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Doebler, Anna – Applied Psychological Measurement, 2012
It is shown that deviations of estimated from true values of item difficulty parameters, caused for example by item calibration errors, the neglect of randomness of item difficulty parameters, testlet effects, or rule-based item generation, can lead to systematic bias in point estimation of person parameters in the context of adaptive testing.…
Descriptors: Adaptive Testing, Computer Assisted Testing, Computation, Item Response Theory
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Green, Bert F. – Applied Psychological Measurement, 2011
This article refutes a recent claim that computer-based tests produce biased scores for very proficient test takers who make mistakes on one or two initial items and that the "bias" can be reduced by using a four-parameter IRT model. Because the same effect occurs with pattern scores on nonadaptive tests, the effect results from IRT scoring, not…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Bias, Item Response Theory
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Rulison, Kelly L.; Loken, Eric – Applied Psychological Measurement, 2009
A difficult result to interpret in Computerized Adaptive Tests (CATs) occurs when an ability estimate initially drops and then ascends continuously until the test ends, suggesting that the true ability may be higher than implied by the final estimate. This study explains why this asymmetry occurs and shows that early mistakes by high-ability…
Descriptors: Computer Assisted Testing, Adaptive Testing, Item Response Theory, Academic Ability
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Zwick, Rebecca; Thayer, Dorothy T. – Applied Psychological Measurement, 2002
Used a simulation to investigate the applicability to computerized adaptive test data of a differential item functioning (DIF) analysis method. Results show the performance of this empirical Bayes enhancement of the Mantel Haenszel DIF analysis method to be quite promising. (SLD)
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Item Bias
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Wang, Tianyou; Hanson, Bradley A.; Lau, Che-Ming A. – Applied Psychological Measurement, 1999
Extended the use of a beta prior in trait estimation to the maximum expected a posteriori (MAP) method of Bayesian estimation. This new method, essentially unbiased MAP, was compared with MAP, essentially unbiased expected a posteriori, weighted likelihood, and maximum-likelihood estimation methods. The new method significantly reduced bias in…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Estimation (Mathematics)
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Chang, Hua-Hua; Ying, Zhiliang – Applied Psychological Measurement, 1996
An item selection procedure for computerized adaptive testing based on average global information is proposed. Results from simulation studies comparing the approach with the usual maximum item information item selection indicate that the new method leads to improvement in terms of bias and mean squared error reduction under many circumstances.…
Descriptors: Adaptive Testing, Computer Assisted Testing, Error of Measurement, Item Response Theory
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Zwick, Rebecca; And Others – Applied Psychological Measurement, 1994
Simulated data were used to investigate the performance of modified versions of the Mantel-Haenszel method of differential item functioning (DIF) analysis in computerized adaptive tests (CAT). Results indicate that CAT-based DIF procedures perform well and support the use of item response theory-based matching variables in DIF analysis. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Computer Simulation, Error of Measurement
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van der Linden, Wim J. – Applied Psychological Measurement, 2006
Two local methods for observed-score equating are applied to the problem of equating an adaptive test to a linear test. In an empirical study, the methods were evaluated against a method based on the test characteristic function (TCF) of the linear test and traditional equipercentile equating applied to the ability estimates on the adaptive test…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Format, Equated Scores