Glossary

Bonferroni Adjustment

Bonferroni Adjustment:

Bonferroni adjustment is used in multiple comparison procedures to calculate an adjusted probability a of comparison-wise type I error from the desired probability a_FW0 of family-wise type I error. The calculation guarantees that the use of the adjusted a in pairwise comparisons keeps the actual probability a_FW of family-wise type I errors not higher than the desired level, as specified by the significance level of the test.

Bonferroni, an Italian mathematician, proved the following inequality:

1 – (1 – a)^C Ã‚Â£ C a; 0 Ã‚Â£ a Ã‚Â£ 1

for any value C. Since a_FW and a are linked by the formula

a_FW = 1 – (1 – a)^C,

(see Family-wise Type I Error), where C is the total number of pairwise comparisons, the Bonferroni inequality gives the following approximate formula

a =

a_FW0

Suppose 4 populations are to be compared, and the maximum allowed family-wise type I error is a_FW0 = 0.05. Then, the total number of pairs C=4(4-1)/2=6, and Bonferroni adjustment gives a = 0.05/6 ? 0.0083. Now we may be sure that, if all the 4 populations have the same mean, and we test pairwise differences at significance level a = 0.0083, the probability a_FW that you will erroneously conclude that the population means in at least one pair differ is not higher than 0.05.

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