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Finch, Holmes – Applied Psychological Measurement, 2011
Estimation of multidimensional item response theory (MIRT) model parameters can be carried out using the normal ogive with unweighted least squares estimation with the normal-ogive harmonic analysis robust method (NOHARM) software. Previous simulation research has demonstrated that this approach does yield accurate and efficient estimates of item…
Descriptors: Item Response Theory, Computation, Test Items, Simulation
Wang, Wen-Chung; Jin, Kuan-Yu – Applied Psychological Measurement, 2010
In this study, all the advantages of slope parameters, random weights, and latent regression are acknowledged when dealing with component and composite items by adding slope parameters and random weights into the standard item response model with internal restrictions on item difficulty and formulating this new model within a multilevel framework…
Descriptors: Test Items, Difficulty Level, Regression (Statistics), Generalization
Peer reviewedKim, Seock-Ho; Cohen, Allan S. – Applied Psychological Measurement, 1998
Compared three methods for developing a common metric under item response theory through simulation. For smaller numbers of common items, linking using the characteristic curve method yielded smaller root mean square differences for both item discrimination and difficulty parameters. For larger numbers of common items, the three methods were…
Descriptors: Comparative Analysis, Difficulty Level, Item Response Theory, Simulation
Peer reviewedLiou, Michelle – Applied Psychological Measurement, 1988
In applying I. I. Bejar's method for detecting the dimensionality of achievement tests, researchers should be cautious in interpreting the slope of the principal axis. Other information from the data is needed in conjunction with Bejar's method of addressing item dimensionality. (SLD)
Descriptors: Achievement Tests, Computer Simulation, Difficulty Level, Equated Scores
Peer reviewedMeijer, Rob R.; And Others – Applied Psychological Measurement, 1994
The power of the nonparametric person-fit statistic, U3, is investigated through simulations as a function of item characteristics, test characteristics, person characteristics, and the group to which examinees belong. Results suggest conditions under which relatively short tests can be used for person-fit analysis. (SLD)
Descriptors: Difficulty Level, Group Membership, Item Response Theory, Nonparametric Statistics

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