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Imputation Methods to Deal with Missing Responses in Computerized Adaptive Multistage Testing
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Cetin-Berber, Dee Duygu; Sari, Halil Ibrahim; Huggins-Manley, Anne Corinne – Educational and Psychological Measurement, 2019
Routing examinees to modules based on their ability level is a very important aspect in computerized adaptive multistage testing. However, the presence of missing responses may complicate estimation of examinee ability, which may result in misrouting of individuals. Therefore, missing responses should be handled carefully. This study investigated…
Descriptors: Computer Assisted Testing, Adaptive Testing, Error of Measurement, Research Problems
Item Pool Design for an Operational Variable-Length Computerized Adaptive Test
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He, Wei; Reckase, Mark D. – Educational and Psychological Measurement, 2014
For computerized adaptive tests (CATs) to work well, they must have an item pool with sufficient numbers of good quality items. Many researchers have pointed out that, in developing item pools for CATs, not only is the item pool size important but also the distribution of item parameters and practical considerations such as content distribution…
Descriptors: Item Banks, Test Length, Computer Assisted Testing, Adaptive Testing
Estimating the Standard Error of the Maximum Likelihood Ability Estimator in Adaptive Testing Using the Posterior-Weighted Test Information Function
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Penfield, Randall D. – Educational and Psychological Measurement, 2007
The standard error of the maximum likelihood ability estimator is commonly estimated by evaluating the test information function at an examinee's current maximum likelihood estimate (a point estimate) of ability. Because the test information function evaluated at the point estimate may differ from the test information function evaluated at an…
Descriptors: Simulation, Adaptive Testing, Computation, Maximum Likelihood Statistics
Effects of Estimation Bias on Multiple-Category Classification with an IRT-Based Adaptive Classification Procedure
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Yang, Xiangdong; Poggio, John C.; Glasnapp, Douglas R. – Educational and Psychological Measurement, 2006
The effects of five ability estimators, that is, maximum likelihood estimator, weighted likelihood estimator, maximum a posteriori, expected a posteriori, and Owen's sequential estimator, on the performances of the item response theory-based adaptive classification procedure on multiple categories were studied via simulations. The following…
Descriptors: Classification, Computation, Simulation, Item Response Theory
A Comparison of Maximum Likelihood Estimation and Expected A Posteriori Estimation in CAT Using the Partial Credit Model.
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Chen, Ssu-Kuang; Hou, Liling; Dodd, Barbara G. – Educational and Psychological Measurement, 1998
A simulation study was conducted to investigate the application of expected a posteriori (EAP) trait estimation in computerized adaptive tests (CAT) based on the partial credit model and compare it with maximum likelihood estimation (MLE). Results show the conditions under which EAP and MLE provide relatively accurate estimation in CAT. (SLD)
Descriptors: Adaptive Testing, Comparative Analysis, Computer Assisted Testing, Estimation (Mathematics)
The Effect of Population Distribution and Method of Theta Estimation on Computerized Adaptive Testing (CAT) Using the Rating Scale Model.
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Chen, Ssu-Kuang; And Others – Educational and Psychological Measurement, 1997
A simulation study explored the effect of population distribution on maximum likelihood estimation (MLE) and expected a posteriori (EAP) estimation in computerized adaptive testing based on the rating scale model of D. Andrich (1978). The choice between EAP and MLE for particular situations is discussed. (SLD)
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Estimation (Mathematics)