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American Journal of Applied Mathematics and Statistics. 2013, 1(5), 99-102
DOI: 10.12691/AJAMS-1-5-4
Original Research

Robustness and Power of the Kornbrot Rank Difference, Signed Ranks, and Dependent Samples T-test

Norman N. Haidous1, and Shlomo S. Sawilowsky1

1Department of Evaluation and Research, Wayne State University, Detroit, USA

Pub. Date: October 22, 2013

Cite this paper

Norman N. Haidous and Shlomo S. Sawilowsky. Robustness and Power of the Kornbrot Rank Difference, Signed Ranks, and Dependent Samples T-test. American Journal of Applied Mathematics and Statistics. 2013; 1(5):99-102. doi: 10.12691/AJAMS-1-5-4

Abstract

The purpose of the study was to compare the power and accuracy of the Kornbrot rank difference test to classical parametric and nonparametric alternatives when the assumption of normality is not met, the data are ordinal, and the sample size is small. Although the procedure is robust, there was no evidence the rank difference test had power advantages over Wilcoxon Signed-Ranks test.

Keywords

nonparametric statistics, power, rank tests, Monte Carlo simulations

Copyright

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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