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In this paper, the authors deal with the general ROC curve comparison problem on paired design.
The conjecture can be restated as a comparison problem for Brownian motions with reflecting boundary conditions.
This approach allowed for increasing the test sensitivity based on the assumption of temporal continuity of the data, thereby avoiding a massive multiple comparison problem and resulting in continuous intervals.
The usage of likelihood ratio models is common in both the classification and comparison problem designed especially for evidence evaluation dedicated to physicochemical data.
(This threshold was set to t = 1.8, corresponding to p < 0.05 with 13 degrees of freedom; note that the selection of this threshold still leads to a conservative treatment of the multiple comparison problem since a permutation test is subsequently performed). Contiguous threshold-surviving edges are defined as a cluster.
The main aim of this study was to verify whether selected analytical parameters may affect solving the comparison problem of Raman spectra with the use of the likelihood ratio (LR) approach.
Family‐based designs require specialized analytic methods but they have distinct advantages: They are robust to confounding and variance inflation, which can arise in standard designs in the presence of population substructure; they test for both linkage and association; and they offer a natural solution to the multiple comparison problem.
23There are formal ways to address the multiple comparison problem (see Schochet 2008,2008).
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The multiple-comparison problem was addressed by means of cluster-based non-parametric permutation testing (see Further statistical analysis).
The multiple-comparison problem is addressed using a cluster analysis based on non-stationary Gaussian random field theory.
To test for statistically significant differences between conditions and reduce the multiple-comparison problem, we used the cluster-based approach implemented in the Fieldtrip toolbox (Maris and Oostenveld 2007).
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