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政大典藏 > College of Commerce > Department of Statistics > Periodical Articles > Item 140.119/72222

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/72222

Title:	Online Calibration Via Variable Length Computerized Adaptive Testing
Authors:	張源俊 Chang, Yuan-chin I.;Lu, Hung-Yi
Contributors:	統計系
Date:	2009-07
Issue Date:	2014-12-23 15:18:51 (UTC+8)
Abstract:	Item calibration is an essential issue in modern item response theory based psychological or educational testing. Due to the popularity of computerized adaptive testing, methods to efficiently calibrate new items have become more important than that in the time when paper and pencil test administration is the norm. There are many calibration processes being proposed and discussed from both theoretical and practical perspectives. Among them, the online calibration may be one of the most cost effective processes. In this paper, under a variable length computerized adaptive testing scenario, we integrate the methods of adaptive design, sequential estimation, and measurement error models to solve online item calibration problems. The proposed sequential estimate of item parameters is shown to be strongly consistent and asymptotically normally distributed with a prechosen accuracy. Numerical results show that the proposed method is very promising in terms of both estimation accuracy and efficiency. The results of using calibrated items to estimate the latent trait levels are also reported.
Relation:	Psychometrika,75(1), 140-157
Data Type:	article
Appears in Collections:	[Department of Statistics] Periodical Articles

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