Mediation and Moderation

Session 2: June 12 – 16, 2017
Albuquerque, NM
Embassy Suites by Hilton

Payment Options
Per Course Qty
Facultyshow details + $1,795.00 (USD)  
Studentshow details + $1,095.00 (USD)  

Statistics Course Objectives

The five-day training institute on Mediation and Moderation will enable participants to:

  • Estimate, test, and interpret mediated (i.e., indirect) effects using OLS regression and other advanced techniques (e.g. SEM).
  • Estimate, test, and interpret moderated (i.e., interaction) effects using OLS regression and other advanced techniques (e.g. SEM).
  • Combine mediation and moderation models to test conditional indirect effects.
  • Use freely-available R software to test these models.


Course Syllabus

Summer Stats Camp 2017: Mediation Moderation
9:00-10:45 Welcome & Introduction to R
10:45-11:00 Snack and Refreshment Break
11:00-12:30 Review of regression
12:30-1:30 Lunch
1:30-3:15 Introduction to mediation
3:15-3:30 Snack and Refreshment Break
3:30-5:00 Computing, testing and interpreting mediation in regression
9:00-10:45 SEM refresher & Introduction to lavaan
10:45-11:00 Snack and Refreshment Break
11:00-12:30 Latent variable mediation
12:30-1:30 Lunch
1:30-3:15 Mediation with four or more variables
3:15-3:30 Snack and Refreshment Break
3:30-5:00 Advanced topics in mediation: logistic regression, multilevel modeling
9:00-10:45 Longitudinal mediation
10:45-11:00 Snack and Refreshment Break
11:00-12:30 Introduction to moderation
12:30-1:30 Lunch
1:30-3:15 Computing moderation in regression
3:15-3:30 Snack and Refreshment Break
3:30-5:00 Graphing and interpreting moderation in regression / Individual Consultations
9:00-10:45 Continue Graphing and interpreting
10:45-11:00 Snack and Refreshment Break
11:00-12:30 Polynomial relationships
12:30-1:30 Lunch
1:30-3:15 Advance topics in moderation: multilevel modeling, SEM
3:15-3:30 Snack and Refreshment Break
3:30-5:00 Continue Advanced topics / Individual Consultations
9:00-10:45 Combining mediation and moderation
10:45-11:00 Snack and Refreshment Break
11:00-12:30 Testing and interpreting conditional indirect effects
12:30-1:30 Lunch
1:30-~3:30 Individual Consultations

Why Should You Attend?

  • Get 1 on 1 Consultation With Instructor
  • Professional Networking
  • Peer Socializing
  • Collaboration
  • All Course Resources
  • Breakfast (Embassy guests), Lunches, & Snacks Daily

Statistical Methods Course Description

Overview: In many scientific fields research questions have become more complex. Researchers are no longer simply interested in if one variable (X) is related to another (Y). Instead, research questions such as: “Why is X related to Y?” and “When is X related to Y?” abound. This course addresses methods to test why two variables are related (mediation) and when two variables are related (moderation).

Topics include:

• Classic and contemporary approaches
• Estimating moderation
• Mediation effects
• Path analysis
• Indirect and direct effects
• Testing intervening variable effects
• Probing and plotting interactions
• Combining moderation and mediation

Instructor: Kyle Lang

Kyle is a postdoctoral research associate at the Texas Tech Institute for Measurement, Methodology, Analysis, and Policy. He earned his Ph.D. in quantitative psychology from the University of Kansas in 2015. Kyle’s research focuses on missing data analysis with a particukyle_1lar emphasis on developing and evaluating multiple imputation techniques for use with difficult missing data problems (e.g., imputing categorical data, imputation in large datasets, high-dimensional imputation models). He also has extensive experience applying cutting edge statistical methods such as those for testing mediation and moderation to substantive research questions in fields such as psychology, education, social work, and political science as both a statistical consultant and a collaborating researcher. Dr. Lang has been involved in Stats Camp every year since 2009. He has provided general statistical consulting for all of the courses offered and given numerous guest lectures on topics such as mixture modeling, regularized regression modeling, and Bayesian structural equation modeling.


Software and Computer Support

All examples will be presented in the R Statistical Programing language. R is an open-source software package for statistical analysis that can be downloaded for free at Please install R on your personal computer before the first class meeting. Also, R’s built-in text editor is pretty terrible, so please download one of the following freely-available text editors as well:

If you are using Windows or Mac, Vincent Goulet provides repackaged version of Emacs that are bundled into auto-magical executables that already contain ESS. His packages are freely-available at I recommend using Dr. Goulet’s bundles if you want to install Emacs on a Windows or Mac machine.

Course Audience

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 freely-available R software. Participants should have a good working knowledge of the principles and practice of multiple regression and elementary statistical inference.

Course Files

Below are links to course files for those who enrolled in the course. Please download these files onto your computer before the first day of the course. The files are password protected to respect the intellectual property rights of the instructors. By using your login information you agree not to share your login information or the content protected by it.

After May 1st: Click Here to Access Mediation and Moderation Course Files

Mediation and Moderation Seminar