Homogeneity test for correlated binary data.

Homogeneity test for correlated binary data.

In ophthalmologic studies, measurements obtained from both eyes of an individual are often highly correlated. Ignoring the correlation could lead to incorrect inferences. An asymptotic method was proposed by Tang and others (2008) for testing equality of proportions between two groups under Rosner&#...

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Main Authors: Changxing Ma, Guogen Shan, Song Liu
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4405297?pdf=render
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spelling doaj-0ce6bb0c1bfc4bc2b8c9211898811d6e2020-11-24T21:48:58ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01104e012433710.1371/journal.pone.0124337Homogeneity test for correlated binary data.Changxing MaGuogen ShanSong LiuIn ophthalmologic studies, measurements obtained from both eyes of an individual are often highly correlated. Ignoring the correlation could lead to incorrect inferences. An asymptotic method was proposed by Tang and others (2008) for testing equality of proportions between two groups under Rosner's model. In this article, we investigate three testing procedures for general g ≥ 2 groups. Our simulation results show the score testing procedure usually produces satisfactory type I error control and has reasonable power. The three test procedures get closer when sample size becomes larger. Examples from ophthalmologic studies are used to illustrate our proposed methods.http://europepmc.org/articles/PMC4405297?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Changxing Ma
Guogen Shan
Song Liu
spellingShingle Changxing Ma
Guogen Shan
Song Liu
Homogeneity test for correlated binary data.
PLoS ONE
author_facet Changxing Ma
Guogen Shan
Song Liu
author_sort Changxing Ma
title Homogeneity test for correlated binary data.
title_short Homogeneity test for correlated binary data.
title_full Homogeneity test for correlated binary data.
title_fullStr Homogeneity test for correlated binary data.
title_full_unstemmed Homogeneity test for correlated binary data.
title_sort homogeneity test for correlated binary data.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2015-01-01
description In ophthalmologic studies, measurements obtained from both eyes of an individual are often highly correlated. Ignoring the correlation could lead to incorrect inferences. An asymptotic method was proposed by Tang and others (2008) for testing equality of proportions between two groups under Rosner's model. In this article, we investigate three testing procedures for general g ≥ 2 groups. Our simulation results show the score testing procedure usually produces satisfactory type I error control and has reasonable power. The three test procedures get closer when sample size becomes larger. Examples from ophthalmologic studies are used to illustrate our proposed methods.
url http://europepmc.org/articles/PMC4405297?pdf=render
work_keys_str_mv AT changxingma homogeneitytestforcorrelatedbinarydata
AT guogenshan homogeneitytestforcorrelatedbinarydata
AT songliu homogeneitytestforcorrelatedbinarydata
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