A Confidence Interval Approach for Comparative Studies Involving Binary Outcomes in Paired Organs

Bilateral binary data are very common in medical comparative studies and clinical trials (e.g., comparison of two treatments in ophthalmologic studies) in which information involving paired organs (e.g., eyes) is available from each subject. Previous studies reported that ignoring the dependence fea...

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Published inCommunications in statistics. Simulation and computation Vol. 42; no. 2; pp. 425 - 453
Main Authors Tang, Man-lai, He, Xinjie, Tian, Guoliang
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis Group 01.02.2013
Taylor & Francis Ltd
Subjects
Bilateral data
Comparative studies
Confidence interval estimator
Method of variance estimate recovery (MOVER)
Primary 92B15
Secondary 97K80
Square-and-add approach
Studies
Online AccessGet full text
ISSN0361-0918
1532-4141
DOI10.1080/03610918.2011.639002

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Abstract Bilateral binary data are very common in medical comparative studies and clinical trials (e.g., comparison of two treatments in ophthalmologic studies) in which information involving paired organs (e.g., eyes) is available from each subject. Previous studies reported that ignoring the dependence feature of bilateral data could lead to severely incorrect coverage probabilities. In this article, we study various confidence interval estimators for the difference of response rates under the dependence nature of bilateral data. Their performances are evaluated with respect to their expected coverage probabilities, mesial/distal non-coverage probabilities and interval widths via simulation studies. A real example from an otolaryngologic study is used to demonstrate our proposed methodologies.
AbstractList Bilateral binary data are very common in medical comparative studies and clinical trials (e.g., comparison of two treatments in ophthalmologic studies) in which information involving paired organs (e.g., eyes) is available from each subject. Previous studies reported that ignoring the dependence feature of bilateral data could lead to severely incorrect coverage probabilities. In this article, we study various confidence interval estimators for the difference of response rates under the dependence nature of bilateral data. Their performances are evaluated with respect to their expected coverage probabilities, mesial/distal non-coverage probabilities and interval widths via simulation studies. A real example from an otolaryngologic study is used to demonstrate our proposed methodologies.
Bilateral binary data are very common in medical comparative studies and clinical trials (e.g., comparison of two treatments in ophthalmologic studies) in which information involving paired organs (e.g., eyes) is available from each subject. Previous studies reported that ignoring the dependence feature of bilateral data could lead to severely incorrect coverage probabilities. In this article, we study various confidence interval estimators for the difference of response rates under the dependence nature of bilateral data. Their performances are evaluated with respect to their expected coverage probabilities, mesial/distal non-coverage probabilities and interval widths via simulation studies. A real example from an otolaryngologic study is used to demonstrate our proposed methodologies. [PUBLICATION ABSTRACT]
Author Tian, Guoliang
He, Xinjie
Tang, Man-lai
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SubjectTerms Bilateral data
Comparative studies
Confidence interval estimator
Method of variance estimate recovery (MOVER)
Primary 92B15
Secondary 97K80
Square-and-add approach
Studies
Title A Confidence Interval Approach for Comparative Studies Involving Binary Outcomes in Paired Organs
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