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In order to avoid significance values of zero in case that no permutation test is more significant than the original data a pseudo-count can be added.
Differences in the MPI scales between the samples were analyzed with one-way analysis of variance (ANOVA) starting with an overall test for differences between the samples followed by post-hoc tests where the study population A was contrasted with each one of the study populations B, C and D according to Dunnett's t-test (to avoid significance due to multiple testing).
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According to the current guidelines for reporting observational data (STROBE) [ 13], we avoided significance tests for the evaluation of differences in baseline characteristics.
Only TEq and sums were analysed to avoid mass significance of multiple comparisons.
To avoid mass significance, univariate analyses were performed exclusively on the X-variables that contributed most to the respective models.
In order to avoid statistical significance that might have occurred by chance, a corrected alpha level of P ≤ 0.01 was accepted as significant (Bonferroni correction).
In order to avoid assigning significance to a N-neuron pattern just because it contains N-1-neuron motifs we incorporate the N-1-neuron statistics into the expectations used to search for N-neuron motifs [ 8].
As the experimental unit is the cell and each cell is represented by multiple pixels, considering pixel numbers would unduly increase the analysis degrees of freedom; thus, to avoid overestimating significance, pixels were binned by using a bin size approaching cell size (200 pixels ≈150 μm).
The values of APPs and eosinophils of the different days were also tested pairwise with the values day 0 using Dunnett adjustment to avoid mass significances.
In case of biochemical variables, the Bonferroni test adjusted for intra correlations between the biomedical variables and a P-value of <0.01 was required to declare significance to avoid chance of mass significance.
In order to compensate for the multiple testing and thus to avoid imparting spurious significance, we used a stringent significance level of 0.002 for each test.
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