The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Semiparametric Estimation in the Rasch Model and Related Exponential Response Models, Including a Simple Latent Class Model for Item Analysis
Abstract
The Rasch model for item analysis is an important member of the class of exponential response models in which the number of nuisance parameters increases with the number of subjects, leading to the failure of the usual likelihood methodology. Both conditional-likelihood methods and mixture-model techniques have been used to circumvent these problems. In this article, we show that these seemingly unrelated analyses are in fact closely linked to each other, despite dramatic structural differences between the classes of models implied by each approach. We show that the finite-mixture model for J dichotomous items having T latent classes gives the same estimates of item parameters as conditional likelihood on a set whose probability approaches one if T ≥ (J + 1)/2. Unconditional maximum likelihood estimators for the finite-mixture model can be viewed as Keifer-Wolfowitz estimators for the random-effects version of the Rasch model. Latent-class versions of the model are especially attractive when T is small relative to J. We analyze several sets of data, propose simple diagnostic checks, and discuss procedures for assigning scores to subjects based on posterior means. A flexible and general methodology for item analysis based on latent class techniques is proposed.
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Cites
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Cited by
Clogg, C. C. (1995) · Handbook of Statistical Modeling for the Social and Behavioral Sciences · doi:10.1007/978-1-4899-1292-3_6 · Cited by 621
Self-citationInternational Market Segmentation Based on Consumer–Product Relations
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Measuring progressions: Assessment structures underlying a learning progression
Wilson, M. (2009) · Journal of Research in Science Teaching · doi:10.1002/tea.20318 · Cited by 329
Markon, K. E., & Krueger, R. F. (2006) · Psychological Methods · doi:10.1037/1082-989x.11.3.228 · Cited by 53
Item Response Theory: A Statistical Framework for Educational and Psychological Measurement
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Metadata
- Authors
- Lindsay, B., Clogg, C. C., & Grego, J.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1991-03
- Volume
- 86
- Issue
- 413
- Pages
- 96-107
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2062828949
- Cited by
- 289
- References
- 40
- FWCI
- 17.62
- Type
- journal article
- Language
- en
- Open access
- closed
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- Lindsay, B., Clogg, C. C., & Grego, J. (1991). Semiparametric Estimation in the Rasch Model and Related Exponential Response Models, Including a Simple Latent Class Model for Item Analysis. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1991.10475008
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