Literaturnachweis - Detailanzeige
| Autor/in | Mislevy, Robert J. |
|---|---|
| Institution | Educational Testing Service, Princeton, NJ. |
| Titel | Bayes Modal Estimation in Item Response Models. |
| Quelle | (1985), (57 Seiten)
PDF als Volltext kostenfreie Datei |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Monographie |
| Schlagwörter | Algorithms; Bayesian Statistics; Estimation (Mathematics); Latent Trait Theory; Mathematical Models; Maximum Likelihood Statistics; Psychometrics; Simulation; Statistical Analysis; Statistical Data |
| Abstract | Simultaneous estimation of many parameters can often be improved, sometimes dramatically so, if it is reasonable to consider one or more subsets of parameters as exchangeable members of corresponding populations. While each observation may provide limited information about the parameters it is modeled directly in terms of, it also contributes information about the populations to which they belong. Knowledge about the populations, generally superior to knowledge about individual parameters, can in turn be brought to bear in the estimation of any individual parameter. This article describes a Bayesian framework for estimation in item response models, with two-stage prior distributions on both item and examinee populations. Strategies for point and interval estimation are discussed and a general procedure based on the EM algorithm is presented. Details are given for implementation under one-, two-, and three-parameter logistic item response theory models. Novel features include minimally restrictive assumptions about examinee distributions and the exploitation of dependence among item parameters in a population of interest. Improved estimation in a moderately small sample is demonstrated with simulated data. Possible extensions of the procedures are discussed. (Author/PN) |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
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