Indeed, using those defaults with factorial experiments can lead researchers to draw erroneous conclusions from their data. It is unexpectedly complicated, and the defaults provided in R turn out to be wholly inappropriate for factorial experiments. Many experimentalists who are trying to make the leap from ANOVA to linear mixed-effects models (LMEMs) in R struggle with the coding of categorical predictors. The mutate() / if_else() / case_when() approach for a three-level factor.
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