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Activity Number:
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298
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Type:
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Invited
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Date/Time:
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Tuesday, August 5, 2008 : 2:00 PM to 3:50 PM
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Sponsor:
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ENAR
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| Abstract - #300076 |
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Title:
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A Signed-Rank Test for Clustered Data
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Author(s):
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Somnath Datta*+ and Glenn Satten
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Companies:
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University of Louisville and Centers for Disease Control and Prevention
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Address:
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Dept of Bioinformatics & Biostat, Louisville, KY, 40202,
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Keywords:
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Dependent data ; Paired comparison ; Sign test ; Repeated measures
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Abstract:
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We consider the problem of comparing two outcome measures when the pairs are clustered. Using the general principle of within cluster resampling, we obtain a novel signed rank test for clustered paired data. We show by a simple informative cluster size simulation model that only our test maintains the correct size under a null hypothesis of marginal symmetry compared to four other existing signed rank tests; further, our test has adequate power when cluster size is non-informative. In general, cluster size is informative if the common distribution the difference in each pair within a cluster depends on the cluster size. An application of our method to testing radiation toxicity trend is presented.
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