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Non-i.i.d. Generalizations of the Matched-Pairs t-Test
Abstract
This paper generalizes the matched-pairs t-test for difference in mean to nonidentically distributed data. A variety of conditions generate a Central Limit Theorem, which makes this test asymptotically standard normal, while the finite-sample distribution is analytically unobtainable. Initially, independence is assumed to show that this test can be constructed when the differences are not identically distributed. Independence also assures the consistency of the bootstrap and wild bootstrap for estimating significance levels. Dependence is introduced using the Martingale Central Limit Theorem, near epoch dependence and mixing conditions. The test is then applied to biological and population estimates data.
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Page Last Revised - September 10, 2024
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