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Jewsbury, Paul A.; van Rijn, Peter W. – Journal of Educational and Behavioral Statistics, 2020
In large-scale educational assessment data consistent with a simple-structure multidimensional item response theory (MIRT) model, where every item measures only one latent variable, separate unidimensional item response theory (UIRT) models for each latent variable are often calibrated for practical reasons. While this approach can be valid for…
Descriptors: Item Response Theory, Computation, Test Items, Adaptive Testing
Chun Wang; Ping Chen; Shengyu Jiang – Journal of Educational Measurement, 2020
Many large-scale educational surveys have moved from linear form design to multistage testing (MST) design. One advantage of MST is that it can provide more accurate latent trait [theta] estimates using fewer items than required by linear tests. However, MST generates incomplete response data by design; hence, questions remain as to how to…
Descriptors: Test Construction, Test Items, Adaptive Testing, Maximum Likelihood Statistics

Cheng, Philip E.; Liou, Michelle – Applied Psychological Measurement, 2000
Reviewed methods of estimating theta suitable for computerized adaptive testing (CAT) and discussed the differences between Fisher and Kullback-Leibler information criteria for selecting items. Examined the accuracy of different CAT algorithms using samples from the National Assessment of Educational Progress. Results show when correcting for…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing

Brennan, Robert L. – Applied Measurement in Education, 1992
A conceptual framework and heuristic model for considering the existence, magnitude, and consequences of context effects are presented through an extension of some generalizability theory concepts. Context effects are often misunderstood, and current measurement models have serious limitations for examining them. Their importance needs to be…
Descriptors: Adaptive Testing, Context Effect, Equated Scores, Equations (Mathematics)