Sample size determination in the Mann–Whitney test

Andrzej Kornacki, Andrzej Bochniak, and Agnieszka Kubik-Komar. "Sample size determination in the Mann–Whitney test." Biometrical Letters 54.2 (2017): 175-186. <http://eudml.org/doc/288482>.

@article{AndrzejKornacki2017,
abstract = {This paper discusses the problem of determining the number of observations necessary to apply the nonparametric Mann-Whitney test. We describe the method given by Noether (1987) for determining a sample size which guarantees that the Mann-Whitney test at a given significance level α has a predetermined power 1-β. The presented theory is tested by calculating the empirical power in computer simulations. The paper also raises the issue of the method of rounding the determined sample size to an even number when the sample is divided into two equinumerous subsamples.},
author = {Andrzej Kornacki, Andrzej Bochniak, Agnieszka Kubik-Komar},
journal = {Biometrical Letters},
keywords = {Mann-Whitney test; sample size; empirical power},
language = {eng},
number = {2},
pages = {175-186},
title = {Sample size determination in the Mann–Whitney test},
url = {http://eudml.org/doc/288482},
volume = {54},
year = {2017},
}

TY - JOUR
AU - Andrzej Kornacki
AU - Andrzej Bochniak
AU - Agnieszka Kubik-Komar
TI - Sample size determination in the Mann–Whitney test
JO - Biometrical Letters
PY - 2017
VL - 54
IS - 2
SP - 175
EP - 186
AB - This paper discusses the problem of determining the number of observations necessary to apply the nonparametric Mann-Whitney test. We describe the method given by Noether (1987) for determining a sample size which guarantees that the Mann-Whitney test at a given significance level α has a predetermined power 1-β. The presented theory is tested by calculating the empirical power in computer simulations. The paper also raises the issue of the method of rounding the determined sample size to an even number when the sample is divided into two equinumerous subsamples.
LA - eng
KW - Mann-Whitney test; sample size; empirical power
UR - http://eudml.org/doc/288482
ER -