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Nomogram for sample size calculation in assessing validity of a new method based on a regression line

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dc.contributor.authorHong, Hyunsook-
dc.contributor.authorHahn, Seokyoung-
dc.contributor.authorKim, Ho-
dc.contributor.authorChoi, Yunhee-
dc.date.accessioned2023-04-18T06:18:45Z-
dc.date.available2023-04-18T06:18:45Z-
dc.date.created2023-03-21-
dc.date.created2023-03-21-
dc.date.issued2023-08-
dc.identifier.citationCommunications in Statistics - Theory and Methods, Vol.52 No.16, pp.5900-5909-
dc.identifier.issn0361-0926-
dc.identifier.urihttps://hdl.handle.net/10371/190014-
dc.description.abstractThe validity of a newly developed diagnostic method is usually proven by comparing with a well-grounded reference method. When measurements from a new method are continuous but in different units from a reference standard and having a linear relationship, validity can be usually assessed by Pearson correlation coefficient, but it does not provide clinical guidance for judging validity. We defined a limits-of-agreement derived from regression models for assessing validity of new method, and developed a sample size formula. The sample size formula to achieve a certain probability that the limits-of-agreement is within a pre-defined, clinically acceptable range [-delta, delta] was derived and the result is presented as a nomogram. When a ratio of upper bound of a limits-of-agreement to delta is expected to be 0.95, a sample size of approximately 300 achieves a 90% probability that the limits-of-agreement lies within +/- delta. The simulation showed that the suggested sample size formula had the targeted coverages. The sample size determination based on a limits-of-agreement is practical for showing validity of new methods, measuring the same attribute but in different units, and the presented nomogram is useful.-
dc.language영어-
dc.publisherMarcel Dekker Inc.-
dc.titleNomogram for sample size calculation in assessing validity of a new method based on a regression line-
dc.typeArticle-
dc.identifier.doi10.1080/03610926.2021.2023182-
dc.citation.journaltitleCommunications in Statistics - Theory and Methods-
dc.identifier.wosid000746730300001-
dc.identifier.scopusid2-s2.0-85123852041-
dc.citation.endpage5909-
dc.citation.number16-
dc.citation.startpage5900-
dc.citation.volume52-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorKim, Ho-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.subject.keywordPlusCALIBRATION-
dc.subject.keywordPlusSTATISTICS-
dc.subject.keywordPlusAGREEMENT-
dc.subject.keywordAuthorMethod comparison-
dc.subject.keywordAuthorvalidity-
dc.subject.keywordAuthorlimits-of-agreement-
dc.subject.keywordAuthora regression line-
dc.subject.keywordAuthorsample size-
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