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dc.contributor.authorSiminovsky, Allison Bari
dc.date.accessioned2014-03-04T21:04:08Z
dc.date.available2014-03-04T21:04:08Z
dc.date.issued2013-05
dc.identifier.othersiminovsky_allison_b_201305_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/siminovsky_allison_b_201305_ms
dc.identifier.urihttp://hdl.handle.net/10724/28905
dc.description.abstractAssessment centers (ACs) have remained a popular selection and development tool for years. Although ACs often demonstrate criterion-related validity, researchers have struggled with finding content validity for AC dimensions. The problem exists for two reasons: nonconvergence and inadmissibility issues when using the MTMM framework, and dominance of dimension variance by exercise variance. The current study reexamined previously reported AC matrices, reclassified using three different schemes of broad dimension factors in order to increase each model’s indicator-to-factor ratio to promote convergence and admissibility. Additionally, a number of design modifications were examined as to their influence on increasing dimension variance. Results show a significant increase in convergence and admissibility rates as indicator-to-factor ratio increases. However, the remaining analyses reached inconclusive and nonsignificant results. Possible explanations for these results are discussed, as well as ramifications for the findings.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectAssessment Center
dc.subjectMTMM
dc.subjectConstruct Validity
dc.subjectIndicator-to-Factor Ratio
dc.subjectDimension Factors
dc.titleAssessment center construct validity
dc.title.alternativemethodological and design modifications
dc.typeThesis
dc.description.degreeMS
dc.description.departmentPsychology
dc.description.majorPsychology
dc.description.advisorChuck Lance
dc.description.committeeChuck Lance
dc.description.committeeRobert Mahan


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