Dale Barr (@datacmdr) recently had a nice blog post about coding categorical predictors, which reminded me to share my thoughts about multiple pairwise comparisons for categorical predictors in growth curve analysis. As Dale pointed out in his post, the R default is to treat the reference level of a factor as a baseline and to estimate parameters for each of the remaining levels. This will give pairwise comparisons for each of the other levels with the baseline, but not among those other levels. Here's a simple example using the

`ChickWeight`

data set (part of the `datasets`

package). As a reminder, this data set is from an experiment on the effect of diet on early growth of chicks. There were 50 chicks, each fed one of 4 diets, and their weights were measured up to 12 times over the first 3 weeks after they were born.