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2018/8/7 -The simplest way to adjust your P values is to use the conservative Bonferroni correction method which multiplies the raw P values by the number ...

A separate adjusted P value is computed for each comparison in a family of comparisons. But the value of these adjusted P values depends on the entire family.

Use for multiple comparisons in ANOVA, the adjusted p-value indicates which factor level comparisons within a family of comparisons (hypothesis tests) are ...

Key facts about multiplicity adjusted P values. •A separate adjusted P values is computed for each comparison in a family of comparisons. •The value of each ...

Another way to look at the difference is that a p-value of 0.05 implies that 5% of all tests will result in false positives. An FDR adjusted p-value (or q-value) ...

2002/6/17 -Classicists believe that if multiple measures are tested in a given study, the p-value should be adjusted upward to reduce the chance of ...

The adjusted P-value for a particular hypothesis within a collection of hypotheses, then, is the smallest overall (i.e., “experimentwise”) significance level at ...

2021/9/28 -The simplest method is a so-called Bonferroni correction. This means multiplying the p-values by the number of hypotheses, in this case six, ...

The adjustment methods include the Bonferroni correction ( "bonferroni" ) in which the p-values are multiplied by the number of comparisons. Less conservative ...

For studies with multiple outcomes, p-values can be adjusted to account for the multiple comparisons issue. The 'p.adjust( )' command in R calculates adjusted p ...