Race, personal history characteristics, and vocational rehabilitation outcomes : a structural equation modeling approach

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dc.contributor.advisor Sorrells , Audrey McCray
dc.creator Martin , Frank H .
dc.date.accessioned 2009 -10 -19T20 :27 :18Z
dc.date.accessioned 2014 -02 -19T22 :36 :32Z
dc.date.available 2009 -10 -19T20 :27 :18Z
dc.date.available 2014 -02 -19T22 :36 :32Z
dc.date.created 2009 -05
dc.date.issued 2009 -10 -19T20 :27 :18Z
dc.identifier.uri http : / /hdl .handle .net /2152 /6569
dc.description.abstract Numerous studies have indicated racial and ethnic disparities in the vocational rehabilitation (VR ) system , including differences in eligibility , services provided , and employment outcomes . Few of these studies , however , have utilized advanced multivariate techniques or latent constructs to measure quality of employment outcomes (QEO ) or tested hypothesized models for the relationship between race , personal history characteristics , and VR outcomes . Furthermore , few VR disparities studies have examined southwestern states such as Texas , which has large Hispanic and Black populations . The purpose of this study was to utilize structural equation modeling (SEM ) to examine several implied conceptual models for the relationship between race , personal history characteristics , and VR outcomes for White , Black , and Hispanic participants in the Texas VR system . The implied conceptual models were tested for goodness of fit and multiple -group invariance . A measurement model for QEO , a latent construct , was tested and used in the study . QEO was measured by three indicator variables and evaluated using confirmatory factor analysis . A MIMIC model was tested to assess racial /ethnic variation in QEO . The MIMIC results were compared to a multiple regression approach . In addition , a path model and logistic regressions were conducted to assess racial variation in VR closure status among consumers who were unemployed at application to VR . All models were retested with an independent sample to assess predictive validity . The study results indicated good model fit and measurement invariance for the QEO construct . The structural model for race , personal history characteristics , and QEO indicated moderate model fit . It also indicated interaction effects for race by gender and for race by public support . The MIMIC model results suggest that QEO decreased for Blacks and Hispanics compared to Whites . Furthermore , the MIMIC results , which utilized QEO as an endogenous variable , differed from the multiple regression findings , which utilized one criterion . The multiple regression findings indicated no statistically significant difference between Blacks and Whites . The path model for race and VR closure status indicated poor model fit . The logistic regression indicated no racial /ethnic differences in VR closure status . Several model estimates did not cross -validate . Study limitations and suggestions for future research are described . en_US
dc.format.medium electronic
dc.language.iso eng en_US
dc.rights Copyright © is held by the author . Presentation of this material on the Libraries' web site by University Libraries , The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works .
dc.subject Vocational rehabilitation en_US
dc.subject Racial disparity en_US
dc.subject Ethnic disparity en_US
dc.subject Employment outcomes en_US
dc.subject Structural equation modeling en_US
dc.title Race , personal history characteristics , and vocational rehabilitation outcomes : a structural equation modeling approach en_US
dc.description.department Special Education en_US
dc.type.genre Thesis
dc.type.material text
thesis.degree.name Doctor of Philosophy en_US
thesis.degree.level Doctoral en_US
thesis.degree.discipline Special Education en_US
thesis.degree.grantor The University of Texas at Austin
thesis.degree.department Special Education en_US

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Race, personal history characteristics, and vocational rehabilitation outcomes : a structural equation modeling approach. Doctoral dissertation, The University of Texas at Austin. Available electronically from http : / /hdl .handle .net /2152 /6569 .

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