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- W2138415768 abstract "In computerized adaptive testing (CAT), an examinee’s trait level (Θ) must be estimated with reasonable accuracy based on a small number of item responses. A successful implementation of CAT depends on (1) the accuracy of statistical methods used for estimating and (2) the efficiency of the item-selection criterion. Methods of estimating suitable for CAT are reviewed, and the differences between Fisher and Kullback-Leibler information criteria for selecting items are discussed. The accuracy of different CAT algorithms was examined in an empirical study. The results showed that correcting estimates for bias was necessary at earlier stages of CAT, but most CAT algorithms performed equally well for tests of 10 or more items." @default.
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- W2138415768 date "2000-09-01" @default.
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- W2138415768 title "Estimation of Trait Level in Computerized Adaptive Testing" @default.
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- W2138415768 doi "https://doi.org/10.1177/01466210022031723" @default.
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