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Johnson et al. BMC Genomics 2010, 11:724 http://www.biomedcentral.com/1471-2164/11/724 RESEARCH ARTICLE Open Access Accounting for multiple comparisons in a genome-wide association study (WAS) Randall
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Accounting for multiple comparisons is a statistical method used to adjust the significance levels or p-values when conducting multiple statistical tests in order to control the overall Type I error rate.
Researchers or analysts who are conducting multiple statistical tests and want to control the overall Type I error rate need to perform accounting for multiple comparisons.
Accounting for multiple comparisons can be done by using various statistical methods or software packages specifically designed for this purpose. These methods typically involve adjusting p-values using techniques such as Bonferroni correction, false discovery rate correction, or Tukey's honest significance test.
The purpose of accounting for multiple comparisons is to reduce the likelihood of obtaining false positive results or Type I errors when conducting multiple statistical tests. By adjusting the significance levels, it helps to maintain the overall error rate within an acceptable range.
Accounting for multiple comparisons typically involves reporting the adjusted p-values, the chosen method or correction technique used, and any relevant statistics or measures associated with the analysis.
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