The role of the bifactor model in resolving dimensionality issues in health outcomes measures
Abstract
Objectives We propose the application of a bifactor model for exploring the dimensional structure of an item response matrix, and for handling multidimensionality. Background We argue that a bifactor analysis can complement traditional dimensionality investigations by: (a) providing an evaluation of the distortion that may occur when unidimensional models are fit to multidimensional data, (b) allowing researchers to examine the utility of forming subscales, and, (c) providing an alternative to non-hierarchical multidimensional models for scaling individual differences. Method To demonstrate our arguments, we use responses (N = 1,000 Medicaid recipients) to 16 items in the Consumer Assessment of Healthcare Providers and Systems (CAHPS2.0) survey. Analyses Exploratory and confirmatory factor analytic and item response theory models (unidimensional, multidimensional, and bifactor) were estimated. Results CAHPS items are consistent with both unidimensional and multidimensional solutions. However, the bifactor model revealed that the overwhelming majority of common variance was due to a general factor. After controlling for the general factor, subscales provided little measurement precision. Conclusion The bifactor model provides a valuable tool for exploring dimensionality related questions. In the Discussion, we describe contexts where a bifactor analysis is most productively used, and we contrast bifactor with multidimensional IRT models (MIRT). We also describe implications of bifactor models for IRT applications, and raise some limitations.
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The ratio of the first to the second eigenvalue (4.38) suggests that the AAQ-II is probably a unidimensional measure represented by only one factor.
“This ratio of the first to the second eigenvalue (i.e., 4.38) suggests that this is probably a unidimensional measure and, thus, is represented by only one factor (Reise, Morizot & Hays, 2007; Robins, Fraley & Krueger, 2007).”
From Preliminary Psychometric Properties of the Acceptance and Action Questionnaire–II: A Revised Measure of Psychological Inflexibility and Experiential Avoidance (2011) · cites this paper as Reise, Morizot & Hays, 2007
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- Authors
- Reise, S. P., Morizot, J., & Hays, R. D.
- Affiliations
- University of California, Los Angeles (US)
- Corresponding author
- Reise, Steven P.
- Venue
- Quality of Life Research
- Published
- 2007-05-04
- Volume
- 16
- Issue
- S1
- Pages
- 19-31
- ISSN
- 0962-9343 (ISSN-L)
- 1573-2649
- OpenAlex
- W2088832685
- Cited by
- 747
- References
- 1
- Citations by year
- 2026: 22 · 2025: 20 · 2024: 25 · 2023: 39 · 2022: 37 · 2021: 58 · 2020: 36 · 2019: 58 · 2018: 53 · 2017: 45 · 2016: 55 · 2015: 49 · 2014: 54 · 2013: 56 · 2012: 46
- FWCI
- 24.88
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Quality of Life Research (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5p20md000148-05)
- Agency for Healthcare Research and Quality (5 U18 HS00924)
- National Institute on Aging (AG-02-004)
- National Institute on Minority Health and Health Disparities (P20-MD00148-01)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Keywords
- bifactor model, dimensionality, multidimensionality, item response theory, multidimensional item response theory, general factor, subscales, measurement precision, Medicaid beneficiaries, individual differences
- MeSH terms
- Factor Analysis, Statistical, Health Status, Humans, Models, Theoretical, Pilot Projects, Surveys and Questionnaires, Research, Models, Statistical, Outcome Assessment, Health Care
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