The Bonferroni p-value adjustment method maintains the desired Type I error rate by dividing the alpha value (e.g., 0.05) by: the beta value the desired level of statistical power the number of tests to be conducted none of the above options are correct
Added by Barbara M.
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It is done by dividing the alpha level by the number of comparisons being made. Show more…
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Using a Bonferroni correction for multiple comparisons, and using the formula alpha/m, where m is the number of comparisons, this is the largest the type error can be across the tests. alpha = 0.05 beta = 1.10
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The Bonferroni correction can be applied as: a. The nominal α-level divided by the number of comparisons b. The observed p-value times the number of groups c. The observed p-value divided by the number of comparisons d. The nominal α-level times the number of comparisons
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Out of the following statements, identify and select all the ones that are true. When multiple tests are independently evaluated for significance at the threshold level α, the Type I Error rate across all tests will be α. When conducting pairwise tests, it is necessary to use a procedure, such as Holm's correction, to maintain the specified false positive rate. When conducting a proportion test that compares more than two samples, if you obtain a significant result, it is still necessary to perform pairwise testing to determine which samples differ. Multiple testing corrections, such as Holm's procedure, are primarily focused on reducing the number of Type II statistical errors.
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