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dc.contributor.advisorLevin, Joel R.en_US
dc.contributor.authorZhou, Dora Xinyue
dc.creatorZhou, Dora Xinyueen_US
dc.date.accessioned2013-05-09T10:58:08Zen
dc.date.available2013-05-09T10:58:08Zen
dc.date.issued2004en_US
dc.identifier.urihttp://hdl.handle.net/10150/290098en
dc.description.abstractThe present study extends the previous one-way ANOVA multiple-comparison findings of Meyers and Beretvas (2003) to interaction comparisons in factorial ANOVA designs, one-factor MANOVA comparisons, and tests of partial regression coefficients in multiple regression, in specific regard to the practical utility of modified (sequential) Scheffe-based procedures. Researchers who are concerned with maintaining familywise Type I error rates while increasing statistical power are encouraged to consider these improved multiple-comparison methods.
dc.language.isoen_USen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectStatistics.en_US
dc.subjectEducation, Educational Psychology.en_US
dc.subjectPsychology, Psychometrics.en_US
dc.titleA type I error investigation of modified Scheffe-based multiple-comparison procedures in factorial ANOVA, MANOVA, and multiple-regression situationsen_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.identifier.proquest3132281en_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineEducational Psychologyen_US
thesis.degree.namePh.D.en_US
dc.identifier.bibrecord.b46708224en_US
refterms.dateFOA2018-08-15T02:44:54Z
html.description.abstractThe present study extends the previous one-way ANOVA multiple-comparison findings of Meyers and Beretvas (2003) to interaction comparisons in factorial ANOVA designs, one-factor MANOVA comparisons, and tests of partial regression coefficients in multiple regression, in specific regard to the practical utility of modified (sequential) Scheffe-based procedures. Researchers who are concerned with maintaining familywise Type I error rates while increasing statistical power are encouraged to consider these improved multiple-comparison methods.


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