Bias in the Correlated Uniqueness Model for MTMM Data

By J. Conway, Filip Lievens, Steven E. Scullen, C. Lance. 2004

54 citations recorded by the source corpus.

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.

Subfields: Computer Networks and Communications, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/2c54869b8f496724f65f5422736e8f3d24d5dd81

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Richard P. Bagozzi
2. K. Kraus
3. S. Pohl
4. Rolf Steyer

In Management Science and Operations Research

1. Richard P. Bagozzi
2. K. Kraus
3. S. Pohl
4. Rolf Steyer

In Statistics and Probability

1. Richard P. Bagozzi
2. K. Kraus
3. S. Pohl
4. Rolf Steyer

Citations in the corpus

• Modelling method effects as individual causal effects (2007, background): “Finally, the rater effects cannot be related to external variables such as social desirability and, last but not least, the assumption of uncorrelated rater effects can lead to biased estimates for the trait variances and covariances (Conway et al., 2004).”
• Measurement and Meaning in Information Systems and Organizational Research: Methodological and Philosophical Foundations (2011, background): “To the extent that the assumption of uncorrelated method effects is violated, parameter estimates for trait variances and co-variances will be biased (e.g., Conway et al. 2004).”