Multivariate Behavioral Research· 2012Q1
The Rediscovery of Bifactor Measurement Models
- 2,049citations
- Q1SCImago
- 2012year
Short summary
Bifactor models, which account for a general factor and specific group factors influencing item responses, are re-emerging as a powerful tool for understanding complex psychological constructs.
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Key points
- Bifactor models capture both a general factor and specific group factors influencing item responses.
- The Schmid-Leiman procedure is a historical method, but newer analytic and target bifactor rotations offer advancements.
- Confirmatory bifactor models can be estimated using limited or full-information approaches and compared to nested models.
- Bifactor modeling offers a strong foundation for construct conceptualization and measure evaluation, but has restrictive assumptions.
AI-generated from the title and abstract; the full text is not read.
Abstract
multidimensionality in a set of ordered categorical item responses. I begin by describing the Schmid-Leiman bifactor procedure (Schmid & Leiman, 1957), and highlight its relations with correlated-factors and second-order exploratory factor models. After describing limitations of the Schmid-Leiman, two newer methods of exploratory bifactor modeling are considered, namely, analytic bifactor (Jennrich & Bentler, 2011) and target bifactor rotations (Reise, Moore, & Maydeu-Olivares, 2011). In section two, I discuss limited and full-information estimation approaches to confirmatory bifactor models that have emerged from the item response theory and factor analysis traditions, respectively. Comparison of the confirmatory bifactor model to alternative nested confirmatory models and establishing parameter invariance for the general factor also are discussed. In the final section, important applications of bifactor models are reviewed. These applications demonstrate that bifactor modeling potentially provides a solid foundation for conceptualizing psychological constructs, constructing measures, and evaluating a measure's psychometric properties. However, some applications of the bifactor model may be limited due to its restrictive assumptions.
The authors' abstract, as published at the source. Multivariate Behavioral Research, 2012 · DOI ↗
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Field: Management Science and Operations Research
Management Science and Operations ResearchDecision Sciences