Please use this identifier to cite or link to this item: https://doi.org/10.1080/10543406.2010.508346
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dc.titleSample sizes for estimating differences in proportionscan we keep things simple?
dc.contributor.authorTan, S.H.
dc.contributor.authorMacHin, D.
dc.contributor.authorTan, S.B.
dc.date.accessioned2014-11-26T05:04:50Z
dc.date.available2014-11-26T05:04:50Z
dc.date.issued2012-01-01
dc.identifier.citationTan, S.H., MacHin, D., Tan, S.B. (2012-01-01). Sample sizes for estimating differences in proportionscan we keep things simple?. Journal of Biopharmaceutical Statistics 22 (1) : 133-140. ScholarBank@NUS Repository. https://doi.org/10.1080/10543406.2010.508346
dc.identifier.issn10543406
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/109040
dc.description.abstractSample sizes for studies that aim to estimate differences in proportions are often calculated using a confidence interval approach. In particular, the methods advocated by Day (1988) and Bristol (1989), based on asymptotic normal approximations, are commonly used. We compare these to the Wilson score approach discussed by Newcombe (1998) and show, except for extreme values, that the Day method gives results close to those of Wilson score method, while that of Bristol is consistently higher. We argue that the asymptotic normal approximation approach of Day serves as a better guide for quick calculations of sample sizes. © 2012 Copyright Taylor and Francis Group, LLC.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1080/10543406.2010.508346
dc.sourceScopus
dc.subjectConfidence interval
dc.subjectDifferences in proportions
dc.subjectSample size
dc.typeArticle
dc.contributor.departmentSAW SWEE HOCK SCHOOL OF PUBLIC HEALTH
dc.description.doi10.1080/10543406.2010.508346
dc.description.sourcetitleJournal of Biopharmaceutical Statistics
dc.description.volume22
dc.description.issue1
dc.description.page133-140
dc.description.codenJBSTE
dc.identifier.isiut000302064800009
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