Multiple comparisons

From WikiMD's Wellnesspedia

Multiple comparisons or multiple testing is a term used in statistics to address the problem of simultaneously testing a series of hypotheses. The issue arises when one considers that, as the number of hypotheses tested increases, the likelihood of identifying at least one significant result due to random chance also increases.

Overview[edit | edit source]

The problem of multiple comparisons arises when a number of inferential statistics tests are being performed simultaneously. This is a common occurrence in data analysis, where multiple variables or outcomes are being compared. The issue is that as the number of comparisons increases, the probability of observing a statistically significant result by chance (a Type I error) also increases.

Solutions[edit | edit source]

Several solutions have been proposed to control the familywise error rate (FWER) or the false discovery rate (FDR). These include the Bonferroni correction, the Šidák correction, the Holm-Bonferroni method, and the Benjamini–Hochberg procedure.

See also[edit | edit source]

References[edit | edit source]


Multiple comparisons Resources

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