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Permutation tests for mixed paired and two-sample designs

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Abstract

Permutation tests based on previously developed statistics are proposed for the case of mixed paired and two-sample designs. Different weighting schemes of previous tests are explored to understand the strengths and weaknesses of each test. A simulation study compares the power and Type I error rates of the new tests with those previously developed. Rank-based statistics generally performed as well as or better than parametric statistics, particularly for nonnormal distributions.

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Authors and Affiliations

  1. Wake Forest School of Medicine, Winston-Salem, NC, USA

    E. N. Johnson

  2. University of North Carolina at Greensboro, Greensboro, NC, USA

    S. J. Richter

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  1. E. N. Johnson
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  2. S. J. Richter
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Correspondence to S. J. Richter.

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Johnson, E.N., Richter, S.J. Permutation tests for mixed paired and two-sample designs. Comput Stat 37, 739–750 (2022). https://doi.org/10.1007/s00180-021-01137-9

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  • DOI: https://doi.org/10.1007/s00180-021-01137-9

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