title: Continuous Online Item Calibration: Parameter Recovery and Item Utilization.
abstract: Parameter recovery and item utilization were investigated for different designs for online test item calibration. The design was adaptive in a double sense: it assumed both adaptive testing of examinees from an operational pool of previously calibrated items and adaptive assignment of field-test items to the examinees. Four criteria of optimality for the assignment of the field-test items were used, each of them based on the information in the posterior distributions of the examinee's ability parameter during adaptive testing as well as the sequentially updated posterior distributions of the field-test item parameters. In addition, different stopping rules based on target values for the posterior standard deviations of the field-test parameters and the size of the calibration sample were used. The impact of each of the criteria and stopping rules on the statistical efficiency of the estimates of the field-test parameters and on the time spent by the items in the calibration procedure was investigated. Recommendations as to the practical use of the designs are given.
authors.affiliation: Pacific Metrics, 1 Lower Ragsdale Dr #150, Monterey, CA, 93940, USA. hren@pacificmetrics.com.
authors.forename: Hao
authors.initials: H
authors.lastname: Ren
authors.affiliation: Pacific Metrics, 1 Lower Ragsdale Dr #150, Monterey, CA, 93940, USA.
authors.forename: Wim J
authors.initials: WJ
authors.lastname: van der Linden
authors.affiliation: Pacific Metrics, 1 Lower Ragsdale Dr #150, Monterey, CA, 93940, USA.
authors.forename: Qi
authors.initials: Q
authors.lastname: Diao
mesh_terms: D002138:Calibration; D006801:Humans; D011594:Psychometrics
keywords: Bayesian optimal design; D-optimality; adaptive testing; item calibration