Although non-normal data are widespread in biomedical research, parametric tests unnecessarily, predominate in statistical analyses. Five biomedical journals were surveyed and for all studies which contain at least the unpaired t-test or the non-parametric Wilcoxon and Mann-Whitney U test - investigated the relationship between the choice of a statistical test and other variables such as type of journal, sample size, randomization, sponsoring etc. The non-parametric Wilcoxon and Mann-Whitney U were 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.
Key words: Wilcoxon and Mann-Whitney U test, univariate analyses, non-parametric test, logistic regression.
Copyright © 2021 Author(s) retain the copyright of this article.
This article is published under the terms of the Creative Commons Attribution License 4.0