A Confirmatory Factor Analysis Approach to Test Anxiety

Peter F. Halpin, Cibele da-Silva, Paul De Boeck

Research output: Contribution to journalArticlepeer-review


This article addresses the role of test anxiety in aptitude testing. Our approach is rooted in confirmatory factor analysis (CFA). We find that the usual parameter constraints used for model identification in CFA have nontrivial implications for the effects of interest. We suggest 2 methods for dealing with this identification problem. First, we consider testable parameter constraints that identify the proposed model. Second, we consider structural relations that do not depend on model identification. In particular we derive the partial factor correlation between a test and an external variable, conditional on test anxiety, and show that this correlation (a) is not affected by the choice of model identification constraints, and (b) can be estimated using true score theory.

Original languageEnglish (US)
Pages (from-to)455-467
Number of pages13
JournalStructural Equation Modeling
Issue number3
StatePublished - Jul 2014


  • confirmatory factor analysis
  • model identification
  • partial correlation
  • test anxiety

ASJC Scopus subject areas

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


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