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Jyun-Hong Chen; Hsiu-Yi Chao – Journal of Educational and Behavioral Statistics, 2024
To solve the attenuation paradox in computerized adaptive testing (CAT), this study proposes an item selection method, the integer programming approach based on real-time test data (IPRD), to improve test efficiency. The IPRD method turns information regarding the ability distribution of the population from real-time test data into feasible test…
Descriptors: Data Use, Computer Assisted Testing, Adaptive Testing, Design
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Gu, Zhengguo; Emons, Wilco H. M.; Sijtsma, Klaas – Journal of Educational and Behavioral Statistics, 2021
Clinical, medical, and health psychologists use difference scores obtained from pretest--posttest designs employing the same test to assess intraindividual change possibly caused by an intervention addressing, for example, anxiety, depression, eating disorder, or addiction. Reliability of difference scores is important for interpreting observed…
Descriptors: Test Reliability, Scores, Pretests Posttests, Computation
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Wang, Yu; Chiu, Chia-Yi; Köhn, Hans Friedrich – Journal of Educational and Behavioral Statistics, 2023
The multiple-choice (MC) item format has been widely used in educational assessments across diverse content domains. MC items purportedly allow for collecting richer diagnostic information. The effectiveness and economy of administering MC items may have further contributed to their popularity not just in educational assessment. The MC item format…
Descriptors: Multiple Choice Tests, Nonparametric Statistics, Test Format, Educational Assessment
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Longford, Nicholas T. – Journal of Educational and Behavioral Statistics, 2014
A method for medical screening is adapted to differential item functioning (DIF). Its essential elements are explicit declarations of the level of DIF that is acceptable and of the loss function that quantifies the consequences of the two kinds of inappropriate classification of an item. Instead of a single level and a single function, sets of…
Descriptors: Test Items, Test Bias, Simulation, Hypothesis Testing
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Segall, Daniel O. – Journal of Educational and Behavioral Statistics, 2004
A new sharing item response theory (SIRT) model is presented that explicitly models the effects of sharing item content between informants and test takers. This model is used to construct adaptive item selection and scoring rules that provide increased precision and reduced score gains in instances where sharing occurs. The adaptive item selection…
Descriptors: Scoring, Item Analysis, Item Response Theory, Adaptive Testing