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

Joseph F. Hair, Barry J. Babin, Nina Krey

Research output: Contribution to journalArticlepeer-review

153 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)163-177
Number of pages15
JournalJournal of Advertising
Volume46
Issue number1
DOIs
StatePublished - Jan 2 2017

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Communication
  • Marketing

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