A Comparison of Method Effects in Two Confirmatory Factor Models for Structurally Different Methods

Christian Geiser, Michael Eid, Stephen West, Tanja Lischetzke, Fridtjof W. Nussbeck

Research output: Contribution to journalArticle

30 Scopus citations

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 (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.

Original languageEnglish (US)
Pages (from-to)409-436
Number of pages28
JournalStructural Equation Modeling
Volume19
Issue number3
DOIs
StatePublished - Jul 1 2012

Keywords

  • CT-C(M - 1)
  • confirmatory factor analysis
  • latent difference
  • method effects
  • multitrait-multimethod analysis

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Modeling and Simulation
  • Sociology and Political Science
  • Economics, Econometrics and Finance(all)

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