Mediation, Moderation, and Conditional Process Analysis - Online Course
A 3-Day Livestream Seminar Taught by
Amanda Montoya10:00am-12:30pm (convert to your local time)
1:30pm-3:30pm
Mediation and moderation analyses are widely used in many different fields. Mediation analysis tests hypotheses about mechanisms or processes by which effects occur. Moderation analysis examines questions of contingencies (e.g., for whom, or when), commonly described as an “interaction.”
Moderation and mediation can be combined analytically to investigate questions of contingencies in mechanisms. This is called conditional process analysis or moderated mediation. These statistical approaches help researchers generate theoretical models of how and when, which can then be statistically evaluated using observed data.
This course covers methods for statistical mediation, moderation, and conditional process analysis using ordinary least squares (OLS) regression and the PROCESS macro, available for SPSS, SAS, and R.
Starting April 3, this seminar will be presented as a 3-day synchronous, livestream workshop via Zoom. Each day will feature two lecture sessions with hands-on exercises, separated by a 1-hour break. Live attendance is recommended for the best experience. But if you can’t join in real time, recordings will be available within 24 hours and can be accessed for four weeks after the seminar.
Closed captioning is available for all live and recorded sessions. Captions can be translated to a variety of languages including Spanish, Korean, and Italian. For more information, click here.
ECTS Equivalent Points: 1
More details about the course content
By the end of this class you will be able to:
-
- Define and calculate direct, indirect, and total effects in mediation models.
- Estimate and conduct inference on indirect effects in single mediator models.
- Generalize previous concepts to multiple mediator models.
- Estimate models with moderation and conditional effects.
- Probe and visualize interactions.
- Define conditional process analysis (AKA “moderated mediation.”)
- Quantify and conduct inference on conditional indirect effects.
- Test a moderated mediation hypothesis and compare conditional indirect effects.
This introductory seminar focuses primarily on research designs that are experimental or cross-sectional in nature with continuous outcomes. It does not cover complex models involving dichotomous outcomes, latent variables, models with repeated measures, nested data (i.e., multilevel models), or the use of structural equation modeling.
By the end of this class you will be able to:
-
- Define and calculate direct, indirect, and total effects in mediation models.
- Estimate and conduct inference on indirect effects in single mediator models.
- Generalize previous concepts to multiple mediator models.
- Estimate models with moderation and conditional effects.
- Probe and visualize interactions.
- Define conditional process analysis (AKA “moderated mediation.”)
- Quantify and conduct inference on conditional indirect effects.
- Test a moderated mediation hypothesis and compare conditional indirect effects.
This introductory seminar focuses primarily on research designs that are experimental or cross-sectional in nature with continuous outcomes. It does not cover complex models involving dichotomous outcomes, latent variables, models with repeated measures, nested data (i.e., multilevel models), or the use of structural equation modeling.
Computing
Because this is a hands-on course, you are strongly encouraged to use your own computer (Mac or Windows) with one of the following packages installed: SPSS Statistics (version 23 or later), SAS (release 9.2 or later, with PROC IML installed), or R (v3.6 or later; base R; no special packages are needed).
You can choose which statistics package you want to use while working through the course material. You should have good familiarity with the use of SPSS, SAS, or R, including opening and executing data files and programs. You are also encouraged to have your own data available to apply what you’ve learned.
There is now a free version of SAS, called SAS OnDemand for Academics, that is available to anyone.
If you’d like to use R for this course but don’t yet have much experience with that package, here are some excellent online resources for building your R skills.
Because this is a hands-on course, you are strongly encouraged to use your own computer (Mac or Windows) with one of the following packages installed: SPSS Statistics (version 23 or later), SAS (release 9.2 or later, with PROC IML installed), or R (v3.6 or later; base R; no special packages are needed).
You can choose which statistics package you want to use while working through the course material. You should have good familiarity with the use of SPSS, SAS, or R, including opening and executing data files and programs. You are also encouraged to have your own data available to apply what you’ve learned.
There is now a free version of SAS, called SAS OnDemand for Academics, that is available to anyone.
If you’d like to use R for this course but don’t yet have much experience with that package, here are some excellent online resources for building your R skills.
Who should register?
This seminar 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, SAS and R.
You 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. You should be familiar with linear regression and the basics of OLS regression in one of the following software packages: SPSS, SAS, or R.
This seminar 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, SAS and R.
You 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. You should be familiar with linear regression and the basics of OLS regression in one of the following software packages: SPSS, SAS, or R.
Seminar outline
Day 1: Introduction to mediation analysis
-
- Review of basic OLS regression concepts
- Introduction to path analysis
- Estimation and inference for total, direct, and indirect effects
- Assumptions and causality in mediation analysis
- Writing clear and compelling mediation results
Day 2: Introduction to moderation analysis
-
- Estimation of models with a single moderator
- Symmetry of moderation models
- Estimation of and inference in moderation parameters
- Estimation of and inference for conditional effects
- Probing and visualizing interactions
- Writing clear and compelling mediation results
Day 3: Conditional process analysis
-
- Advantages of combining mediation and moderation
- Path analysis for conditional process models with a single mediator and single moderator
- Estimation of and inference for conditional indirect effects
- Estimation of and inference for the index of moderated mediation
- Comparing tests of moderated mediation to conditional indirect effects
- Writing clear and compelling conditional process analysis results
Day 1: Introduction to mediation analysis
-
- Review of basic OLS regression concepts
- Introduction to path analysis
- Estimation and inference for total, direct, and indirect effects
- Assumptions and causality in mediation analysis
- Writing clear and compelling mediation results
Day 2: Introduction to moderation analysis
-
- Estimation of models with a single moderator
- Symmetry of moderation models
- Estimation of and inference in moderation parameters
- Estimation of and inference for conditional effects
- Probing and visualizing interactions
- Writing clear and compelling mediation results
Day 3: Conditional process analysis
-
- Advantages of combining mediation and moderation
- Path analysis for conditional process models with a single mediator and single moderator
- Estimation of and inference for conditional indirect effects
- Estimation of and inference for the index of moderated mediation
- Comparing tests of moderated mediation to conditional indirect effects
- Writing clear and compelling conditional process analysis results
Payment information
The fee of $995 USD includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.
The fee of $995 USD includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.