Categorical and Count Outcome Variables

Abstract

In Chapter 8, longitudinal data analysis with a categorical outcome variable is discussed. The discussion includes simple methods which are mostly based on the change in proportions as well as regression-based methods, such as multinomial logistic mixed model analysis. Inn addition, longitudinal data analysis with a count outcome variable is also discussed. Regarding this, both Poisson GEE analysis and Poisson mixed model analysis can be used. When the count outcome variable suffers from overdispersion, negative binomial GEE analysis and negative binomial mixed model analysis can be used. Both longitudinal Poisson regression and longitudinal mixed model regression give rate ratios as effect estimates and the results of both methods are comparable. All methods in this chapter are accompanied by extensive real-life data examples.