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Eray Selçuk; Ergül Demir – International Journal of Assessment Tools in Education, 2024
This research aims to compare the ability and item parameter estimations of Item Response Theory according to Maximum likelihood and Bayesian approaches in different Monte Carlo simulation conditions. For this purpose, depending on the changes in the priori distribution type, sample size, test length, and logistics model, the ability and item…
Descriptors: Item Response Theory, Item Analysis, Test Items, Simulation
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Wheadon, Christopher – Research Papers in Education, 2013
This paper describes how item response theory (IRT) methods of test-equating could be applied to the maintenance of public examination standards in England. IRT methods of test-equating have been sparingly applied to the main public examinations in England, namely the General Certificate of Secondary Education (GCSE), the equivalent of a school…
Descriptors: Test Theory, Foreign Countries, Exit Examinations, Item Response Theory
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Ramsay, James O. – Psychometrika, 1989
An alternative to the Rasch model is introduced. It characterizes strength of response according to the ratio of ability and difficulty parameters rather than their difference. Joint estimation and marginal estimation models are applied to two test data sets. (SLD)
Descriptors: Ability, Bayesian Statistics, College Entrance Examinations, Comparative Analysis
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Jansen, Margo G. H. – Journal of Educational Statistics, 1986
In this paper a Bayesian procedure is developed for the simultaneous estimation of the reading ability and difficulty parameters which are assumed to be factors in reading errors by the multiplicative Poisson Model. According to several criteria, the Bayesian estimates are better than comparable maximum likelihood estimates. (Author/JAZ)
Descriptors: Achievement Tests, Bayesian Statistics, Comparative Analysis, Difficulty Level
Haladyna, Tom; Roid, Gale – 1980
The problems associated with misclassifying students when pass-fail decisions are based on test scores are discussed. One protection against misclassification is to set a confidence interval around the cutting score. Those whose scores fall above the interval are passed; those whose scores fall below the interval are failed; and those whose scores…
Descriptors: Bayesian Statistics, Classification, Comparative Analysis, Criterion Referenced Tests