What actually happens when you add a covariate to a regression model? What does it mean to "control for" or "adjust for" a variable? What is the difference between a model with two main effects and a model with a two-way interaction?
A deeper understanding of these questions can make advanced regression concepts much more accessible. Check out my tutorial using a silly dog-related example:
https://saraemilyburke.com/stats/main_effects_vs_interaction.html
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