A note on the use of the non-parametric Wilcoxon-Mann-Whitney test in the analysis of medical studies.
Year: 2008
Type: article
Abstract: 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.
Source: Europe PMC (PubMed Central)
Authors: Corinna Kühnast, Markus Neuhäuser
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1952810607