Publication Type
Journal Article
Version
acceptedVersion
Publication Date
1-2004
Abstract
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.
Keywords
Computer simulation, Correlation methods, Mathematical models, Matrix algebra, Parameter estimation
Discipline
Human Resources Management | Organizational Behavior and Theory
Research Areas
Organisational Behaviour and Human Resources
Publication
Structural Equation Modeling
Volume
11
Issue
4
First Page
535
Last Page
559
ISSN
1070-5511
Identifier
10.1207/s15328007sem1104_3
Publisher
Taylor & Francis (Routledge): STM, Behavioural Science and Public Health Titles
Citation
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.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/5588
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1207/s15328007sem1104_3