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Liou, 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
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Eggen, 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 reviewed Peer reviewed
Muraki, 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
Peer reviewed Peer reviewed
Andrich, David – Applied Psychological Measurement, 1988
A simple probabilistic model for unfolding data collected by a direct response design in which responses were scored dichotomously was applied to the measurement of attitudes toward capital punishment. Responses conformed to the unfolding mechanism. Scale values of the statements were statistically equivalent to those of Thurstone's methods. (SLD)
Descriptors: Algorithms, Attitude Measures, Capital Punishment, Computer Simulation
Peer reviewed Peer reviewed
Reise, Steven P.; Due, Allan M. – Applied Psychological Measurement, 1991
Previous person-fit research is extended through explication of an unexplored model for generating aberrant response patterns. The proposed model is then implemented to investigate the influence of test properties on the aberrancy detection power of a person-fit statistic. Difficulties of aberrancy detection are discussed. (SLD)
Descriptors: Algorithms, Computer Simulation, Item Response Theory, Mathematical Models
Peer reviewed Peer reviewed
Rost, Jurgen – Applied Psychological Measurement, 1990
Combining Rasch and latent class models is presented as a way to overcome deficiencies and retain the positive features of both. An estimation algorithm is outlined, providing conditional maximum likelihood estimates of item parameters for each class. The model is illustrated with simulated data and real data (n=869 adults). (SLD)
Descriptors: Adults, Algorithms, Computer Simulation, Equations (Mathematics)
Peer reviewed Peer reviewed
Muraki, Eiji – Applied Psychological Measurement, 1990
This study examined the application of the marginal maximum likelihood-EM algorithm to the parameter estimation problems of the normal ogive and logistic polytomous response models for Likert-type items. A rating scale model, based on F. Samejima's (1969) graded response model, was developed. (TJH)
Descriptors: Algorithms, Computer Simulation, Equations (Mathematics), Goodness of Fit
Peer reviewed Peer reviewed
Andrich, David – Applied Psychological Measurement, 1989
A probabilistic item response theory (IRT) model is developed for pair-comparison design in which the unfolding principle governing the choice process uses a discriminant process analogous to Thurstone's Law of Comparative Judgment. A simulation study demonstrates the feasibility of estimation, and two examples illustrate the implications for…
Descriptors: Algorithms, Computer Simulation, Discrimination Learning, Equations (Mathematics)