2017
DOI: 10.1080/03610918.2017.1353613
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Comparison of nonparametric analysis of variance methods: A vote for van der Waerden

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Cited by 34 publications
(28 citation statements)
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“…Demographic, clinical, and lipidomic data are presented as median and interquartile range. Because lipidomic data did not fulfil the assumptions of normality (Shapiro–Wilk test) and homoscedasticity (F test), we applied the Van der Waerden test for between-subjects analysis of variance 56 . Subsequently, Van der Waerden post-hoc tests were performed for pairwise multiple comparisons.…”
Section: Methodsmentioning
confidence: 99%
“…Demographic, clinical, and lipidomic data are presented as median and interquartile range. Because lipidomic data did not fulfil the assumptions of normality (Shapiro–Wilk test) and homoscedasticity (F test), we applied the Van der Waerden test for between-subjects analysis of variance 56 . Subsequently, Van der Waerden post-hoc tests were performed for pairwise multiple comparisons.…”
Section: Methodsmentioning
confidence: 99%
“…However, due to the nature of the scale and its susceptibility to floor effects, this was to be expected and transformations that were conducted accordingly had little influence on the pattern of results. Although non-parametric analyses are generally more suitable for use with non-normally distributed data, nonnormal distributions do not violate the parametric F-test and both parametric and nonparametric tests are equally susceptible to problems associated with heterogeneity of variances (Luepsen, 2017).…”
Section: Discussionmentioning
confidence: 99%
“…Model checking for variance homogeneity were based on the Levene test. For a sound discussion about nonparametric analysis of variance methods see for example [48]. The 30 lipids with the smallest p-value of the F-test were chosen to perform a principle component analysis on the centered and to unit variance scaled data.…”
Section: Methodsmentioning
confidence: 99%