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dc.contributor.advisorBorich, Gary D.en
dc.creatorLockhart, Lester Lelanden
dc.date.accessioned2011-07-25T20:23:54Zen
dc.date.available2011-07-25T20:23:54Zen
dc.date.issued2011-05en
dc.date.submittedMay 2011en
dc.identifier.urihttp://hdl.handle.net/2152/ETD-UT-2011-05-2733en
dc.descriptiontexten
dc.description.abstractMediational analysis quantifies proposed causal mechanisms through which treatments act on outcomes. In the presence of clustered data, conventional multiple regression mediational methods break down, requiring the use of hierarchical linear modeling techniques. As an additional consideration, nonlinear relationships in multilevel mediation models require unique specifications that are ignored if modeled linearly. Improper specification of nonlinear relationships can lead to a consistently overestimated mediated effect. This has direct implications for inferences regarding intervention causality and efficacy. The current investigation proposes a nonlinear multilevel mediation model to account for nonlinear relationships in clustered data. A simulation study is proposed to compare the statistical performance of the proposed nonlinear multilevel mediation model with that of conventional methods.en
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.subjectNonlinear mediationen
dc.subjectProgram evaluationen
dc.titleNonlinear mediation in clustered data : a nonlinear multilevel mediation modelen
dc.date.updated2011-07-25T20:24:00Zen
dc.identifier.slug2152/ETD-UT-2011-05-2733en
dc.contributor.committeeMemberBeretvas, Susan N.en
dc.description.departmentEducational Psychologyen
dc.type.genrethesisen
thesis.degree.departmentEducational Psychologyen
thesis.degree.disciplineEducational Psychologyen
thesis.degree.grantorUniversity of Texas at Austinen
thesis.degree.levelMastersen
thesis.degree.nameMaster of Artsen


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