Covariance-Based Structural Equation Modeling in the Journal of Advertising: Review and Recommendations

In this article, we review applications of covariance-based structural equation modeling (SEM) in the Journal of Advertising (JA) starting with the first issue in 1972. We identify 111 articles from the earliest application of SEM in 1983 through 2015, and discuss important methodological issues rel...

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Veröffentlicht in:Journal of advertising Jg. 46; H. 1; S. 163 - 177
Hauptverfasser: Hair, Joseph F., Babin, Barry J., Krey, Nina
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Abingdon Routledge 01.01.2017
Taylor & Francis Group, LLC
Taylor & Francis Ltd
Schlagworte:
Advertisements
Advertising
Analysis of covariance
Best practice
Causal models
Confirmatory factor analysis
Discriminant analysis
Factor analysis
Group psychotherapy
Methodological problems
Quantitative Research
Structural analysis
Structural equation modeling
Terminology
ISSN:0091-3367, 1557-7805
Online-Zugang:Volltext
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Zusammenfassung:In this article, we review applications of covariance-based structural equation modeling (SEM) in the Journal of Advertising (JA) starting with the first issue in 1972. We identify 111 articles from the earliest application of SEM in 1983 through 2015, and discuss important methodological issues related to the following aspects: confirmatory factor analysis (CFA), causal modeling, multiple group analysis, reporting, and guidelines for interpretation of results. Moreover, we summarize some issues related to varying terminology associated with different SEM methods. Findings indicate that the use of SEM in the JA contributes greatly to conceptual, empirical, and methodological advances in advertising research. The assessment contributes to the literature by offering advertising researchers a summary guide to best practices and a reminder of the basics that distinguish the powerful and unique approach involving structural analysis of covariances.
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ISSN:0091-3367
1557-7805
DOI:10.1080/00913367.2017.1281777