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Karadavut, Tugba – International Journal of Assessment Tools in Education, 2019
Item Response Theory (IRT) models traditionally assume a normal distribution for ability. Although normality is often a reasonable assumption for ability, it is rarely met for observed scores in educational and psychological measurement. Assumptions regarding ability distribution were previously shown to have an effect on IRT parameter estimation.…
Descriptors: Item Response Theory, Computation, Bayesian Statistics, Ability
MacDonald, George T. – ProQuest LLC, 2014
A simulation study was conducted to explore the performance of the linear logistic test model (LLTM) when the relationships between items and cognitive components were misspecified. Factors manipulated included percent of misspecification (0%, 1%, 5%, 10%, and 15%), form of misspecification (under-specification, balanced misspecification, and…
Descriptors: Simulation, Item Response Theory, Models, Test Items
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Paek, Insu; Park, Hyun-Jeong; Cai, Li; Chi, Eunlim – Educational and Psychological Measurement, 2014
Typically a longitudinal growth modeling based on item response theory (IRT) requires repeated measures data from a single group with the same test design. If operational or item exposure problems are present, the same test may not be employed to collect data for longitudinal analyses and tests at multiple time points are constructed with unique…
Descriptors: Item Response Theory, Comparative Analysis, Test Items, Equated Scores
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Rudner, Lawrence M. – Practical Assessment, Research & Evaluation, 2001
Provides and illustrates a method to compute the expected number of misclassifications of examinees using three-parameter item response theory and two state classifications (mastery or nonmastery). The method uses the standard error and the expected examinee ability distribution. (SLD)
Descriptors: Ability, Classification, Computation, Error of Measurement