Summary

SEM is a very versatile tool for analyzing MTMM data because it allows the separation of measurement error from method-specific effects and trait influences. Moreover, these models enable researchers to test hypotheses concerning the structure of trait and method effects in a confirmatory way. The SEM approaches in this chapter refer to metrical observed variables, but SEM approaches for ordinal variables (e.g., Muthen, 2002) can be applied to analyze the same MTMM models (Nussbeck, Eid, & Lischetzke, in press). In the case of categorical variables, models of item response theory can be applied (Rost & Walter, chap. 18, this volume). Because of their considerable advantages, MTMM models of SEM have been widely and successfully applied in different areas of psychological research (e.g., Burns & Haynes, chap. 27, this volume; Marsh, Martin, & Hau, chap. 30, this volume).

Chapter 2 1

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