01322nas a2200145 4500008003900000245005100039210004900090300000900139490000700148520091500155100001801070700001801088700001901106856005101125 2015 d00aOnline Item Calibration for Q-Matrix in CD-CAT0 aOnline Item Calibration for QMatrix in CDCAT a5-150 v393 a
Item replenishment is important for maintaining a large-scale item bank. In this article, the authors consider calibrating new items based on pre-calibrated operational items under the deterministic inputs, noisy-and-gate model, the specification of which includes the so-called -matrix, as well as the slipping and guessing parameters. Making use of the maximum likelihood and Bayesian estimators for the latent knowledge states, the authors propose two methods for the calibration. These methods are applicable to both traditional paper–pencil–based tests, for which the selection of operational items is prefixed, and computerized adaptive tests, for which the selection of operational items is sequential and random. Extensive simulations are done to assess and to compare the performance of these approaches. Extensions to other diagnostic classification models are also discussed.
1 aChen, Yunxiao1 aLiu, Jingchen1 aYing, Zhiliang uhttp://apm.sagepub.com/content/39/1/5.abstract