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Adjusting for multiplicity testing using Bonferroni methodology, which is the most conservative approach, the adjusted statistical significance corresponds to an alpha risk of 0.025.
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Raw p values were adjusted for multiplicity of testing using the false discovery rate (FDR) procedure of Reiner and colleagues [ 28] using Spotfire (Somerville, MA).
Mammary carcinoma multiplicity was tested using One-Way ANOVA with Bonferroni-Dunn multiple comparison.
When appropriate, we corrected for multiplicity of statistical tests using standard procedures [54], [55].
We estimated 0.05 significance thresholds using method D, adjusted for multiplicity of the tests, using 1000 permutations of the genotypic data in the subsample (see section 5 in File S1 for more information).
Viral efficacy was tested using multiplicity of infections (MOIs) of 1 and 5 in HEK293 cells.
Each family was tested using the Hochberg procedure controlling for multiplicity at the 2.5% significance level.
The same cell line was used as in the study of Maggs et al. and conditions were tested using two different virus to cell ratios (multiplicity of infection of 0.1 and 1).
Two sample t-tests using the −ΔCT values were performed; Holm's method was applied to adjust for multiplicity and control the overall family-wise type I error rate at α=0.05.
Considering multiplicity testing issues, comparisons were controlled using the false discovery rate at the 5% test level [ 24].
Nine of these genes were ranked among the top 35 ones (the p-value of enrichment after Bonferroni correction for multiplicity testing is 9.99 × 10-13, with multiplicity correction factor 283; we used right-hand side exact Fisher's test based on hypergeometric distribution).
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