An interaction between two predictor variables means that one predictor variable affects a third variable differently at different values of the other predictor.
How you understand that interaction depends on many things, including:
- Whether one, or both, of the predictor variables is categorical or numerical
- How each of those variables is coded (specifically, whether each categorical variable is dummy or effect coded and whether numerical variables are centered)
- Whether it’s a two-way or three-way interaction
- Whether there is a directionality to the interaction (moderation) or not
Sometimes you need to get pretty sophisticated in your coding, in the output you ask for, and in writing out regression equations.
In this webinar, we’ll examine how to put together and break apart output to understand what your interaction is telling you.
Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.
About the Instructor
Karen Grace-Martin helps statistics practitioners gain an intuitive understanding of how statistics is applied to real data in research studies.
She has guided and trained researchers through their statistical analysis for over 15 years as a statistical consultant at Cornell University and through The Analysis Factor. She has master’s degrees in both applied statistics and social psychology and is an expert in SPSS and SAS.
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