The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Assessing the Quality and Appropriateness of Factor Solutions and Factor Score Estimates in Exploratory Item Factor Analysis
Open accessAbstract
This article proposes a comprehensive approach for assessing the quality and appropriateness of exploratory factor analysis solutions intended for item calibration and individual scoring. Three groups of properties are assessed: (a) strength and replicability of the factorial solution, (b) determinacy and accuracy of the individual score estimates, and (c) closeness to unidimensionality in the case of multidimensional solutions. Within each group, indices are considered for two types of factor-analytic models: the linear model for continuous responses and the categorical-variable-methodology model that treats the item scores as ordered-categorical. All the indices proposed have been implemented in a noncommercial and widely known program for exploratory factor analysis. The usefulness of the proposal is illustrated with a real data example in the personality domain.
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
Buss, A. H., & Perry, M. (1992) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.63.3.452 · Cited by 4,693
Rhemtulla, M., Brosseau-Liard, P. É., & Savalei, V. (2012) · Psychological Methods · doi:10.1037/a0029315 · Cited by 2,816
The Rediscovery of Bifactor Measurement Models
Reise, S. P. (2012) · Multivariate Behavioral Research · doi:10.1080/00273171.2012.715555 · Cited by 2,112 · cited 2×
“, Hancock & Mueller, 2000), but recently, Rodriguez, Reise, and Haviland (2016a, 2016b) have put forward a well-organized proposal in the context of bifactor FA solutions (Reise, 2012).”
BackgroundEvaluating Bifactor Models: Calculating and Interpreting Statistical Indices
Rodriguez, A., Reise, S. P., & Haviland, M. G. (2016) · Psychological Methods · doi:10.1037/met0000045 · Cited by 1,599
Scoring and Modeling Psychological Measures in the Presence of Multidimensionality
Reise, S. P., Bonifay, W. E., & Haviland, M. G. (2013) · Journal of Personality Assessment · doi:10.1080/00223891.2012.725437 · Cited by 1,069
Applying Bifactor Statistical Indices in the Evaluation of Psychological Measures
Rodriguez, A., Reise, S. P., & Haviland, M. G. (2016) · Journal of Personality Assessment · doi:10.1080/00223891.2015.1089249 · Cited by 990
Cited by
Psychometric Properties of the Climate Change Worry Scale
Stewart, A. E. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18020494 · Cited by 286
Wlodarczyk, A., Zumeta, L., Pizarro, J. J., Bouchat, P., Hatibovic, F., Basabe, N., & Rimé, B. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.01721 · Cited by 65
Lorenzo-Seva, U., Calderon, C., Ferrando, P. J., del Mar Muñoz, M., Beato, C., Ghanem, I., Castelo, B., Carmona-Bayonas, A., Hernández, R., & Jiménez-Fonseca, P. (2019) · Quality of Life Research · doi:10.1007/s11136-019-02106-y · Cited by 57
Self-citationLecavalier, L., Bodfish, J., Harrop, C., Whitten, A., Jones, D., Pritchett, J., Faldowski, R., & Boyd, B. (2020) · Autism Research · doi:10.1002/aur.2257 · Cited by 40
Paladines-Costa, B., López-Guerra, V., Ruisoto, P., Vaca-Gallegos, S., & Cacho, R. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18062944 · Cited by 37
“Other indicators, such as UniCo, ECV, and MIREAL, proposed by Ferrando and Lorenzo-Seva [34], also suggested unidimensionality, consistent with the original study [1] and with other versions (Hungary [11], Greece [12], Brazil [16], Spain [6], and Colombia [7]).”
Result
Metadata
- Authors
- Ferrando, P. J., & Lorenzo-Seva, U.
- Venue
- Educational and Psychological Measurement
- Publisher
- SAGE Publications
- Published
- 2017-07-07
- Volume
- 78
- Issue
- 5
- Pages
- 762-780
- ISSN
- 0013-1644 (ISSN-L)
- 1552-3888
- OpenAlex
- W2779971212
- Cited by
- 581
- References
- 6
- FWCI
- 15.23
- Type
- journal article
- Language
- en
- Open access
- green
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: Assessing the Quality and Appropriateness of Factor Solutions and Factor Score Estimates in Exploratory Item Factor Analysis. https://app.cochat.ai/papers/10.1177/0013164417719308
- The paper
- Ferrando, P. J., & Lorenzo-Seva, U. (2018). Assessing the Quality and Appropriateness of Factor Solutions and Factor Score Estimates in Exploratory Item Factor Analysis. Educational and Psychological Measurement. https://doi.org/10.1177/0013164417719308
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.
