p-Value for two-Sample Linear Rank Tests Using Permutation Simulations and the Normal Approximation Method |
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Authors: | Alya O. Al Mutairi Heng Chin Low |
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Affiliation: | School of Mathematical Sciences, Universiti Sains Malaysia, Penang, Malaysia |
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Abstract: | Test statistics from the class of two-sample linear rank tests are commonly used to compare a treatment group with a control group. Two independent random samples of sizes m and n are drawn from two populations. As a result, N = m + n observations in total are obtained. The aim is to test the null hypothesis of identical distributions. The alternative hypothesis is that the populations are of the same form but with a different measure of central tendency. This article examines mid p-values from the null permutation distributions of tests based on the class of two-sample linear rank statistics. The results obtained indicate that normal approximation-based computations are very close to the permutation simulations, and they provide p-values that are close to the exact mid p-values for all practical purposes. |
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Keywords: | Linear rank test Mid p-value Normal approximation Permutation distribution |
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