Permutation tests for mixed paired and two-sample designs

E. N. Johnson () and S. J. Richter ()
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E. N. Johnson: Wake Forest School of Medicine
S. J. Richter: University of North Carolina at Greensboro

Computational Statistics, 2022, vol. 37, issue 2, No 9, 739-750

Abstract: 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.

Keywords: Paired design; Missing data; Permutation test; Ranks (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s00180-021-01137-9

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