Generalized Linear Mixed Models (GLMM)
You've probably heard of GLMM (generalized linear mixed models) -- or maybe you've heard of one of its popular software implementations, such as glmer or GLIMMIX.

Are you wondering if this is something that you need to use when analyzing your data?

Join us on Thursday, April 26th at 3pm (EST) for this free webinar to help you reach the next level of your statistics expertise. 

Important: Attendees should feel comfortable with linear models, and it may be helpful to have some background in generalized linear models and/or linear mixed effects models. This webinar is not software specific.

Covered in this webinar: 


The type of outcome variables that may require GLMM


The structure of data that may require GLMM


The assumptions of GLMM


A basic outline of the analytical method

Examples of the practical results obtained from GLMM
About the Instructor
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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