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Describes experiment-wise error rate and how to address it by taking a larger sample or reducing the number of analyses or reducing the significance level.

To explore these associations in vivo, we evaluated 30 Aβ PET-positive patients (mean ± sd age 62.4 ± 8.3) with mild probable AD and 12 Aβ PET-negative healthy controls (HC) (mean ± sd age 77.3 ± 6.9) as comparison. 0.05 Family.

Nov 2, 2002. This is the probability that we will make at least one Type I error in a set (family) of comparisons. If we compare Treatment1 against Treatment2, Treatment 3 against Treatment4, and Treatment1 against Treatment4, the familywise error rate is the probability that our set of three conclusions will contain at.

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Nov 27, 2001. If we ran several tests, each at a , the probability of at least one error is no greater than ca , where c is the number of comparisons, or tests. In general, multiple comparison procedures are established to control the familywise error rate in some way. Different procedures do this in different ways.

In statistics, family-wise error rate. Tukey's procedure is only applicable for pairwise comparisons. It assumes independence of the observations being tested,

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α pc is the per-comparison error rate, and c is the number of comparisons. If the comparisons are not independent then the experimentwise error rate is less than.

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The following table defines the possible outcomes when testing multiple null hypotheses. Suppose we have a number m of null hypotheses, denoted by: H.

Figure 1: Comparison of family-wise error rate (FWER) obtained by 1000 resampling runs and estimated by the heuristic method presented here. The test groups of size T = 20, T = 100 and T = 250 were chosen randomly from all GO- annotated probe-sets on Affymetrix's HG-133A (solid lines, 15652 annotated probe-sets).

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Statistical analyses were adjusted for multivariate effects using the Benjamini–Hochberg false discovery rate method.

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