The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Generalized Latent Trait Models
Abstract
In this paper we discuss a general model framework within which manifest variables with different distributions in the exponential family can be analyzed with a latent trait model. A unified maximum likelihood method for estimating the parameters of the generalized latent trait model will be presented. We discuss in addition the scoring of individuals on the latent dimensions. The general framework presented allows, not only the analysis of manifest variables all of one type but also the simultaneous analysis of a collection of variables with different distributions. The approach used analyzes the data as they are by making assumptions about the distribution of the manifest variables directly.
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Cites
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A Rasch model for partial credit scoring
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ESTIMATION OF LATENT ABILITY USING A RESPONSE PATTERN OF GRADED SCORES1
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Application of Model-Selection Criteria to Some Problems in Multivariate Analysis
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Cited by
The theoretical status of latent variables.
Borsboom, D., Mellenbergh, G. J., & van Heerden, J. (2003) · Psychological Review · doi:10.1037/0033-295x.110.2.203 · Cited by 1,566
Kamakura, W. A., Wedel, M., de Rosa, F., & Mazzon, J. A. (2003) · International Journal of Research in Marketing · doi:10.1016/s0167-8116(02)00121-0 · Cited by 336
Bayesian Latent Variable Models for Clustered Mixed Outcomes
Dunson, D. B. (2000) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00236 · Cited by 305
Item Response Theory: A Statistical Framework for Educational and Psychological Measurement
Chen, Y., Li, X., Liu, J., & Ying, Z. (2025) · Statistical Science · doi:10.1214/23-sts896 · Cited by 30
Metadata
- Authors
- Moustaki, I., & Knott, M.
- Venue
- Psychometrika
- Publisher
- Cambridge University Press (CUP)
- Published
- 2000-09
- Volume
- 65
- Issue
- 3
- Pages
- 391-411
- ISSN
- 0033-3123 (ISSN-L)
- 1860-0980
- OpenAlex
- W2079953459
- Cited by
- 254
- References
- 41
- FWCI
- 8.78
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
