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Download full textHan, Kyung T.; Guo, Fanmin – Practical Assessment, Research & Evaluation, 2014
The full-information maximum likelihood (FIML) method makes it possible to estimate and analyze structural equation models (SEM) even when data are partially missing, enabling incomplete data to contribute to model estimation. The cornerstone of FIML is the missing-at-random (MAR) assumption. In (unidimensional) computerized adaptive testing…
Descriptors: Maximum Likelihood Statistics, Structural Equation Models, Data, Computer Assisted Testing
Reckase, Mark D. – 1981
This report summarizes the research findings of a four year contract investigating the applicability of item response theory and tailored testing to criterion-referenced measurement. Six major areas were studied on the project: (1) techniques for forming unidimensional item sets; (2) techniques for calibrating items; (3) item parameter linking…
Descriptors: Achievement Tests, Adaptive Testing, Criterion Referenced Tests, Decision Making
De Ayala, R. J.; And Others – 1991
The robustness of a partial credit (PC) model-based computerized adaptive test's (CAT's) ability estimation to items that did not fit the PC model was investigated. A CAT program was written based on the PC model. The program used maximum likelihood estimation of ability. Item selection was on the basis of information. The simulation terminated…
Descriptors: Adaptive Testing, Computer Assisted Testing, Equations (Mathematics), Error of Measurement
