ABSTRACT
The focus of this chapter is on models designed specifically for scenarios in which the outcome of interest is either categorical or count in nature, and the data have been collected in a multilevel framework. Chapter organization will mirror that of Chapter 7, beginning with a description of fitting logistic regression for dichotomous data, followed by models for ordinal and nominal dependent variables, and concluding with models for frequency count data that fit the Poisson distribution, and for the case of overdispersed counts. Given that the previous chapter provided the relevant mathematical underpinnings for these various models in the single-level case, and Chapter 2 introduced some of the theory underlying multilevel models, the current chapter will focus almost exclusively on the application of the R software package to fit these models, and on the interpretation of the resultant output.
