A Multilevel CFA-MTMM Model for Nested Structurally Different Methods

The numerous advantages of structural equation modeling (SEM) for the analysis of multitrait-multimethod (MTMM) data are well known. MTMM-SEMs allow researchers to explicitly model the measurement error, to examine the true convergent and discriminant validity of the given measures, and to relate external variables to the latent trait as well as the latent method factors in the model. According to Eid et al. (2008) different MTMM measurement designs require different types of MTMM-SEMs. Eid et al. (2008) proposed three different MTMM-SEMs for measurement designs with (a) structurally different methods, (b) interchangeable methods, and (c) a combination of both types of methods. In the present work, we extend this taxonomy to a multilevel correlated traits--correlated methods minus one [CTC(M?-?1)] model for nested structurally different methods. The new model enables researchers to study method effects on both measurement levels (i.e., within and between clusters, classes, schools, etc.) and evaluate the convergent and discriminant validity of the measures. The statistical performance of the model is examined by a simulation study, and recommendations for the application of the model are given.