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The Utility of the Bifactor Method for Unidimensionality Assessment When Other Methods Disagree

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  • Yong Luo
  • Khaleel Al-Harbi

Abstract

This article provides an empirical illustration of the utility of the bifactor method for unidimensionality assessment when other methods disagree. Specifically, we used two popular methods for unidimensionality assessment: (a) evaluating the model fit of a one-factor model using Mplus, and (b) DIMTEST to show that different unidimensionality methods may lead to different results, and argued that in such cases the bifactor method can be particularly useful. Those procedures were applied to English Placement Test (EPT), a high-stakes English proficiency test in Saudi Arabia, to determine whether EPT is unidimensional so that a unidimensional item response theory (IRT) model can be used for calibration and scoring. We concluded that despite the inconsistency between the one-factor model approach and DIMTEST, the bifactor method indicates that, for practical purposes, unidimensionality assumption holds for EPT.

Suggested Citation

  • Yong Luo & Khaleel Al-Harbi, 2016. "The Utility of the Bifactor Method for Unidimensionality Assessment When Other Methods Disagree," SAGE Open, , vol. 6(4), pages 21582440166, October.
    • Handle: RePEc:sae:sagope:v:6:y:2016:i:4:p:2158244016674513
    DOI: 10.1177/2158244016674513
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    References listed on IDEAS

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    1. William Stout, 1987. "A nonparametric approach for assessing latent trait unidimensionality," Psychometrika, Springer;The Psychometric Society, vol. 52(4), pages 589-617, December.
    2. Yoshio Takane & Jan Leeuw, 1987. "On the relationship between item response theory and factor analysis of discretized variables," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 393-408, September.
    3. Jinming Zhang & William Stout, 1999. "Conditional covariance structure of generalized compensatory multidimensional items," Psychometrika, Springer;The Psychometric Society, vol. 64(2), pages 129-152, June.
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    Cited by:

    1. Maura A. E. Pilotti, 2021. "What Lies beneath Sustainable Education? Predicting and Tackling Gender Differences in STEM Academic Success," Sustainability, MDPI, vol. 13(4), pages 1-15, February.

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