Information Matrices in Latent-Variable Models

Robert J. Mislevy and Kathleen M. Sheehan

Journal of Educational and Behavioral Statistics, 1989, vol. 14, issue 4, 335-350

Abstract: The Fisher, or expected, information matrix for the parameters in a latent-variable model is bounded from above by the information that would be obtained if the values of the latent variables could also be observed. The difference between this upper bound and the information in the observed data is the “missing information.†This paper explicates the structure of the expected information matrix and related information matrices, and characterizes the degree to which missing information can be recovered by exploiting collateral variables for respondents. The results are illustrated in the context of item response theory models, and practical implications are discussed.

Keywords: collateral information; item response theory; latent variables; missing information principle (search for similar items in EconPapers)
Date: 1989
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.3102/10769986014004335 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:14:y:1989:i:4:p:335-350

DOI: 10.3102/10769986014004335

Access Statistics for this article

More articles in Journal of Educational and Behavioral Statistics
Bibliographic data for series maintained by SAGE Publications ().