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A sharper Bonferroni procedure for multiple tests of significance.
This video describes the fitting procedure for Multiple Stripe Analysis, and demonstrates the Excel spreadsheet for this procedure.
A computational procedure for multiple wave scattering in unidirectional fiber-reinforced composite materials is presented.
Although application of a Bonferroni correction procedure for multiple comparisons eliminated a number of the significant results, several striking enhancements in test performance due to atypical antipsychotic administration (WMS-R General Memory Index score and Category fluency scores) remained significant.
In this regard, a two-level design procedure for multiple loops with H∞ based self-triggered control applied over the modified IEEE 802.15.4 wireless protocol is presented.
Two-stage hepatectomy (TSH) is a feasible procedure for multiple liver tumors that are considered unresectable or that have a high risk of POLF following one-stage hepatectomy.
We chose to use a stepwise Bonferroni-type procedure for multiple testing since simulation studies have confirmed that such procedures generally perform as well or better than more complicated alternative procedures (Cribbie, 2017).
Employing the Bonferroni procedure for "multiple comparisons" further reduces the number of statistically significant regression coefficients, and the reader should consider only those coefficients appearing in the tables with a significance level of p≤.000 as statistically significant at the 0.05 level.
In order to use the closed testing procedure for multiple testing adjustment when comparing three groups, a global test is needed which compares three groups for differences.
Since the variances of the samples were rather heterogeneous, the statistical differences in the distribution pattern and volume of these interneurons were calculated using the Kruskal-Wallis and ANOVA tests with post-hoc Tamhane procedure for multiple comparisons.
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The Benjamin-Hochberg procedure for multiple-testing correction was used to analyze the false discovery rate.
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