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We further show that the DeLong et al. method tests a different hypothesis and has the nominal type I error when it is used within its designed scope.
This method tests a series of regression models, excluding in each new model the worst predictor of the previously tested model according to a statistical criterion (p ≥.10).
Although this method tests a slightly different null hypothesis namely, whether the GAM data at the CD SNPs follow expectations under a neutral model, given the EUR and MKK data the results strongly support the findings of method 1.
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This method tests for a linear trend in the number of alleles at a single locus.
Briefly, this method tests for a non-intermediate optimum by constraining the fitness optimum at either the maximum or minimum of the phenotypic distribution.
Basically, the method tests the association of a score variable that manifests a combined effect of many SNPs.
The last method tested was a bracket removal plier (BRP), as shown in Fig. 1d.
The projection extension method tested is a simple but adequate method to estimate down-scatter of the 99mTc photons originating from the liver.
We argue that this is related to how a segmentation method tests for a change point.
However, our method is testing a different aspect of the activity of a pathway than SPIA and GSEA do.
There is a great variability in efficiency for the methods tested as a function of the origin of the HTs (Figure 2A).
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