We consider the statistical problem of analyzing the association between two categorical variables from cross-classified data. The focus is put on measures which enable one to study the possible dependencies at a local level and to assess whether the data support some more or less strong association model. Statistical inference is envisaged using an imprecise Dirichlet model; this model answers several difficulties of frequentist and Bayesian methods.
Keywords. Contingency Tables, Association, Logical model, Directional association model, Statistical inference, Upper and lower probabilities, IDM, Prior ignorance, Bayesian inference.
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Authors addresses:
Laboratoire de Psychologie Environnementale
Universite Paris 5
71 avenue Edouard Vaillant
92774 - Boulogne-Billancourt Cedex
E-mail addresses:
| Jean-Marc Bernard | jmbernard@psycho.univ-paris5.fr |