TY - JOUR
T1 - A Comparison of Method Effects in Two Confirmatory Factor Models for Structurally Different Methods
AU - Geiser, Christian
AU - Eid, Michael
AU - West, Stephen
AU - Lischetzke, Tanja
AU - Nussbeck, Fridtjof W.
N1 - Funding Information:
Stephen G. West was supported by a Forschungspreis from the Alexander von Foundation. We are grateful to Martin Schultze for his help in creating the tables.
PY - 2012/7
Y1 - 2012/7
N2 - 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 (Geiser, Eid, & Nussbeck, 2008) and the latent difference model (Lischetzke, 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.
AB - 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 (Geiser, Eid, & Nussbeck, 2008) and the latent difference model (Lischetzke, 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.
KW - CT-C(M - 1)
KW - confirmatory factor analysis
KW - latent difference
KW - method effects
KW - multitrait-multimethod analysis
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U2 - 10.1080/10705511.2012.687658
DO - 10.1080/10705511.2012.687658
M3 - Article
AN - SCOPUS:84864658895
SN - 1070-5511
VL - 19
SP - 409
EP - 436
JO - Structural Equation Modeling
JF - Structural Equation Modeling
IS - 3
ER -