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December 5, 2012
Iterative Scaling for Irregular Patterns of Association
UW Center for Statistics and the Social Sciences

Anna Klimova, UW Statistics

Some patterns of association that naturally appear in, for example, market basket analysis, text recognition, multistage capture-recapture procedures, and others seem irregular if considered from the point of view of conventional log-linear models. Such patterns of association cannot be described using partitions in a contingency table, and thus are lacking the so-called overall effect. The lack of the overall effect is an intrinsic property of a model, and cannot be fixed by a re-parameterization. Models without the overall effect are illustrated using a model of independence between two morphological structures in the Hungarian language. Traditional iterative scaling procedures, used for computing the expected cell counts in contingency tables, do not work for such a model. The algorithm described in this presentation can be used for models with or without the overall effect.

12:30 pm - 1:20 pm
Savery 409
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