Bonferroni method

Bon·fer·ro·ni meth·od

(bōn-fer-rō'nē meth'ŏd)
Multiple comparison method used in studies involving analysis of variance.
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The Bonferroni method was further used to determine the origin of this difference, and the revised P = 0.
05 level across all three comparisons, Holm's sequential Bonferroni method was used as shown in Table 1.
Genome-wide significance was defined based on genomic control p-value integration of 5 SNPs and Bonferroni method to correct p-value thresholds of significance after p-value integration: significant association of 0.
In order to prevent type-1 errors resulting from multiple comparisons, we used the Bonferroni method.
1 software (R Foundation for Statistical Computing, Vienna, Austria) package of Bonferroni method was used to adjust the P value to eliminate the risk of type I error in multi-group analyses.
To test significant difference of continuous variables between more than two groups, ANOVA with post hoc Bonferroni tests was used for normally distributed data and Kruskal-Wallis test with multiple comparisons Bonferroni method was used for non-normally distributed data.
Characteristics of the CpG sites from meta-analysis of 28-day trailing average, significant with Bonferroni method, or FDR significant and located in a gene with another CpG that meets genome-wide significance, or FDR significant and Bonferroni significant at shorter time-window.
The Holm method is an extension of the Bonferroni method, which controls the familywise error rate for all N hypotheses at level [alpha] (=[alpha]/N).
0018, to correct for multiple comparisons with the conservative Bonferroni method.
Multiple comparisons using the Bonferroni method concerning the five subscales of time perspective revealed the following significant differences; (a) the score on Hope for the future showed that the Indecision group was significantly lower than the other five groups (p < .