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ERIC Number: EJ746798
Record Type: Journal
Publication Date: 2006
Pages: 41
Abstractor: Author
Reference Count: N/A
ISBN: N/A
ISSN: ISSN-0027-3171
The Performance of Cross-Validation Indices Used to Select among Competing Covariance Structure Models under Multivariate Nonnormality Conditions
Whittaker, Tiffany A.; Stapleton, Laura M.
Multivariate Behavioral Research, v41 n3 p295-335 2006
Cudeck and Browne (1983) proposed using cross-validation as a model selection technique in structural equation modeling. The purpose of this study is to examine the performance of eight cross-validation indices under conditions not yet examined in the relevant literature, such as nonnormality and cross-validation design. The performance of each cross-validation index was measured in terms of true model selection rate as well as consistency of model selection. The performance of the cross-validation indices tended to improve as factor loading and sample size increased but performed less well as nonnormality increased. The double cross-validated indices outperformed their simple cross-validated counterparts in certain conditions. Recommendations are provided as to which cross-validation methods would optimally perform in a given condition.
Lawrence Erlbaum Associates, Inc. 10 Industrial Avenue, Mahwah, NJ 07430. Tel: 800-926-6579; Tel: 201-258-2200; Fax: 201-236-0072; e-mail: journals@erlbaum.com; Web site: https://www.erlbaum.com
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A