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dc.contributor.authorFan, Yi
dc.date.accessioned2016-02-11T05:30:40Z
dc.date.available2016-02-11T05:30:40Z
dc.date.issued2015-08
dc.identifier.otherfan_yi_201508_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/fan_yi_201508_ms
dc.identifier.urihttp://hdl.handle.net/10724/34188
dc.description.abstractThis study evaluated a neglected parameterization approach by Rindskof (1984) and its application to analyzing Multitrait-Multimethod (MTMM) data. Through taking analyses on a Monte Carlo simulation study and a large review of MTMM studies, I examined the Rindskopf raparameterization model (CTCM-R model) and compared its performance with the other two widely applied CFA-MTMM models, namely, the correlated trait-correlated method model (CTCM) and the correlated trait-correlated uniqueness model (CTCU), in regards to their convergence, admissibility, model fit, and parameter estimation biases. Results from analyzing both simulated MTMM data and previous published MTMM data showed that the CTCM-R model serves as a favorable alternative approach to MTMM studies.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectMultitrait-Multimethod
dc.subjectMonte Carlo Simulation
dc.subjectRindskopf Reparameterization
dc.titleExhuming the Rindskopf reparameterization
dc.title.alternativea comparison of three alternatives to the analysis of MTMM data
dc.typeThesis
dc.description.degreeMS
dc.description.departmentPsychology
dc.description.majorPsychology
dc.description.advisorNathan Carter
dc.description.committeeNathan Carter
dc.description.committeeRobert Mahan
dc.description.committeeKarl Kuhnert


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