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Li, Feifei – ETS Research Report Series, 2017
An information-correction method for testlet-based tests is introduced. This method takes advantage of both generalizability theory (GT) and item response theory (IRT). The measurement error for the examinee proficiency parameter is often underestimated when a unidimensional conditional-independence IRT model is specified for a testlet dataset. By…
Descriptors: Item Response Theory, Generalizability Theory, Tests, Error of Measurement
Hutten, Leah R. – 1979
Goodness of fit of raw test score data were compared, using two latent trait models: the Rasch model and the Birnbaum three-parameter logistic model. Data were taken from various achievement tests and the Scholastic Aptitude Test (Verbal). A minimum sample size of 1,000 was required, and the minimum test length was 40 items. Results indicated that…
Descriptors: Ability Identification, Achievement Tests, College Entrance Examinations, Comparative Analysis