The DOI matches its Crossref record.
Multicomponent Latent Trait Models for Ability Tests
Abstract
A major research direction for ability measurement has been to identify the information-processes that are involved in solving test items through mathematical modeling of item difficulty. However, this research has had limited impact on ability measurement, since person parameters are not included in the process models. The current paper presents some multicomponent latent trait models for reproducing test performance from both item and person parameters on processing components. Components are identified from item subtasks, in which performance is a logistic function (i.e., Rasch model) of person and item parameters, and then are combined according to a mathematical model of processing on the composite item.
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
Cited by
The Development of a Rasch-Type Loneliness Scale
de Jong-Gierveld, J., & Kamphuls, F. (1985) · Applied Psychological Measurement · doi:10.1177/014662168500900307 · Cited by 1,291
The Interaction of Domain-Specific and Strategic Knowledge in Academic Performance
Alexander, P. A., & Judy, J. E. (1988) · Review of Educational Research · doi:10.3102/00346543058004375 · Cited by 728
Estimating Multiple Classification Latent Class Models
Maris, E. (1999) · Psychometrika · doi:10.1007/bf02294535 · Cited by 417
Metadata
- Authors
- Whitely, S. E.
- Venue
- Psychometrika
- Publisher
- Cambridge University Press (CUP)
- Published
- 1980-12
- Volume
- 45
- Issue
- 4
- Pages
- 479-494
- ISSN
- 0033-3123 (ISSN-L)
- 1860-0980
- OpenAlex
- W2002091574
- Cited by
- 180
- References
- 0
- FWCI
- 6.38
- 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: Multicomponent Latent Trait Models for Ability Tests. https://app.cochat.ai/papers/10.1007/bf02293610
- The paper
- Whitely, S. E. (1980). Multicomponent Latent Trait Models for Ability Tests. Psychometrika. https://doi.org/10.1007/bf02293610
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.
