Centering variables is common practice in some areas, and rarely seen in others. That being the case, it isn’t always clear what are the reasons for centering variables. 
Is it only a matter of preference, or does centering variables help with analysis and interpretation?
In this training, we discuss what centering is (so don’t worry if you haven’t heard of it before). We talk about the reasons for centering, and see examples ranging from the very basic (simple linear regression) to the more complex (models with interactions and multi-level data).
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
Kim is a Statistically Speaking mentor and workshop instructor for The Analysis Factor. She is also owner/lead consultant at K.R. Love Quantitative Consulting and Collaboration.
She has worked as a statistical consultant and collaborator in multiple professional roles, most recently as the associate director of the University of Georgia Statistical Consulting Center.
Kim has more than a decade of professional and academic experience in the fields of regression and linear models, categorical data, generalized linear models, mixed effects models, nonlinear models, repeated measures, and experimental design. She has a B.A. in mathematics from the University of Virginia, and an M.S. and PhD in statistics from Virginia Tech.
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