Event Phone: 1-610-715-0115

Cancellation Policy: If you cancel your registration at least two weeks before the course is scheduled to begin, you are entitled to a full refund (minus a processing fee of $50).

In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.

A 5-Day Seminar 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 among the leading recent contributors to the literature on these methods. He has developed methods and easy-to-use tools for estimating mediation and moderation effects that can be used with SAS and SPSS.

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 a mechanism can be contingent and how to determine statistically whether an indirect effect is moderated.

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). Students in this course will receive an early beta release of PROCESS v3, before it is released to the public in late 2017 or early 2018.

Compared to the two-day introductory version of the seminar, previously offered by Statistical Horizons, the five day seminar will go into further depth with more examples and touch on a greater number of topics.

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.