"MULTIPLE-COMPARISONS" PROBLEM

[摘要] Often investigators report many P values in the same study. The expected number of P values smaller than 0.05 is 1 in 20 tests of true null hypotheses; therefore the probability that at least one P value will be smaller than 0.05 increases with the number of tests, even when the null hypothesis is correct for each test. This increase is known as the "multiple-comparisons" problem...One reasonable way to correct for multiplicity is simply to multiply the P value by the number of tests. Thus, with five tests, an orignal 0.05 level for each is increased, perhaps to a value as high as 0.25 for the set. To achieve a level of not more than 0.05 for the set, we need to choose a level of 0.05/5 = 0.01 for the individual tests. This adjustment is conservative. We know only that the probability does not exceed 0.05 for the set.

[学科分类] 儿科学