نتایج جستجو برای: concurrent equating
تعداد نتایج: 63715 فیلتر نتایج به سال:
BACKGROUND The MRCP(UK) exam, in 2008 and 2010, changed the standard-setting of its Part 1 and Part 2 examinations from a hybrid Angoff/Hofstee method to statistical equating using Item Response Theory, the reference group being UK graduates. The present paper considers the implementation of the change, the question of whether the pass rate increased amongst non-UK candidates, any possible role...
Abstract We wonder if there is a way to make all Schur functions in representations equal. This impossible for fixed value of time variables, but can be achieved averages. It appears that the corresponding measure just Gaussian times, which are independent. The generating function number Young diagrams does not straightforwardly appear as product, reproduced non-trivial way.
BACKGROUND Examinations are necessary for assessment of student proficiency in medical education, but comparison of achievement across different cohorts in different tests is challenging. We applied psychometric test equating methods to compare student proficiency in two different examinations for a clinical anesthesiology course. METHODS Each examination contained 50 multiple choice items an...
The standard error of equating is a useful index to quantify the amount of equating error. It is the standard deviation of equated scores over replications of an equating procedure in samples from a population or populations of examines. The current study estimates the SE of item response theory true score equating in the Nonequivalent Groups with Anchor Test design using simulations. Specifica...
Since the invention of z-scores (standardized scores), comparison among different tests has been widely conducted by test developers, instructors, educational researchers, and psychometricians. Equating, calibration, and moderation are terms used to describe broad levels of possible comparison among educational assessments (Dorans, 2004; Feuer, Holland, Green, Bertenthal, & Hemphill, 1999; Linn...
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