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Scores can be corrected for multiple hypothesis testing using either Benjamini Hochberg correction or q-value method.
The SVC procedure, as implemented in SPM2 using the family-wise error (FWE) correction (P < 0.05), allows results to be corrected for multiple nonindependent comparisons with a defined region of interest (ROI).
Subsequently, the p-values could be corrected for multiple hypothesis testing with a simple Bonferroni correction.
The test protocol is time consuming and, if conducted completely, the mere number of parameters, which have to be corrected for multiple testing, requires sample sizes that cannot feasibly be recruited at a single headache clinic.
The analysis is to be done only for the primary outcome, be complemented by statistical tests of interaction, and be corrected for multiple comparisons (Section 2.8.4 GMS TAPS 5).
Since the topographies of the two populations were compared sensor-wise (independently for each sensor), in order for the maps to have statistical sense as a whole, the P-values of each comparison needed to be corrected for multiple comparisons.
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All microarray analysis was corrected for multiple testing using correction for False Discovery Rate (FDR) [ 41].
The level of statistical significance was corrected for multiple tests (Bonferroni correction = p<0.0015).
P-Values were corrected for multiple testing by Bonferroni correction.
The level of significance was corrected for multiple testing using Bonferronis' correction.
P-values were corrected for multiple comparisons using the Bonferroni correction.
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