A U-statistics based approach to sample size planning of two-arm trials with discrete outcome criterion aiming to establish either superiority or noninferiority
In current practice, the most frequently applied approach to the handling of ties in the Mann-Whitney-Wilcoxon (MWW) test is based on the conditional distribution of the sum of mid-ranks, given the observed pattern of ties. Starting from this conditional version of the testing procedure, a sample si...
Gespeichert in:
| 1. Verfasser: | |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
28 February 2017
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| In: |
Statistics in medicine
Year: 2017, Jahrgang: 36, Heft: 5, Pages: 799-812 |
| ISSN: | 1097-0258 |
| DOI: | 10.1002/sim.7183 |
| Online-Zugang: | Verlag, Volltext: http://dx.doi.org/10.1002/sim.7183 Verlag, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/sim.7183 
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| Verfasserangaben: | Stefan Wellek |
MARC
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| 245 | 1 | 2 | |a A U-statistics based approach to sample size planning of two-arm trials with discrete outcome criterion aiming to establish either superiority or noninferiority |c Stefan Wellek |
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| 520 | |a In current practice, the most frequently applied approach to the handling of ties in the Mann-Whitney-Wilcoxon (MWW) test is based on the conditional distribution of the sum of mid-ranks, given the observed pattern of ties. Starting from this conditional version of the testing procedure, a sample size formula was derived and investigated by Zhao et al. (Stat Med 2008). In contrast, the approach we pursue here is a nonconditional one exploiting explicit representations for the variances of and the covariance between the two U-statistics estimators involved in the Mann-Whitney form of the test statistic. The accuracy of both ways of approximating the sample sizes required for attaining a prespecified level of power in the MWW test for superiority with arbitrarily tied data is comparatively evaluated by means of simulation. The key qualitative conclusions to be drawn from these numerical comparisons are as follows: With the sample sizes calculated by means of the respective formula, both versions of the test maintain the level and the prespecified power with about the same degree of accuracy. Despite the equivalence in terms of accuracy, the sample size estimates obtained by means of the new formula are in many cases markedly lower than that calculated for the conditional test. Perhaps, a still more important advantage of the nonconditional approach based on U-statistics is that it can be also adopted for noninferiority trials. Copyright © 2016 John Wiley & Sons, Ltd. | ||
| 650 | 4 | |a asymptotic normality | |
| 650 | 4 | |a conditional test | |
| 650 | 4 | |a nonparametric two-sample problem | |
| 650 | 4 | |a ties | |
| 650 | 4 | |a U-statistics | |
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