Bias in the correlated uniqueness model for MTMM data

• Main Authors: CONWAY, James M., LIEVENS, Filip, SCULLEN, Steven E., LANCE, Charles E.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2004
• Subjects: Computer simulation; Correlation methods; Mathematical models; Matrix algebra; Parameter estimation; Human Resources Management; Organizational Behavior and Theory
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/5588; https://ink.library.smu.edu.sg/context/lkcsb_research/article/6587/viewcontent/cu.pdf
• Institution: Singapore Management University

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.