Linear Confirmatory Factor Models To Evaluate Multitrait-Multimethod Matrices: The Effects of Number of Indicators and Correlation among Methods.

Tomas, Jose M.; Hontangas, Pedro M.; Oliver, Amparo

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Peer reviewed

ERIC Number: EJ625807

Record Type: Journal

Publication Date: 2000

Pages: N/A

Abstractor: N/A

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ISSN: ISSN-0027-3171

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Linear Confirmatory Factor Models To Evaluate Multitrait-Multimethod Matrices: The Effects of Number of Indicators and Correlation among Methods.

Tomas, Jose M.; Hontangas, Pedro M.; Oliver, Amparo

Multivariate Behavioral Research, v35 n4 p469-99 2000

Assessed two models for confirmatory factor analysis of multitrait-multimethod data through Monte Carlo simulation. The correlated traits-correlated methods (CTCM) and the correlated traits-correlated uniqueness (CTCU) models were compared. Results suggest that CTCU is a good alternative to CTCM in the typical multitrait-multimethod matrix, but the CTCM model performs better when multiple indicators per trait-method combination exist. (SLD)

Descriptors: Matrices, Monte Carlo Methods, Multitrait Multimethod Techniques, Simulation

Publication Type: Journal Articles; Reports - Evaluative

Education Level: N/A

Audience: N/A

Language: English

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Authoring Institution: N/A

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