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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
Direct linkTalento-Miller, Eileen; Guo, Fanmin; Han, Kyung T. – International Journal of Testing, 2013
When power tests include a time limit, it is important to assess the possibility of speededness for examinees. Past research on differential speededness has examined gender and ethnic subgroups in the United States on paper and pencil tests. When considering the needs of a global audience, research regarding different native language speakers is…
Descriptors: Adaptive Testing, Computer Assisted Testing, English, Scores
Cheng, Ying; Chang, Hua-Hua; Douglas, Jeffrey; Guo, Fanmin – Educational and Psychological Measurement, 2009
a-stratification is a method that utilizes items with small discrimination (a) parameters early in an exam and those with higher a values when more is learned about the ability parameter. It can achieve much better item usage than the maximum information criterion (MIC). To make a-stratification more practical and more widely applicable, a method…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Selection
