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Gonzalez, Oscar – Educational and Psychological Measurement, 2023
When scores are used to make decisions about respondents, it is of interest to estimate classification accuracy (CA), the probability of making a correct decision, and classification consistency (CC), the probability of making the same decision across two parallel administrations of the measure. Model-based estimates of CA and CC computed from the…
Descriptors: Classification, Accuracy, Intervals, Probability
Guerra-Peña, Kiero; Steinley, Douglas – Educational and Psychological Measurement, 2016
Growth mixture modeling is generally used for two purposes: (1) to identify mixtures of normal subgroups and (2) to approximate oddly shaped distributions by a mixture of normal components. Often in applied research this methodology is applied to both of these situations indistinctly: using the same fit statistics and likelihood ratio tests. This…
Descriptors: Growth Models, Bayesian Statistics, Sampling, Statistical Inference
Chen, Pei-Hua; Chang, Hua-Hua; Wu, Haiyan – Educational and Psychological Measurement, 2012
Two sampling-and-classification-based procedures were developed for automated test assembly: the Cell Only and the Cell and Cube methods. A simulation study based on a 540-item bank was conducted to compare the performance of the procedures with the performance of a mixed-integer programming (MIP) method for assembling multiple parallel test…
Descriptors: Test Items, Selection, Test Construction, Item Response Theory

McQuitty, Louis L.; Koch, Valerie L. – Educational and Psychological Measurement, 1975
Develops and illustrates a method for clustering hierarchically the interrelationships between many persons, as represented in a matrix of a thousand by a thousand. (RC)
Descriptors: Classification, Cluster Grouping, Matrices, Measurement Techniques

Koslowsky, Meni – Educational and Psychological Measurement, 1985
The technique of generalizing sample results in a classification study to large subpopulations of unequal sizes was examined. The usual output from the discriminant analysis routine in the Statistical Package for the Social Sciences was extended to handle the present statistical problems. Advantages of the technique were discussed. (Author/DWH)
Descriptors: Classification, Computer Software, Discriminant Analysis, Generalization

Hanges, Paul J.; And Others – Educational and Psychological Measurement, 1991
Whether it is possible to develop a classification function that identifies the underlying range restriction from sample information alone was investigated in a simulation. Results indicate that such a function is possible. The procedure was found to be relatively accurate, robust, and powerful. (SLD)
Descriptors: Classification, Computer Simulation, Equations (Mathematics), Mathematical Models