Cognitive diagnosis models (CDMs) are latent class multidimensional statistical models that help classify people accurately by using a set of discrete latent variables, commonly referred to as attributes. These models require a Q-matrix that indicates the attributes involved in each item. A potential problem is that the Q-matrix construction…

A method for evaluating the validity of multicomponent measurement instruments in heterogeneous populations is discussed. The procedure can be used for point and interval estimation of criterion validity of linear composites in populations representing mixtures of an unknown number of latent classes. The approach permits also the evaluation of…

The current study proposes novel methods to predict multistage testing (MST) performance without conducting simulations. This method, called MST test information, is based on analytic derivation of standard errors of ability estimates across theta levels. We compared standard errors derived analytically to the simulation results to demonstrate the…

In this study, we explored the potential for machine scoring of short written responses to the Classroom-Video-Analysis (CVA) assessment, which is designed to measure teachers' usable mathematics teaching knowledge. We created naïve Bayes classifiers for CVA scales assessing three different topic areas and compared computer-generated scores to…

This article investigates several methods of identifying individual guessers from their response data. Both the posterior probability method and the likelihood ratio method are based on the two-state mixture modeling approach to response times. The accuracy method is based on response accuracy data. Results from the simulation study showed that…

Shows how a theorem proven by H. Brogden (1951, 1959) can be used to estimate the allocation average (a predictor based classification of a test battery) assuming that the predictor intercorrelations and validities are known and that the predictor variables have a joint multivariate normal distribution. (SLD)

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)

Discussion of a method of classification which attempts to use the particular set of indices of association which produce the most reliable and valid solution. (PR)

The potential importance of suppressor variables in the personality domain was studied in classifying white-collar criminals with a validation sample of 435 prisoners and a cross-validation sample of 214. Results suggest that suppressor variables can increase prediction and may contribute to knowledge and theory development. (SLD)