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Sijia Huang; Dubravka Svetina Valdivia – Educational and Psychological Measurement, 2024
Identifying items with differential item functioning (DIF) in an assessment is a crucial step for achieving equitable measurement. One critical issue that has not been fully addressed with existing studies is how DIF items can be detected when data are multilevel. In the present study, we introduced a Lord's Wald X[superscript 2] test-based…
Descriptors: Item Analysis, Item Response Theory, Algorithms, Accuracy
Zhichen Guo; Daxun Wang; Yan Cai; Dongbo Tu – Educational and Psychological Measurement, 2024
Forced-choice (FC) measures have been widely used in many personality or attitude tests as an alternative to rating scales, which employ comparative rather than absolute judgments. Several response biases, such as social desirability, response styles, and acquiescence bias, can be reduced effectively. Another type of data linked with comparative…
Descriptors: Item Response Theory, Models, Reaction Time, Measurement Techniques

Rasmussen, Jeffrey Lee – Educational and Psychological Measurement, 1993
J. P. Shaffer has presented two tests to improve the power of multiple comparison procedures. This article described an algorithm to carry out the tests. The logic of the algorithm and an application to a data set are given. (SLD)
Descriptors: Algorithms, Analysis of Variance, Comparative Analysis, Logic

Eggen, T. J. H. M.; Straetmans, G. J. J. M. – Educational and Psychological Measurement, 2000
Studied the use of adaptive testing when examinees are classified into three categories. Established testing algorithms with two different statistical computation procedures and evaluated them through simulation using an operative item bank from Dutch basic adult education. Results suggest a reduction of at least 22% in the mean number of items…
Descriptors: Adaptive Testing, Adult Education, Algorithms, Classification

Frigon, Jean-Yves; Laurencelle, Louis – Educational and Psychological Measurement, 1993
The statistical power of analysis of covariance (ANCOVA) and its advantages over simple analysis of variance are examined in some experimental situations, and an algorithm is proposed for its proper application. In nonrandomized experiments, an ANCOVA is generally not a good approach. (SLD)
Descriptors: Algorithms, Analysis of Covariance, Analysis of Variance, Educational Research