Application of Equal Local Levels to Improve Q-Q Plot Testing Bands with R Package qqconf.

Equal Local Levels GWAS Global Testing Kolmogorov-Smirnov Multiple Testing Q-Q plots Simultaneous Region

Journal

Journal of statistical software
ISSN: 1548-7660
Titre abrégé: J Stat Softw
Pays: United States
ID NLM: 101307056

Informations de publication

Date de publication:
2023
Historique:
medline: 19 5 2023
pubmed: 19 5 2023
entrez: 19 5 2023
Statut: ppublish

Résumé

Quantile-Quantile (Q-Q) plots are often difficult to interpret because it is unclear how large the deviation from the theoretical distribution must be to indicate a lack of fit. Most Q-Q plots could benefit from the addition of meaningful global testing bands, but the use of such bands unfortunately remains rare because of the drawbacks of current approaches and packages. These drawbacks include incorrect global Type I error rate, lack of power to detect deviations in the tails of the distribution, relatively slow computation for large data sets, and limited applicability. To solve these problems, we apply the equal local levels global testing method, which we have implemented in the R Package

Identifiants

pubmed: 37205880
doi: 10.18637/jss.v106.i10
pmc: PMC10193564
mid: NIHMS1890451
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : NHGRI NIH HHS
ID : R01 HG001645
Pays : United States

Références

Biom J. 2015 Jan;57(1):159-80
pubmed: 24914007
Lancet Neurol. 2020 Oct;19(10):840-848
pubmed: 32949544
Biometrika. 1968 Mar;55(1):1-17
pubmed: 5661047

Auteurs

Eric Weine (E)

University of Chicago.

Mary Sara McPeek (MS)

University of Chicago.

Mark Abney (M)

University of Chicago.

Classifications MeSH