Adjustment Factors for Sample Size Calculations

Adjustment Factors for Sample Size Calculations -...

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Adjustment Factors for Sample Size Calculations If there is more than one primary outcome variable or more than one primary comparison, then the significance level should be adjusted to account for the multiple comparisons in order not to inflate the overall false-positive rate. For example, suppose a clinical trial will involve two treatment groups and a placebo group. The investigator may decide that there are two primary comparisons of interest, namely, each treatment group compared to placebo. The simplest adjustment to the significance level for each test is the Bonferroni correction, which uses α/2 instead of α. In general, if there are K comparisons of primary interest, then the Bonferroni correction is to use a significance level of α/K for each of the K comparisons. The Bonferroni correction is not the most powerful or most sophisticated multiple comparison adjustment, but it is a conservative approach and the easiest to apply.
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This note was uploaded on 02/15/2012 for the course GEO 6938 taught by Professor Staff during the Summer '08 term at University of Florida.

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Adjustment Factors for Sample Size Calculations -...

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