Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally w...
Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares
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New York: Springer US
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English
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New York: Springer US
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In confirmatory factor analysis (CFA), the use of maximum likelihood (ML) assumes that the observed indicators follow a continuous and multivariate normal distribution, which is not appropriate for ordinal observed variables. Robust ML (MLR) has been introduced into CFA models when this normality assumption is slightly or moderately violated. Diago...
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Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares
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TN_cdi_proquest_miscellaneous_1815680766
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_1815680766
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E-ISSN
1554-3528
DOI
10.3758/s13428-015-0619-7
