A new, more powerful approach to multitrait-multimethod analyses: Application of second-order confirmatory factor analysis.

The advantages of applying confirmatory factor analysis (CFA) to multitrait-multimethod (MTMM) data are widely recognized. However, because CFA. as traditionally applied to MTMM data, incorporates single indicators of each scale (i.e., each trait-method combination), important weaknesses are the failure to (a) correct appropriately for measurement error in scale scores, (b) separate error due to law internal consistency from uniqueness due to weak trait or method effects, (c) test whether items or subscales accurately reflect the intended factor structure, and (d) test for correlated uniquenesses. However, when the analysis begins with multiple indicators of each scale (i.e., items or subscales), second-order factor analysis can be used to address each of these problems. In this approach, first-order factors defined by multiple items or subscales are posited for each scale, and the method and trait factors are posited as second-order factors.