1964
DOI: 10.2307/1266041
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Multiple Comparisons Using Rank Sums

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Cited by 1,395 publications
(1,222 citation statements)
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“…Pairwise comparisons, using Dunn’s test for multiple comparisons with one control, were made with dunn.test.control function from the PMCMR package (adjusted p ‐value <0.05; Dunn, 1964). …”
Section: Methodsmentioning
confidence: 99%
“…Pairwise comparisons, using Dunn’s test for multiple comparisons with one control, were made with dunn.test.control function from the PMCMR package (adjusted p ‐value <0.05; Dunn, 1964). …”
Section: Methodsmentioning
confidence: 99%
“…Nonetheless, a KruskalWallis H test was also conducted and showed that motivation to learn more programming was different for the three heteroskedastic groups χ 2 (2) = 68.58, p < .001. Pairwise analyses were performed using a Dunn rank sum test (Dunn 1964) with a Bonferroni adjustment. Results show that there was no significant difference in effects (z = .65, p = .77) between Me and Together, but there were significant differences in effects (z = 5.60, p < .001; z = 8.31, p < .001) between these two categories and Others.…”
Section: Motivationmentioning
confidence: 99%
“…We used multivariate analysis techniques such as principal component analysis (PCA) and one-way pairwise analysis of similarity (ANOSIM; Hammer et al 2004) to identify distinct groups or patterns in grass species composition of our sample plots. We applied a Kruskal-Wallis test and a multiple comparison post-hoc test after Dunn (1964) for differences of the most common grass species growing inside and outside of the Roan enclosure beneath and outside canopies. …”
Section: Statistical Analysesmentioning
confidence: 99%