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Activity Number: 477
Type: Contributed
Date/Time: Wednesday, August 9, 2006 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #307311
Title: Dimensionality Reduction of High-Dimensional Tables
Author(s): Siamak Noorbaloochi*+ and David Nelson and Joe Grill
Companies: VAMC, University of Minnesota and VAMC, University of Minnesota and VAMC, Minneapolis
Address: One Veterans Drive, Minneapolis, MN, 55417,
Keywords: collapsibility ; dimensionality reduction
Abstract:

Collapsibility is defined as equivalence of inferences based on a marginal table and its corresponding joint model. The marginalization is defined with respect to a set of variables. We present a method to extend the notion of marginalization with respect to partitioning the cells of the joint model such that collapsibility remains valid. Application of the method in high-dimensional tables with multinomial counts is investigated and a method for estimating the cell probabilities for sparse tables is introduced.

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