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Sen, Sedat – International Journal of Testing, 2018
Recent research has shown that over-extraction of latent classes can be observed in the Bayesian estimation of the mixed Rasch model when the distribution of ability is non-normal. This study examined the effect of non-normal ability distributions on the number of latent classes in the mixed Rasch model when estimated with maximum likelihood…
Descriptors: Item Response Theory, Comparative Analysis, Computation, Maximum Likelihood Statistics
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Tian, Wei; Cai, Li; Thissen, David; Xin, Tao – Educational and Psychological Measurement, 2013
In item response theory (IRT) modeling, the item parameter error covariance matrix plays a critical role in statistical inference procedures. When item parameters are estimated using the EM algorithm, the parameter error covariance matrix is not an automatic by-product of item calibration. Cai proposed the use of Supplemented EM algorithm for…
Descriptors: Item Response Theory, Computation, Matrices, Statistical Inference
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Cohen, Jon; Snow, Stephanie – Journal of Educational Measurement, 2002
Studied the impact of changes in item difficulty on National Assessment of Educational Progress (NAEP) estimates over time through a Monte Carlo study that simulated the responses of 1990 NAEP mathematics respondents to 1990 and 1996 NAEP mathematics items. Results support the idea that these changes have not affected the NAEP trend line.…
Descriptors: Change, Difficulty Level, Estimation (Mathematics), Mathematics Tests
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Finch, W. Holmes; French, Brian F. – Educational and Psychological Measurement, 2007
Differential item functioning (DIF) continues to receive attention both in applied and methodological studies. Because DIF can be an indicator of irrelevant variance that can influence test scores, continuing to evaluate and improve the accuracy of detection methods is an essential step in gathering score validity evidence. Methods for detecting…
Descriptors: Item Response Theory, Factor Analysis, Test Bias, Comparative Analysis