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Gruppenvergleiche bei hypothetischen Konstrukten: Die Prüfung der Übereinstimmung von Messmodellen mit der Strukturgleichungsmethodik

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  • Temme, Dirk
  • Hildebrandt, Lutz

Abstract

Comparing groups with respect to hypothetical constructs requires that the measurement models are equal across groups. Otherwise conclusions drawn from the observed indicators regarding differences at the latent level (mean differences, differences in the structural relations) might be severly distorted. This article provides a state of the art on how to apply multi-group confirmatory factor analysis to assess measurement invariance. The required steps in the analysis of the observed indicator means and variances/covariances are described, placing special emphasis on how to identify noninvariant indicators. The procedure is demonstrated considering the construct brand strength ("Brand Potential Index", BPI®) introduced by GfK Market Research as an example.

Suggested Citation

  • Temme, Dirk & Hildebrandt, Lutz, 2008. "Gruppenvergleiche bei hypothetischen Konstrukten: Die Prüfung der Übereinstimmung von Messmodellen mit der Strukturgleichungsmethodik," SFB 649 Discussion Papers 2008-042, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    • Handle: RePEc:zbw:sfb649:sfb649dp2008-042
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    References listed on IDEAS

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    More about this item

    Keywords

    Measurement invariance; partial metric invariance; multi-group confirmatory; factor analysis; Brand strength;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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