One of my datasets requires mixed models linear regression analyses, so I was reading up on exactly how the analyses are done and what they mean. Found this useful-looking tutorial that walks through several examples of the mixed effects, as well as how to do it in R.
Here’s a graph of individual subjects, grouped by gender, and the distribution of their voice pitch.
To take into account the individual variation in each subject’s voice pitch, run pitch ~ politeness + sex + (1 | subject) + error, where (1 | subject) indicates the assumption that the intercept is different for each subject.
PS. I love box plots!