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Peer reviewedLiou, Michelle – Applied Psychological Measurement, 1994
A recursive equation is proposed for computing higher order derivatives of elementary symmetric functions in the Rasch model. A simulation study indicates a small loss in accuracy for the proposed formula compared to Gustafsson's sum algorithm (1980) for computing higher order derivatives when tests contain 60 items or less. (SLD)
Descriptors: Algorithms, Computation, Item Response Theory, Simulation
Peer reviewedEggen, T. J. H. M. – Applied Psychological Measurement, 1999
Evaluates a method for item selection in adaptive testing that is based on Kullback-Leibler information (KLI) (T. Cover and J. Thomas, 1991). Simulation study results show that testing algorithms using KLI-based item selection perform better than or as well as those using Fisher information item selection. (SLD)
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Selection
Peer reviewedMuraki, Eiji – Applied Psychological Measurement, 1992
The partial credit model with a varying slope parameter is developed and called the generalized partial credit model (GPCM). Analysis results for simulated data by this and other polytomous item-response models demonstrate that the rating formulation of the GPCM is adaptable to the analysis of polytomous item responses. (SLD)
Descriptors: Algorithms, Equations (Mathematics), Generalization, Item Response Theory
