Large tables

Abstract

The traditional exploration of large contingency tables leads to multiple comparisons with the inherent generation of chance associations. To allow for this, a simple empirical Bayesian approach is used here to derive estimates of association 'shrunk' towards a global mean. Estimates are displayed on ordered normal plots, to allow visual detection of outliers, with the addition of 'guide rails', derived from simulation, to facilitate their detection. The methods, and the interpretation of results, are illustrated using a large table of occupations for cancer registrations in England and Wales for 1971-90.