2014
DOI: 10.15446/rce.v37n1.44358
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A New Method for Detecting Significant p-values with Applications to Genetic Data

Abstract: A new method for detecting significant p-values is described in this paper. This method, based on the distribution of the m-th order statistic of a U (0, 1) distribution, is shown to be suitable in applications where m → ∞ independent hypothesis are tested and it is of interest for a fixed type I error probability to determine those being significant while controlling the false positives. Equivalencies and comparisons between our method and others methods based-on p-values are also established, and a graphical… Show more

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Cited by 18 publications
(20 citation statements)
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“…Thus, the collection P 1 , P 2 ,…, P m of P -values were corrected for multiple testing using the false discovery rate (FDR) 35 and a method based on extreme-values theory. 36 Because hypotheses testing were of the same type, correction was only performed on the resulting m P -values. 35,36 For the single locus models, we estimated the Genomic Control “inflation factor” λ, to evaluate potential stratification effects.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Thus, the collection P 1 , P 2 ,…, P m of P -values were corrected for multiple testing using the false discovery rate (FDR) 35 and a method based on extreme-values theory. 36 Because hypotheses testing were of the same type, correction was only performed on the resulting m P -values. 35,36 For the single locus models, we estimated the Genomic Control “inflation factor” λ, to evaluate potential stratification effects.…”
Section: Methodsmentioning
confidence: 99%
“…36 Because hypotheses testing were of the same type, correction was only performed on the resulting m P -values. 35,36 For the single locus models, we estimated the Genomic Control “inflation factor” λ, to evaluate potential stratification effects.…”
Section: Methodsmentioning
confidence: 99%
“…Variants significantly associated with the ADHD phenotype were determined after correction by multiple testing using the false discovery rate (FDR) (Benjamini and Hochberg ) and an alternative method based on extreme‐values theory (Vélez et al. ). As this is an attempt of evaluate an already known association, we have used the criterion of a P ‐value ≤0.10 to consider a positive replication.…”
Section: Methodsmentioning
confidence: 99%
“…After the estimation process using the forward/ backward algorithm concluded, the estimated coefficientsβ 1 ; β 2 ; …;β m were extracted and a hypothesis test of the form H 0,i : β i = 0 vs. H 1,i : β i ≠ 0 was performed for the ith CEFVs to obtain the corresponding P value, P i (i = 1,2,…,m). The collection P 1 , P 2 ,…, P m was subsequently corrected for multiple testing using the false discovery rate (FDR) [31,32] using R [33].…”
Section: Gwas Analysis Of Common Variantsmentioning
confidence: 99%