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Activity Number:
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275
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Type:
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Contributed
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Date/Time:
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Tuesday, August 4, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #303737 |
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Title:
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The Split Sample Permutation t-Tests
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Author(s):
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Shunpu Zhang*+
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Companies:
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University of Nebraska-Lincoln
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Address:
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Department of Statistics, Lincoln, NE, 68583-0963,
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Keywords:
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Exact test ; exchangeability ; permutation tests
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Abstract:
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Without the exchangeability assumption, permutation tests for comparing two population means do not provide exact control of the probability of making a Type I error. Another drawback of permutation tests is that it cannot be used to test hypothesis about one population. In this paper, we propose a new type of permutation tests for testing the difference between two population means: the split sample permutation t-tests. We show that the split sample permutation t-tests do not require the exchangeability assumption, are asymptotically exact and can be easily extended to testing hypothesis about one population. Extensive simulations were carried out to evaluate the performance of two specific split sample permutation t-tests: the split in the middle permutation t-test and the split in the end permutation t-test.
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