Type I error rates and power of robust chi-square difference tests in investigations of measurement invariance ...
A Monte Carlo simulation study was conducted to investigate Type I error rates and power of several corrections for non-normality to the normal theory chi-square difference test in the context of evaluating measurement invariance via Structural Equation Modeling (SEM). Studied statistics include: 1)...
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ftdatacite:10.14288/1.0166587 2024-04-28T08:17:08+00:00 Type I error rates and power of robust chi-square difference tests in investigations of measurement invariance ... Brace, Jordan 2015 https://dx.doi.org/10.14288/1.0166587 https://doi.library.ubc.ca/10.14288/1.0166587 en eng University of British Columbia article-journal Text ScholarlyArticle 2015 ftdatacite https://doi.org/10.14288/1.0166587 2024-04-02T09:28:28Z A Monte Carlo simulation study was conducted to investigate Type I error rates and power of several corrections for non-normality to the normal theory chi-square difference test in the context of evaluating measurement invariance via Structural Equation Modeling (SEM). Studied statistics include: 1) the uncorrected difference test, DML, 2) Satorra’s (2000) original computationally intensive correction, DS0, 3) Satorra and Bentler’s (2001) simplified correction, DSB1, 4) Satorra and Bentler’s (2010) strictly positive correction, DSB10, and 5) a hybrid procedure, DSBH (Asparouhov & Muthén, 2010), which is equal to DSB1 when DSB1 is positive, and DSB10 when DSB1 is negative. Multiple-group data were generated from confirmatory factor analytic models invariant on some but not all parameters. A series of six nested invariance models was fit to each generated dataset. Population parameter values had little influence on the relative performance of the scaled statistics, while level of invariance being tested ... Text DML DataCite Metadata Store (German National Library of Science and Technology) |
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A Monte Carlo simulation study was conducted to investigate Type I error rates and power of several corrections for non-normality to the normal theory chi-square difference test in the context of evaluating measurement invariance via Structural Equation Modeling (SEM). Studied statistics include: 1) the uncorrected difference test, DML, 2) Satorra’s (2000) original computationally intensive correction, DS0, 3) Satorra and Bentler’s (2001) simplified correction, DSB1, 4) Satorra and Bentler’s (2010) strictly positive correction, DSB10, and 5) a hybrid procedure, DSBH (Asparouhov & Muthén, 2010), which is equal to DSB1 when DSB1 is positive, and DSB10 when DSB1 is negative. Multiple-group data were generated from confirmatory factor analytic models invariant on some but not all parameters. A series of six nested invariance models was fit to each generated dataset. Population parameter values had little influence on the relative performance of the scaled statistics, while level of invariance being tested ... |
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Text |
author |
Brace, Jordan |
spellingShingle |
Brace, Jordan Type I error rates and power of robust chi-square difference tests in investigations of measurement invariance ... |
author_facet |
Brace, Jordan |
author_sort |
Brace, Jordan |
title |
Type I error rates and power of robust chi-square difference tests in investigations of measurement invariance ... |
title_short |
Type I error rates and power of robust chi-square difference tests in investigations of measurement invariance ... |
title_full |
Type I error rates and power of robust chi-square difference tests in investigations of measurement invariance ... |
title_fullStr |
Type I error rates and power of robust chi-square difference tests in investigations of measurement invariance ... |
title_full_unstemmed |
Type I error rates and power of robust chi-square difference tests in investigations of measurement invariance ... |
title_sort |
type i error rates and power of robust chi-square difference tests in investigations of measurement invariance ... |
publisher |
University of British Columbia |
publishDate |
2015 |
url |
https://dx.doi.org/10.14288/1.0166587 https://doi.library.ubc.ca/10.14288/1.0166587 |
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DML |
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DML |
op_doi |
https://doi.org/10.14288/1.0166587 |
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1797581906094587904 |