This simulation investigates bias in trait factor loadings and intercorrelations when analyzing multitrait-multimethod (MTMM) data using the correlated uniqueness (CU) confirmatory factor analysis (CFA) model. A theoretical weakness of the CU model is the assumption of uncorrelated methods. However, previous simulation studies have shown little bias in trait estimates even when true method correlations are large. We hypothesized that there would be substantial bias when both method factor correlations and method factor loadings were large. We generated simulated sample data using population parameters based on our review of actual MTMM results. Results confirmed the prediction; substantial bias occurred in trait factor loadings and correlations when both method loadings and method correlations were large.
Computer simulation, Correlation methods, Mathematical models, Matrix algebra, Parameter estimation
Human Resources Management | Organizational Behavior and Theory
Organisational Behaviour and Human Resources
Structural Equation Modeling
Taylor & Francis (Routledge): STM, Behavioural Science and Public Health Titles
CONWAY, James M.; LIEVENS, Filip; SCULLEN, Steven E.; and LANCE, Charles E..
Bias in the correlated uniqueness model for MTMM data. (2004). Structural Equation Modeling. 11, (4), 535-559. Research Collection Lee Kong Chian School Of Business.
Available at: http://ink.library.smu.edu.sg/lkcsb_research/5588
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