The Hitchhiker's Guide to Mixed Models

Linear Mixed Models are, literally, one of my favourite techniques. When I first started learning Mixed Models during my last year of PhD (2017), they were not at all common in my field (Psychology), but their use quickly spread and publications and resources multiplied.

However, a strange confusion started to occur: mixed models became an umbrella term for a couple of other methods (i.e., so-called mixed ANOVA and GEE) that - despite being designed to address similar data designs - do not contain the very feature that defines the mixed model - the random effect.

Last year, my colleague Mary Agyapong and I organised a workshop for introducing and demonstrating Linear Mixed Models in R and SPSS. During this introductory presentation, I went over the Linear Mixed Models confusion, random effects, and a few other things (also see the slides below). In the next few weeks, I will also publish R and SPSS demonstrations.

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Slides