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Liang, Tie; Wells, Craig S.; Hambleton, Ronald K. – Journal of Educational Measurement, 2014
As item response theory has been more widely applied, investigating the fit of a parametric model becomes an important part of the measurement process. There is a lack of promising solutions to the detection of model misfit in IRT. Douglas and Cohen introduced a general nonparametric approach, RISE (Root Integrated Squared Error), for detecting…
Descriptors: Item Response Theory, Measurement Techniques, Nonparametric Statistics, Models
Zheng, Chunmei – ProQuest LLC, 2013
Educational and psychological constructs are normally measured by multifaceted dimensions. The measured construct is defined and measured by a set of related subdomains. A bifactor model can accurately describe such data with both the measured construct and the related subdomains. However, a limitation of the bifactor model is the orthogonality…
Descriptors: Educational Testing, Measurement Techniques, Test Items, Models
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Woods, Carol M. – Applied Psychological Measurement, 2008
In Ramsay-curve item response theory (RC-IRT), the latent variable distribution is estimated simultaneously with the item parameters of a unidimensional item response model using marginal maximum likelihood estimation. This study evaluates RC-IRT for the three-parameter logistic (3PL) model with comparisons to the normal model and to the empirical…
Descriptors: Test Length, Computation, Item Response Theory, Maximum Likelihood Statistics
Davey, Tim; Pommerich, Mary; Thompson, Tony D. – 1999
In computerized adaptive testing (CAT), new or experimental items are frequently administered alongside operational tests to gather the pretest data needed to replenish and replace item pools. The two basic strategies used to combine pretest and operational items are embedding and appending. Variable-length CATs are preferred because of the…
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Banks, Measurement Techniques
Cliff, Norman; And Others – 1977
TAILOR is a computer program that uses the implied orders concept as the basis for computerized adaptive testing. The basic characteristics of TAILOR, which does not involve pretesting, are reviewed here and two studies of it are reported. One is a Monte Carlo simulation based on the four-parameter Birnbaum model and the other uses a matrix of…
Descriptors: Adaptive Testing, Computer Assisted Testing, Computer Programs, Difficulty Level