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Urry, Vern W. – 1983
In this report, selection theory is used as a theoretical framework from which mathematical algorithms for tailored testing are derived. The process of tailored, or adaptive, testing is presented as analogous to personnel selection and rejection on a series of continuous variables that are related to ability. Proceeding from a single common-factor…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Latent Trait Theory
Skaggs, Gary; Stevenson, Jose – 1986
This study assesses the accuracy of ASCAL, a microcomputer-based program for estimating item parameters for the three-parameter logistic model in item response theory. Item responses are generated from a three-parameter model, and item parameter estimates from ASCAL are compared to the generating item parameters and to estimates produced by…
Descriptors: Algorithms, Comparative Analysis, Computer Software, Estimation (Mathematics)
Panter, A. T.; Tanaka, J. S. – 1989
A theoretical framework for incorporating item response theory into the measurement of attitude and other personality processes is presented. The person by item model is introduced by considering the conceptual usefulness of such a model in understanding item responding, outlining the form of the model, briefly discussing methods for examining the…
Descriptors: Algorithms, Attitude Measures, High School Students, High Schools
Muraki, Eiji – 1984
This study examines the application of the marginal maximum likelihood (MML) EM algorithm to the parameter estimation problem of the three-parameter normal ogive and logistic polychotomous item response models. A three-parameter normal ogive model, the Graded Response model, has been developed on the basis of Samejima's two-parameter graded…
Descriptors: Algorithms, Data Analysis, Estimation (Mathematics), Goodness of Fit
Mislevy, Robert J. – 1985
A method for drawing inferences from complex samples is based on Rubin's approach to missing data in survey research. Standard procedures for drawing such inferences do not apply when the variables of interest are not observed directly, but must be inferred from secondary random variables which depend on the variables of interest stochastically.…
Descriptors: Algorithms, Data Interpretation, Estimation (Mathematics), Latent Trait Theory