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Direct linkHan, 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
Han, Kyung T. – Practical Assessment, Research & Evaluation, 2012
For several decades, the "three-parameter logistic model" (3PLM) has been the dominant choice for practitioners in the field of educational measurement for modeling examinees' response data from multiple-choice (MC) items. Past studies, however, have pointed out that the c-parameter of 3PLM should not be interpreted as a guessing parameter. This…
Descriptors: Statistical Analysis, Models, Multiple Choice Tests, Guessing (Tests)
