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Activity Number:
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526
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Type:
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Invited
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Date/Time:
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Thursday, August 2, 2007 : 10:30 AM to 12:20 PM
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Sponsor:
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ASA Interest Group on Statistical Learning and Data Mining
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| Abstract - #308015 |
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Title:
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Screening for Monotone Association
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Author(s):
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Joseph S. Verducci*+
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Companies:
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The Ohio State University
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Address:
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Dept. of Statistics, 404 Cockins Hall, Columbus, OH, 43210,
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Keywords:
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Kendall's tau ; Ulam metric ; non-parametric ; discovery ; false negatives
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Abstract:
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General procedures search through many pairs of variables that have been measured on a common sample, identifying those that are likely to have a structural relationship on some subset of the sample. An unusual aspect considered here is that a subsample is being screened along with the variable-pairs. This is motivated by as example where different subsets of cancer cell-lines may show different types of association between the biological activity and microRNA expression. Several statistical approaches include counting concordances, transforming to a location problem, gradient searching and expanding longest monotone sequence algorithms. All of these behave differently depending on the nature of the association, but for all methods the association must be quite strong to have much chance at correctly identifying the subsample of interest.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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