Seminars
General Departmental Seminar Series
Binary Models for Marginal Independence
Professor Mathias Drton from
the Department of Statistics, University of Chicago
Friday, April 21, 2006
12:00 pm
5235/75 MSC
ABSTRACT 
Loglinear models are a classical tool for the analysis of contingency tables. In particular, the subclass of graphical loglinear models provides a general framework for modelling conditional independences. However, with the exception of special structures, marginal independence hypotheses cannot be accommodated by these traditional models. For example, it is not possible to formulate a model for four variables (A,B,X,Y) such that A is independent of B, and X is independent of Y (and
no other restrictions are imposed). Focusing on binary variables, I will present a new model class that provides a framework for modelling marginal independences in contingency tables. The approach taken is graphical and
based on bidirected graphs, which are in the tradition of path diagrams. In many respects, the resulting models are dual to graphical loglinear models.
(joint work with Thomas Richardson, University of Washington)
