The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Full-Information Item Bifactor Analysis of Graded Response Data
Abstract
A plausible factorial structure for many types of psychological and educational tests exhibits a general factor and one or more group or method factors. This structure can be represented by a bifactor model. The bifactor structure results from the constraint that each item has a nonzero loading on the primary dimension and, at most, one of the group factors. The authors develop estimation procedures for fitting the graded response model when the data follow the bifactor structure. Using maximum marginal likelihood estimation of item parameters, the bifactor restriction leads to a major simplification of the likelihood equations and (a) permits analysis of models with large numbers of group factors, (b) permits conditional dependence within identified subsets of items, and (c) provides more parsimonious factor solutions than an unrestricted full-information item factor analysis in some cases. Analysis of data obtained from 586 chronically mentally ill patients revealed a clear bifactor structure.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Statistical Theories of Mental Test Scores
Rozeboom, W. W., Lord, F. M., Novick, M. R., & Birnbaum, A. (1969) · American Educational Research Journal · doi:10.2307/1162101 · Cited by 8,022
A Rasch model for partial credit scoring
Masters, G. N. (1982) · Psychometrika · doi:10.1007/bf02296272 · Cited by 3,782
Flora, D. B., & Curran, P. J. (2004) · Psychological Methods · doi:10.1037/1082-989x.9.4.466 · Cited by 3,019
ESTIMATION OF LATENT ABILITY USING A RESPONSE PATTERN OF GRADED SCORES1
Samejima, F. (1968) · ETS Research Bulletin Series · doi:10.1002/j.2333-8504.1968.tb00153.x · Cited by 2,587
A General Approach to Confirmatory Maximum Likelihood Factor Analysis
Jöreskog, K. G. (1969) · Psychometrika · doi:10.1007/bf02289343 · Cited by 2,489
Marginal Maximum Likelihood Estimation of Item Parameters: Application of an EM Algorithm
Bock, R. D., & Aitkin, M. (1981) · Psychometrika · doi:10.1007/bf02293801 · Cited by 2,339
Self-citationMuthén, B. (1984) · Psychometrika · doi:10.1007/bf02294210 · Cited by 1,544
Stroud, A. H., & Secrest, D. (1966) · Cited by 1,391
L., Y. L., Stroud, A. H., & Secrest, D. (1967) · Mathematics of Computation · doi:10.2307/2003493 · Cited by 1,266
A quality of life interview for the chronically mentally ill
Lehman, A. F. (1988) · Evaluation and Program Planning · doi:10.1016/0149-7189(88)90033-x · Cited by 1,083
Cited by
mirt: A Multidimensional Item Response Theory Package for the R Environment
Chalmers, R. P. (2012) · Journal of Statistical Software · doi:10.18637/jss.v048.i06 · Cited by 2,643
Pilkonis, P. A., Choi, S. W., Reise, S. P., Stover, A. M., Riley, W. T., Cella, D., & PROMIS Cooperative Group (2011) · Assessment · doi:10.1177/1073191111411667 · Cited by 2,132
Self-citationThe role of the bifactor model in resolving dimensionality issues in health outcomes measures
Reise, S. P., Morizot, J., & Hays, R. D. (2007) · Quality of Life Research · doi:10.1007/s11136-007-9183-7 · Cited by 747
A meta-analytic investigation of the structure of posttraumatic stress disorder symptoms.
Yufik, T., & Simms, L. J. (2010) · Journal of Abnormal Psychology · doi:10.1037/a0020981 · Cited by 323
Willoughby, M. T., The Family Life Project Investigators, Blair, C. B., Wirth, R. J., & Greenberg, M. (2010) · Psychological Assessment · doi:10.1037/a0018708 · Cited by 280
Metadata
- Authors
- Gibbons, R. D., Bock, R. D., Hedeker, D., Weiss, D. J., Segawa, E., Bhaumik, D. K., Kupfer, D. J., Frank, E., Grochocinski, V. J., & Stover, A.
- Venue
- Applied Psychological Measurement
- Publisher
- SAGE Publications
- Published
- 2007-01
- Volume
- 31
- Issue
- 1
- Pages
- 4-19
- ISSN
- 0146-6216 (ISSN-L)
- 1552-3497
- OpenAlex
- W2040455338
- Cited by
- 269
- References
- 26
- FWCI
- 10.07
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Full-Information Item Bifactor Analysis of Graded Response Data. https://app.cochat.ai/papers/10.1177/0146621606289485
- The paper
- Gibbons, R. D., Bock, R. D., Hedeker, D., Weiss, D. J., Segawa, E., Bhaumik, D. K., Kupfer, D. J., Frank, E., Grochocinski, V. J., & Stover, A. (2007). Full-Information Item Bifactor Analysis of Graded Response Data. Applied Psychological Measurement. https://doi.org/10.1177/0146621606289485
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
