Sentence examples for multiple comparison analyses from inspiring English sources

Results of the multiple comparison analyses reveal significant differences (p < .001) between the countries on almost all process scales.

However, multiple comparison analyses revealed that these effects seemed to be due to the difference in the experimental experience rather than the presence or absence of thinning.

We ran multiple comparison analyses using post hoc Dunn's pairwise tests with Bonferroni corrections for the Kruskal Wallis H test; the x 2 test statistic (H 2) was adopted to calculate the effect size (w 2  = H 2 /(n − 1)) to avoid the inflation of overall type I error.

The country comparisons reveal significant differences between the countries regarding the participants' ratings of the importance of the different contributing factors (p < .001), whereby the multiple comparison analyses reveal least differences between the participants in the countries regarding the value of the course contents and the participant participant relations (Table 5).

In all statistical tests multiple comparison analyses, post hoc Bonferroni tests were performed for all pairwise comparisons.

Another useful feature of the results tab is the ability to perform Bayesian multiple comparison analyses.

Table 1 show the results of the multiple comparisons analyses.

All multiple-comparison analyses were followed by post hoc Bonferroni's correction.

These differences cannot be considered statistically significant in multiple-comparison analyses, and do not seem to have a relevant clinical impact.

No adjustment was made for multiple comparisons as analyses were exploratory; exact p-values are shown instead.

To limit spurious findings due to multiple comparisons, correlation analyses of PSG variables were limited to those measures significantly different between groups.