ABSTRACT
At the time of the first edition of this book, Jones and Kenward (1989), the methodology available for binary and categorical cross-over data was rather limited and amounted largely to a somewhat ad hoc collection of tests based on simple contingency tables. An exception to this was the Mainland-Gart test for direct treatment effect from a two-period two-treatment trial with binary data described in Section 2.13. Although introduced there in the context of a contingency table, Gart (1969) gave a derivation for this in terms of a logistic regression model and Altham (1971) considered the same model from a Bayesian viewpoint. Since the time of the first edition, interest in the analysis of repeated and correlated categorical data has grown enormously and since the early 1990s there has been available a much wider range of methodology; see, for example, Chapters 7-11 of Diggle et al. (2002) and Molenberghs and Verbeke (2000). These changes were reflected in the second edition of this book, and only minor developments of an evolutionary nature have occurred since, mainly computational. These have been incorporated in this chapter.
