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Properties of Ability Estimation Methods and Computerized Adaptive Testing.
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Wang, Tianyou; Vispoel, Walter P. – Journal of Educational Measurement, 1998
Used simulations of computerized adaptive tests to evaluate results yielded by four commonly used ability estimation methods: maximum likelihood estimation (MLE) and three Bayesian approaches. Results show clear distinctions between MLE and Bayesian methods. (SLD)
Descriptors: Ability, Adaptive Testing, Bayesian Statistics, Computer Assisted Testing
Data Sparseness and On-Line Pretest Item Calibration-Scaling Methods in CAT.
Peer reviewed Peer reviewed
Ban, Jae-Chun; Hanson, Bradley A.; Yi, Qing; Harris, Deborah J. – Journal of Educational Measurement, 2002
Compared three online pretest calibration scaling methods through simulation: (1) marginal maximum likelihood with one expectation maximization (EM) cycle (OEM) method; (2) marginal maximum likelihood with multiple EM cycles (MEM); and (3) M. Stocking's method B. MEM produced the smallest average total error in parameter estimation; OEM yielded…
Descriptors: Computer Assisted Testing, Error of Measurement, Maximum Likelihood Statistics, Online Systems
Using Patterns of Summed Scores in Paper-and-Pencil Tests and Computer-Adaptive Tests to Detect Misfitting Item Score Patterns
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Meijer, Rob R. – Journal of Educational Measurement, 2004
Two new methods have been proposed to determine unexpected sum scores on sub-tests (testlets) both for paper-and-pencil tests and computer adaptive tests. A method based on a conservative bound using the hypergeometric distribution, denoted p, was compared with a method where the probability for each score combination was calculated using a…
Descriptors: Probability, Adaptive Testing, Item Response Theory, Scores
Influence of Prior Distributions on Detection of DIF.
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Cohen, Allan S.; And Others – Journal of Educational Measurement, 1991
Detecting differential item functioning (DIF) on test items constructed to favor 1 group over another was investigated on parameter estimates from 2 item response theory-based computer programs--BILOG and LOGIST--using data for 1,000 White and 1,000 Black college students. Use of prior distributions and marginal-maximum a posteriori estimation is…
Descriptors: Black Students, College Students, Computer Assisted Testing, Equations (Mathematics)