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dc.contributor.authorJan, Show-Lien_US
dc.contributor.authorShieh, Gwowenen_US
dc.date.accessioned2019-04-02T05:58:53Z-
dc.date.available2019-04-02T05:58:53Z-
dc.date.issued2019-03-12en_US
dc.identifier.issn1471-2288en_US
dc.identifier.urihttp://dx.doi.org/10.1186/s12874-019-0697-9en_US
dc.identifier.urihttp://hdl.handle.net/11536/149031-
dc.description.abstractBackgroundLinear regression analysis is a widely used statistical technique in practical applications. For planning and appraising validation studies of simple linear regression, an approximate sample size formula has been proposed for the joint test of intercept and slope coefficients.MethodsThe purpose of this article is to reveal the potential drawback of the existing approximation and to provide an alternative and exact solution of power and sample size calculations for model validation in linear regression analysis.ResultsA fetal weight example is included to illustrate the underlying discrepancy between the exact and approximate methods. Moreover, extensive numerical assessments were conducted to examine the relative performance of the two distinct procedures.ConclusionsThe results show that the exact approach has a distinct advantage over the current method with greater accuracy and high robustness.en_US
dc.language.isoen_USen_US
dc.subjectLinear regressionen_US
dc.subjectModel validationen_US
dc.subjectPoweren_US
dc.subjectSample sizeen_US
dc.subjectStochastic predictoren_US
dc.titleSample size calculations for model validation in linear regression analysisen_US
dc.typeArticleen_US
dc.identifier.doi10.1186/s12874-019-0697-9en_US
dc.identifier.journalBMC MEDICAL RESEARCH METHODOLOGYen_US
dc.citation.volume19en_US
dc.contributor.department管理科學系zh_TW
dc.contributor.departmentDepartment of Management Scienceen_US
dc.identifier.wosnumberWOS:000461378500001en_US
dc.citation.woscount0en_US
Appears in Collections:Articles