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

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...

Full description

Bibliographic Details
Main Authors: Eric Weine, Mary Sara McPeek, Mark Abney
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2023-04-01
Series:Journal of Statistical Software
Online Access:https://www.jstatsoft.org/index.php/jss/article/view/4843
_version_ 1797813921821753344
author Eric Weine
Mary Sara McPeek
Mark Abney
author_facet Eric Weine
Mary Sara McPeek
Mark Abney
author_sort Eric Weine
collection DOAJ
description 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 qqconf, a versatile tool to create Q-Q plots and probability-probability (P-P) plots in a wide variety of settings, with simultaneous testing bands rapidly created using recently-developed algorithms. qqconf can easily be used to add global testing bands to Q-Q plots made by other packages. In addition to being quick to compute, these bands have a variety of desirable properties, including accurate global levels, equal sensitivity to deviations in all parts of the null distribution (including the tails), and applicability to a range of null distributions. We illustrate the use of qqconf in several applications: assessing normality of residuals from regression, assessing accuracy of p values, and use of Q-Q plots in genome-wide association studies.
first_indexed 2024-03-13T07:59:50Z
format Article
id doaj.art-23533b4fa40a42a39a7686eeccd6e783
institution Directory Open Access Journal
issn 1548-7660
language English
last_indexed 2024-03-13T07:59:50Z
publishDate 2023-04-01
publisher Foundation for Open Access Statistics
record_format Article
series Journal of Statistical Software
spelling doaj.art-23533b4fa40a42a39a7686eeccd6e7832023-06-01T18:48:03ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602023-04-0110613110.18637/jss.v106.i108480Application of Equal Local Levels to Improve Q-Q Plot Testing Bands with R Package qqconfEric Weine0Mary Sara McPeek1https://orcid.org/0009-0007-7344-834XMark Abney2https://orcid.org/0000-0002-1718-5676University of ChicagoUniversity of ChicagoUniversity of ChicagoQuantile-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 qqconf, a versatile tool to create Q-Q plots and probability-probability (P-P) plots in a wide variety of settings, with simultaneous testing bands rapidly created using recently-developed algorithms. qqconf can easily be used to add global testing bands to Q-Q plots made by other packages. In addition to being quick to compute, these bands have a variety of desirable properties, including accurate global levels, equal sensitivity to deviations in all parts of the null distribution (including the tails), and applicability to a range of null distributions. We illustrate the use of qqconf in several applications: assessing normality of residuals from regression, assessing accuracy of p values, and use of Q-Q plots in genome-wide association studies.https://www.jstatsoft.org/index.php/jss/article/view/4843
spellingShingle Eric Weine
Mary Sara McPeek
Mark Abney
Application of Equal Local Levels to Improve Q-Q Plot Testing Bands with R Package qqconf
Journal of Statistical Software
title Application of Equal Local Levels to Improve Q-Q Plot Testing Bands with R Package qqconf
title_full Application of Equal Local Levels to Improve Q-Q Plot Testing Bands with R Package qqconf
title_fullStr Application of Equal Local Levels to Improve Q-Q Plot Testing Bands with R Package qqconf
title_full_unstemmed Application of Equal Local Levels to Improve Q-Q Plot Testing Bands with R Package qqconf
title_short Application of Equal Local Levels to Improve Q-Q Plot Testing Bands with R Package qqconf
title_sort application of equal local levels to improve q q plot testing bands with r package qqconf
url https://www.jstatsoft.org/index.php/jss/article/view/4843
work_keys_str_mv AT ericweine applicationofequallocallevelstoimproveqqplottestingbandswithrpackageqqconf
AT marysaramcpeek applicationofequallocallevelstoimproveqqplottestingbandswithrpackageqqconf
AT markabney applicationofequallocallevelstoimproveqqplottestingbandswithrpackageqqconf