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Rhemtulla, Mijke; Brosseau-Liard, Patricia E.; Savalei, Victoria – Psychological Methods, 2012
A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…
Descriptors: Factor Analysis, Computation, Simulation, Sample Size
Shujuan, Wang; Meihua, Qian; Jianxin, Zhang – Journal of Psychoeducational Assessment, 2009
This article examines the psychometric structure of the Anxiety Control Questionnaire (ACQ) in Chinese adolescents. With the data collected from 212 senior high school students (94 females, 110 males, 8 unknown), seven models are tested using confirmatory factor analyses in the framework of the multitrait-multimethod strategy. Results indicate…
Descriptors: Multitrait Multimethod Techniques, Factor Structure, Adolescents, Measures (Individuals)
Cole, David A.; Ciesla, Jeffrey A.; Steiger, James H. – Psychological Methods, 2007
In practice, the inclusion of correlated residuals in latent-variable models is often regarded as a statistical sleight of hand, if not an outright form of cheating. Consequently, researchers have tended to allow only as many correlated residuals in their models as are needed to obtain a good fit to the data. The current article demonstrates that…
Descriptors: Research Design, Multitrait Multimethod Techniques, Measurement Techniques, Correlation
Marsh, Herbert W.; Grayson, David – 1993
The multitrait-multimethod (MTMM) paradigm is used widely to assess construct validity, but D. A. Kenny and D. A. Kashy (1992) lament that even after 30 years we still do not know how to analyze MTMM data. The Composite Direct Product (CDP) model has recently attracted considerable attention. Its strengths and weaknesses are evaluated, and a…
Descriptors: Computer Simulation, Construct Validity, Foreign Countries, Formative Evaluation