Multivariate Linear Models of the Multitrait-Multimethod Matrix.

Several multivariate statistical methodologies have been proposed to ensure objective and quantitative evaluation of the multitrait-multimethod matrix. The paper examines the performance of confirmatory factor analysis and covariance component models. It is shown, both empirically and formally, that confirmatory factor analysis is not a reliable method for simultaneous estimation of trait and method factors. The poor performance is due to an inherent rotational indeterminacy common to all factor analytic models of trait and method effects. Covariance component analysis, on the other hand, shows a more parsimonious parameterization of general, trait, and method variation in the multitrait-multimethod matrix and is therefore typically unaffected by rotational indeterminacies. The performance with 23 empirical multitrait-multimethod correlation matrices was also found satisfactory. (Author)