Mediation and Moderation

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Date/Time
Date(s) - 10/09/2015 - 10/10/2015
4:24 pm

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Start Date: 10/9/2015

End Date: 10/10/2015

Location:

University of Limerick

Castletroy, Co.

Limerick, Ireland

Website: http://statisticalhorizons.com/seminars/public-seminars/mmlimerick

Contact: 610-642-1941

Taught by Andrew Hayes, Ph.D. 

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 one of the leading contributors to the literature on these methods. He has studied and written about methods of estimating mediation and moderation effects and developed software tools for SPSS and SAS that greatly ease the computational burdens on the researcher.   

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.

 

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