith, Virginia Tech
“This was an excellent class, both as a refresher of what should be basic knowledge (but may be lost or hazy for many) and also a good introduction to PROCESS. I would attend (if possible due to scheduling conflicts) a second workshop that went to a deeper level on PROCESS and other more complex issues.”
Brian Lickel, UMass Amherst