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Andersson, Björn; Xin, Tao – Educational and Psychological Measurement, 2018
In applications of item response theory (IRT), an estimate of the reliability of the ability estimates or sum scores is often reported. However, analytical expressions for the standard errors of the estimators of the reliability coefficients are not available in the literature and therefore the variability associated with the estimated reliability…
Descriptors: Item Response Theory, Test Reliability, Test Items, Scores
Jin, Ying; Eason, Hershel – Journal of Educational Issues, 2016
The effects of mean ability difference (MAD) and short tests on the performance of various DIF methods have been studied extensively in previous simulation studies. Their effects, however, have not been studied under multilevel data structure. MAD was frequently observed in large-scale cross-country comparison studies where the primary sampling…
Descriptors: Test Bias, Simulation, Hierarchical Linear Modeling, Comparative Analysis
Galindo-Garre, Francisca; Vermunt, Jeroen K. – Psychometrika, 2004
This paper presents a row-column (RC) association model in which the estimated row and column scores are forced to be in agreement with a priori specified ordering. Two efficient algorithms for finding the order-restricted maximum likelihood (ML) estimates are proposed and their reliability under different degrees of association is investigated by…
Descriptors: Mathematics, Test Reliability, Computation, Testing
Enders, Craig K. – Educational and Psychological Measurement, 2004
A method for incorporating maximum likelihood (ML) estimation into reliability analyses with item-level missing data is outlined. An ML estimate of the covariance matrix is first obtained using the expectation maximization (EM) algorithm, and coefficient alpha is subsequently computed using standard formulae. A simulation study demonstrated that…
Descriptors: Intervals, Simulation, Test Reliability, Computation
Peer reviewedSegall, Daniel O. – Psychometrika, 1996
Maximum likelihood and Bayesian procedures are presented for item selection and scoring of multidimensional adaptive tests. A demonstration with simulated response data illustrates that multidimensional adaptive testing can provide equal or higher reliabilities with fewer items than are required in one-dimensional adaptive testing. (SLD)
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Equations (Mathematics)

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