Anna Gottard (Florence)
Graphical models for homologous factors
Abstract: Homologous factors are factors measured with the same categorical scale. They are commonly encountered in matched pairs studies, in attitudinal research where subjects’ opinions about some issue are observed under several conditions, or in longitudinal studies that repeatedly observe whether a condition is present at various times. In these cases, it can happen that the contingency table cross classifying the homologous factors shows a special structure, typically captured by symmetry and quasi-symmetry models. In this talk, I will present a class of graphical log linear models having symmetry and quasi-symmetry models as particular cases, and allowing situations of conditional independence and the presence of non-homologous factors. This class of models can be associated with a graph with coloured edges and nodes. (This is partially joint work with G.M. Marchetti and A. Agresti).