Multitrait-Multimethod Analyses: Inferring Each Trait-Method Combination With Multiple Indicators
Herbert W. Marsh · Applied Measurement in Education · 1993
The Campbell and Fiske (1959) guidelines are used extensively for examining multitrait-multimethod data. Although their logic and heuristic value are widely accepted, the guidelines are criticized for being based on correlations among observed variables instead of correlations among latent constructs. Therefore, researchers have developed latent variable models for multitrait- multimethod data that provide information more closely related to the Campbell-Fiske guidelines. In these latent variable approaches, a single scale score, which is often an average of multiple items used to infer the trait being measured, is typically used to represent each trait-method combination. When individual items (or item parcels) are used as multiple indicators of that scale, however, each trait-method combination can be represented as a latent construct, and the Campbell-Fiske guidelines can be applied to correlations among latent constructs, thereby removing a major objection to their use. Furthermore, latent variable approaches can be applied to correlations among latent variables in much the same way as they are applied to correlations among measured variables. For example, in the present investigation, a first-order factor defined by multiple indicators is posited for each trait-method combination, and method and trait factors are posited as second-order factors. This hierarchical approach addresses important weak- nesses in the confirmatory factor analysis approach to multitrait-multi- method.