A note on the use of the non-parametric Wilcoxon-Mann-Whitney test in the analysis of medical studies.
BACKGROUND
Although non-normal data are widespread in biomedical research, parametric tests unnecessarily predominate in statistical analyses.


METHODS
We surveyed five biomedical journals and - for all studies which contain at least the unpaired t-test or the non-parametric Wilcoxon-Mann-Whitney test - investigated the relationship between the choice of a statistical test and other variables such as type of journal, sample size, randomization, sponsoring etc.


RESULTS
The non-parametric Wilcoxon-Mann-Whitney was used in 30% of the studies. In a multivariable logistic regression the type of journal, the test object, the scale of measurement and the statistical software were significant. The non-parametric test was more common in case of non-continuous data, in high-impact journals, in studies in humans, and when the statistical software is specified, in particular when SPSS was used.
Kühnast
Corinna
C
Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Essen, Germany. imibe@uk-essen.de
Neuhäuser
Markus
M
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