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Article: Common risk difference test and interval estimation of risk difference for stratified bilateral correlated data

TitleCommon risk difference test and interval estimation of risk difference for stratified bilateral correlated data
Authors
Issue Date2019
PublisherSage Publications Ltd. The Journal's web site is located at http://smm.sagepub.com
Citation
Statistical Methods in Medical Research, 2019, v. 28 n. 8, p. 2418-2438 How to Cite?
AbstractBilateral correlated data are often encountered in medical researches such as ophthalmologic (or otolaryngologic) studies, in which each unit contributes information from paired organs to the data analysis, and the measurements from such paired organs are generally highly correlated. Various statistical methods have been developed to tackle intra-class correlation on bilateral correlated data analysis. In practice, it is very important to adjust the effect of confounder on statistical inferences, since either ignoring the intra-class correlation or confounding effect may lead to biased results. In this article, we propose three approaches for testing common risk difference for stratified bilateral correlated data under the assumption of equal correlation. Five confidence intervals of common difference of two proportions are derived. The performance of the proposed test methods and confidence interval estimations is evaluated by Monte Carlo simulations. The simulation results show that the score test statistic outperforms other statistics in the sense that the former has robust type I error rates with high powers. The score confidence interval induced from the score test statistic performs satisfactorily in terms of coverage probabilities with reasonable interval widths. A real data set from an otolaryngologic study is used to illustrate the proposed methodologies.
Persistent Identifierhttp://hdl.handle.net/10722/258732
ISSN
2017 Impact Factor: 2.284
2015 SCImago Journal Rankings: 3.774

 

DC FieldValueLanguage
dc.contributor.authorShen, X-
dc.contributor.authorMa, C-
dc.contributor.authorYuen, KC-
dc.contributor.authorTian, GL-
dc.date.accessioned2018-08-22T01:43:09Z-
dc.date.available2018-08-22T01:43:09Z-
dc.date.issued2019-
dc.identifier.citationStatistical Methods in Medical Research, 2019, v. 28 n. 8, p. 2418-2438-
dc.identifier.issn0962-2802-
dc.identifier.urihttp://hdl.handle.net/10722/258732-
dc.description.abstractBilateral correlated data are often encountered in medical researches such as ophthalmologic (or otolaryngologic) studies, in which each unit contributes information from paired organs to the data analysis, and the measurements from such paired organs are generally highly correlated. Various statistical methods have been developed to tackle intra-class correlation on bilateral correlated data analysis. In practice, it is very important to adjust the effect of confounder on statistical inferences, since either ignoring the intra-class correlation or confounding effect may lead to biased results. In this article, we propose three approaches for testing common risk difference for stratified bilateral correlated data under the assumption of equal correlation. Five confidence intervals of common difference of two proportions are derived. The performance of the proposed test methods and confidence interval estimations is evaluated by Monte Carlo simulations. The simulation results show that the score test statistic outperforms other statistics in the sense that the former has robust type I error rates with high powers. The score confidence interval induced from the score test statistic performs satisfactorily in terms of coverage probabilities with reasonable interval widths. A real data set from an otolaryngologic study is used to illustrate the proposed methodologies.-
dc.languageeng-
dc.publisherSage Publications Ltd. The Journal's web site is located at http://smm.sagepub.com-
dc.relation.ispartofStatistical Methods in Medical Research-
dc.rightsStatistical Methods in Medical Research. Copyright © Sage Publications Ltd.-
dc.titleCommon risk difference test and interval estimation of risk difference for stratified bilateral correlated data-
dc.typeArticle-
dc.identifier.emailYuen, KC: kcyuen@hku.hk-
dc.identifier.authorityYuen, KC=rp00836-
dc.description.naturepostprint-
dc.identifier.doi10.1177/0962280218781988-
dc.identifier.hkuros286750-
dc.identifier.volume28-
dc.identifier.issue8-
dc.identifier.spage2418-
dc.identifier.epage2438-
dc.publisher.placeUnited Kingdom-

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