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ERIC Number: EJ779493
Record Type: Journal
Publication Date: 2002
Pages: 21
Abstractor: Author
Reference Count: 0
ISSN: ISSN-0146-6216
Estimating Consistency and Accuracy Indices for Multiple Classifications
Lee, Won-Chan; Hanson, Bradley A.; Brennan, Robert L.
Applied Psychological Measurement, v26 n4 p412-432 2002
This article describes procedures for estimating various indices of classification consistency and accuracy for multiple category classifications using data from a single test administration. The estimates of the classification consistency and accuracy indices are compared under three different psychometric models: the two-parameter beta binomial, four-parameter beta binomial, and three-parameter logistic IRT (item response theory) models. Using real data sets, the estimation procedures are illustrated, and the characteristics of the estimated classification indices are examined. This article also examines the behavior of the estimated classification indices as a function of the latent variable. All three components of the models (i.e., the estimated true score distributions, fitted observed score distributions, and estimated conditional error variances) appear to have considerable influence on the magnitudes of the estimated classification indices. Choosing a model in practice should be based on various considerations including the degree of model fit to the data, suitability of the model assumptions, and the computational feasibility.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A