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Methods to avoid false positives

1 Use a single ( omnibus ) test to avoid a series of pair-wise comparisons [Pg.250]

Multiple endpoints For this scenario, there is a whole other area of analysis referred to as multivariate statistics. These methods also allow omnibus testing - all endpoints are considered simultaneously. Multivariate stats are among the most complex to perform and interpret - there are generally six different ways to do any one [Pg.250]

Multiple time points With observations at several time points, all the data can be considered simultaneously using a technique called repeated measures analysis of variance. This can be carried out using Minitab. Its execution and interpretation is not unduly complex, but is probably best undertaken with expert statistical support. [Pg.251]

Bonferroni keeps the rate of type I errors down to 5 percent... In many instances, omnibus tests are not possible. If there are several comparisons to be made, each involving different groups of individuals and different endpoints, there may be no choice but to use a series of discrete statistical tests. In these circumstances, the Bonferroni correction may be applied to maintain the overall risk of false positives at the standard level of 5 per cent. [Pg.251]

What the Bonferroni correction does is to raise the standard of proof for all the individual tests. Each test is then less likely to produce a false positive and the complete series of analyses will jointly generate a 5 per cent risk. [Pg.251]


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