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Cited by 338

The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.

Estimating Latent Distributions

Mislevy, Robert J.·1984·Psychometrika
DOI 10.1007/bf02306026
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Abstract

Consider vectors of item responses obtained from a sample of subjects from a population in which ability θ is distributed with density g (θ‖α), where the α are unknown parameters. Assuming the responses depend on θ through a fully specified item response model, this paper presents maximum likelihood equations for the estimation of the population parameters directly from the observed responses; i.e., without estimating an ability parameter for each subject. Also provided are asymptotic standard errors and tests of fit, computing approximations, and details of four special cases: a non-parametric approximation, a normal solution, a resolution of normal components, and a beta-binomial solution.

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Metadata

Authors
Mislevy, R. J.
Venue
Psychometrika
Publisher
Cambridge University Press (CUP)
Published
1984-09
Volume
49
Issue
3
Pages
359-381
ISSN
  • 0033-3123 (ISSN-L)
  • 1860-0980
DOI
10.1007/bf02306026
OpenAlex
W1973102368
Cited by
338
References
28
FWCI
13.72
Type
journal article
Language
en
Open access
closed

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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.