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dc.contributor.authorShieh, Gwowenen_US
dc.date.accessioned2014-12-08T15:13:22Z-
dc.date.available2014-12-08T15:13:22Z-
dc.date.issued2007-09-01en_US
dc.identifier.issn0033-3123en_US
dc.identifier.urihttp://dx.doi.org/10.1007/s11336-007-9012-5en_US
dc.identifier.urihttp://hdl.handle.net/11536/10351-
dc.description.abstractThe underlying statistical models for multiple regression analysis are typically attributed to two types of modeling: fixed and random. The procedures for calculating power and sample size under the fixed regression models are well known. However, the literature on random regression models is limited and has been confined to the case of all variables having a joint multivariate normal distribution. This paper presents a unified approach to determining power and sample size for random regression models with arbitrary distribution configurations for explanatory variables. Numerical examples are provided to illustrate the usefulness of the proposed method and Monte Carlo simulation studies are also conducted to assess the accuracy. The results show that the proposed method performs well for various model specifications and explanatory variable distributions.en_US
dc.language.isoen_USen_US
dc.subjectasymptotic distributionen_US
dc.subjecteffect sizeen_US
dc.subjectnoncentral F distributionen_US
dc.titleA unified approach to power calculation and sample size determination for random regression modelsen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s11336-007-9012-5en_US
dc.identifier.journalPSYCHOMETRIKAen_US
dc.citation.volume72en_US
dc.citation.issue3en_US
dc.citation.spage347en_US
dc.citation.epage360en_US
dc.contributor.department管理科學系zh_TW
dc.contributor.departmentDepartment of Management Scienceen_US
dc.identifier.wosnumberWOS:000251153500004-
dc.citation.woscount2-
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