Abstract
Multimethod data analysis is a complex procedure that is often used to examine the degree to which different measures of the same construct converge in the assessment of this construct. Several authors have called for a greater understanding of the definition and meaning of method effects in different models for multimethod data. In this article, we compare 2 recently proposed approaches for modeling data with structurally different methods with regard to the definition and meaning of method effects, the restricted CT-C(M – 1) model (CitationGeiser, Eid, & Nussbeck, 2008) and the latent difference model (CitationLischetzke, Eid, & Nussbeck, 2002). We also introduce the concepts of individual, conditional, and general method bias and show how these types of biases are represented in the models. An application to a multirater data set (N = 199) as well as recommendations for the application and interpretation of each model are provided.
Notes
1Throughout this article, we assume that the latent variable units of measurement and latent variable means are identified by fixing the loading of one indicator per Tm factor to 1.0 and the intercept of the same indicator to 0.0.
2The difference between the restricted CT-C(M – 1) model and the original CT-C(M – 1) model (as discussed in CitationEid et al., 2003; CitationEid et al., 2008) is that the original CT-C(M – 1) model estimates the loadings of the nonreference indicators on the reference factors (λ* im , m ≠ r) freely, whereas the restricted CT-C(M – 1) model imposes the following constraint on these loadings: λ* im = λ im β mr . Furthermore, if a mean structure is included in the restricted CT-C(M – 1) model, the intercepts of the nonreference indicators, α* im , are constrained to equal α* im = α im + λ im γ mr , where α im is equal to the intercept in the baseline TMU model.
3These two properties are logical consequences of the definition of this factor as a residual variable. See Steyer (1988) and CitationZimmerman (1975) for a detailed discussion of the properties of residual variables.
4Given that hypotheses regarding convergent validity are unidirectional, one-tailed tests of significance were used for these tests.
aModel contains no method factors.
bSelf-report was selected as reference method.
cThe latent differences from the self-report were considered.
dStandardized loadings > |1| are admissible in the LD model, because reference and method factors can be correlated in this model so that these loadings represent partial regression coefficients, which are not restricted to a [−1, +1] interval (e.g., CitationDeegan, 1978).
*p < .05.
**p < .01.
***p < .001.
aSelf-report was selected as reference method.
bThe latent differences from the self-report were considered. All parameters set to 0 by definition are represented by a dash.
*p < .05.
**p < .01.
***p < .001.