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Abstract Details
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Activity Number:
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182
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Government Statistics
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| Abstract - #304637 |
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Title:
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Tests for Homogeneity of Multinomial Proportions for Sparse Data
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Author(s):
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Martin Klein*+ and Peter Linton and Bimal Sinha
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Companies:
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and U.S. Census Bureau and University of Maryland Baltimore County
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Address:
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8369 Tamar Drive, Columbia, MD, 21045, United States
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Keywords:
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Categorical data ;
Homogeneity testing ;
Monte Carlo methods ;
Simulation ;
Sparse data
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Abstract:
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It is well known that the standard chi-squared test for testing the homogeneity of multinomial proportions performs poorly in terms of maintaining the stipulated Type I error for sparse data. We will review several tests which have been proposed to remedy this situation, and also provide some new tests. A comparison of all the tests based on extensive simulations will be presented. As an application, we consider tabular decennial census data at the block or tract level, which can be quite sparse. This application arises from a larger goal of building a model that is suitable for generating a synthetic version of the decennial census microdata.
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