The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
The Effects of Item Parceling on Goodness-of-Fit and Parameter Estimate Bias in Structural Equation Modeling
Abstract
Two simulation studies were conducted to investigate the effects of the practice of item parceling. In Study 1, unidimensional sets of normally and nonnormally distributed item-level data were categorized into 2-, 3-, and 4-item parcels. Analyses revealed that the use of item parcels resulted in better fitting solutions, as measured by the root mean squared error of approximation (RMSEA), comparative fit index (CFI), and chi-square test, when items had a unidimensional structure. Parceled solutions also resulted in less bias in estimates of structural parameters under these conditions than did solutions based on the individual items. In Study 2 the issue of whether the use of item parceling could mask a known multidimensional factor structure among a set of items was investigated. Results indicated that certain types of item parceling can obfuscate a multidimensional factor structure in such a way that acceptable values of fit indexes are found for a misspecified solution. In addition, parceling under these conditions was found to result in bias in the estimates of structural parameters. Although parceling can ameliorate the effects of coarsely categorized and nonnormally distributed item-level data when the items are unidimensional, the use of parceling with items that are multidimensional or for which the factor structure is unknown cannot be recommended.
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
Hu, L., & Bentler, P. M. (1999) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705519909540118 · Cited by 108,788
Statistical Power Analysis for the Behavioral Sciences (2nd ed.).
Lachenbruch, P. A., & Cohen, J. (1989) · Journal of the American Statistical Association · doi:10.2307/2290095 · Cited by 37,395
LISREL 7 : user's reference guide
Jöreskog, K. G., & Sörbom, D. (1989) · Medical Entomology and Zoology · Cited by 6,783
Sample size in factor analysis.
MacCallum, R. C., Widaman, K. F., Zhang, S., & Hong, S. (1999) · Psychological Methods · doi:10.1037/1082-989x.4.1.84 · Cited by 5,497
Structural Equation Modeling: Concepts, Issues, and Applications
Rigdon, E. E., & Hoyle, R. H. (1997) · Journal of Marketing Research · doi:10.2307/3151904 · Cited by 4,060
A comparison of some methodologies for the factor analysis of non‐normal Likert variables
Muthén, B., & Kaplan, D. (1985) · British Journal of Mathematical and Statistical Psychology · doi:10.1111/j.2044-8317.1985.tb00832.x · Cited by 1,778 · cited 2×
“…violations of normality (Finch, West, & MacKinnon, 1997; Harlow, 1985; Hutchinson & Olmos, 1998; Muthén & Kaplan, 1985, 1992) and coarse categorization (Babakus, Ferguson, & Jöreskog, 1987; Green, Akey, Fleming, Hershberger, & Marquis, 1997; Hutchinson & Olmos, 1998; Muthén & Kaplan, 1985, 1992).”
Bagozzi, R. P., & Heatherton, T. F. (1994) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1080/10705519409539961 · Cited by 1,481
Is More Ever Too Much? The Number of Indicators per Factor in Confirmatory Factor Analysis
Marsh, H. W., Hau, K.-T., Balla, J. R., & Grayson, D. (1998) · Multivariate Behavioral Research · doi:10.1207/s15327906mbr3302_1 · Cited by 1,307
A General Approach for Representing Constructs in Organizational Research
Bagozzi, R. P., & Edwards, J. R. (1998) · Organizational Research Methods · doi:10.1177/109442819800100104 · Cited by 1,217
Affects of variable and subject sampling on factor pattern recovery.
Velicer, W. F., & Fava, J. L. (1998) · Psychological Methods · doi:10.1037/1082-989x.3.2.231 · Cited by 998
Cited by
MacKenzie, S. B., Podsakoff, P. M., & Podsakoff, N. P. (2011) · MIS Quarterly · doi:10.2307/23044045 · Cited by 3,165
An empirical comparison of the efficacy of covariance-based and variance-based SEM
Reinartz, W., Haenlein, M., & Henseler, J. (2009) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2009.08.001 · Cited by 2,906
Skinner, E. A., Edge, K., Altman, J., & Sherwood, H. (2003) · Psychological Bulletin · doi:10.1037/0033-2909.129.2.216 · Cited by 2,639
Reporting practices in confirmatory factor analysis: an overview and some recommendations
Jackson, D. L., Gillaspy, J. A., & Purc-Stephenson, R. (2009) · Psychological Methods · doi:10.1037/a0014694 · Cited by 2,242
Why the items versus parcels controversy needn’t be one.
Little, T. D., Rhemtulla, M., Gibson, K., & Schoemann, A. M. (2013) · Psychological Methods · doi:10.1037/a0033266 · Cited by 1,603
Metadata
- Authors
- Bandalos, D. L.
- Venue
- Structural Equation Modeling: A Multidisciplinary Journal
- Publisher
- Informa UK Limited
- Published
- 2002-01
- Volume
- 9
- Issue
- 1
- Pages
- 78-102
- ISSN
- 1070-5511 (ISSN-L)
- 1532-8007
- OpenAlex
- W2155173154
- Cited by
- 1,377
- References
- 30
- FWCI
- 27.07
- 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: The Effects of Item Parceling on Goodness-of-Fit and Parameter Estimate Bias in Structural Equation Modeling. https://app.cochat.ai/papers/10.1207/s15328007sem0901_5
- The paper
- Bandalos, D. L. (2002). The Effects of Item Parceling on Goodness-of-Fit and Parameter Estimate Bias in Structural Equation Modeling. Structural Equation Modeling: A Multidisciplinary Journal. https://doi.org/10.1207/s15328007sem0901_5
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.