MARGINAL MODELING OF CATEGORICAL-DATA FROM CROSSOVER EXPERIMENTS

Marginal models provide a useful framework for the analysis of crossov er experiments when the response variable is categorical. In this pape r we use the three-treatment, three-period crossover experiment with a binary outcome variable to demonstrate how marginal models can be use d to perform a likelihood-based analysis of multiple-period crossover experiments. Other designs are discussed in less detail. Maximum likel ihood estimation is performed using a constraint equation specificatio n of the marginal model. Data from a crossover trial comparing treatme nts for primary dysmenorrhoea are used to demonstrate the utility of m arginal models in analysing crossover data.