Sentence examples for multiple comparison error from inspiring English sources

Multiple comparison error was controlled by a false discovery rate (FDR) transformation [ 93].

Additionally, the inverse association may be false positives due to multiple comparison error.

Bar charts representing the relative abundance at the phylum, class and genus levels of each group at the different sampling times were generated for visualization of population structure and relative abundances were compared at the different sampling times by the Steel-Dwass test controlling for multiple comparison error.

The test was run with 100 permutations and gene selection was corrected for multiple comparison errors using a pfp (percentage of false prediction) < 0.05.

In agreement with an earlier study on mice [ 19], sham-operated animals did not show significant changes in gene expression accompanying the early response to PHx that could not be accounted for by multiple comparison errors or animal-to-animal variability and there was no overlap with the differentially expressed genes detected after PHx.

For elimination of multiple comparisons error the false discovery rate (FDR) correction according to Benjamini and Hochberg (2000) was used.

The Mann-Whitney U test was used to compare quantitative variables between two groups of observations, and the Bonferroni correction was applied to avoid multiple comparisons error (PB) (for example, to compare number of CCR5+, CCR6+, CCR7+, CCR8+, and CCR9+ cells in the SF versus the PB compartment).

We confirm that each reported cluster of activation was corrected for multiple comparisons (familywise error correction) within a priori regions of interest (i.e. small volume correction, SVC).

After applying Bonferroni correction to adjust for errors of multiple comparisons (type 1 error), no significant deviations remained.

Statistical analysis was performed by students t-test or by ANOVA followed by the Tukey's multiple comparison test defining different error probabilities as significant (* p≤0.05), (** p≤0.01), (*** p≤0.001).

To reduce the risk of type-I error (multiple comparison), a Tukey's HSD (honestly significant difference) test was applied in cases of statistically significant values.