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Abstract Details
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Activity Number:
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359
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Type:
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Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #302212 |
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Title:
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A Bootstrap Approach for Testing Marginal Independence Between Two Categorical Variables when Subjects Have Repeated Responses
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Author(s):
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Rhonda J. Rosychuk*+ and Christina Alloway and Amanda S. Newton
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Companies:
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University of Alberta and University of Alberta
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Address:
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, , ,
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Keywords:
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non-parametric bootstrap ;
contingency table ;
marginal independence ;
correlated data ;
categorical data
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Abstract:
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Two-way contingency tables are used to classify subjects by two categorical variables. To assess independence in these tables, the Pearson chi-square test or Fisher's exact test are typically used. These tests assume that each subject contributes at most one count to only one table cell (e.g., sex versus blood type). In other situations, each subject may have more than one count contributing to the table. One may wish to test independence, adjusting for the within-subject correlation. We provide a simple non-parametric bootstrap approach and assess its performance through simulation studies. The method is illustrated on subjects with multiple mental health presentations to Emergency Departments.
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