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Reckase, Mark D.; McKinley, Robert L. – 1984
The purpose of this paper is to present a generalization of the concept of item difficulty to test items that measure more than one dimension. Three common definitions of item difficulty were considered: the proportion of correct responses for a group of individuals; the probability of a correct response to an item for a specific person; and the…
Descriptors: Difficulty Level, Item Analysis, Latent Trait Theory, Mathematical Models
McKinley, Robert L.; Reckase, Mark D. – 1982
The usefulness of the general Rasch model for multidimensional data, from the most simple formulations to the more complex versions of the model, is explored. Also investigated was whether the parameters of the models could be readily interpreted. Models investigated included: (1) the vector model; (2) the product term model; (3) the vector and…
Descriptors: Data Analysis, Factor Analysis, Goodness of Fit, Latent Trait Theory
Reckase, Mark D.; McKinley, Robert L. – 1982
This paper reviews the existing multidimensional item response theory (IRT) models and demonstrates how one of the models can be applied to estimation of abilities from a test measuring more than one dimension. The purposes of this paper were threefold. First, the fundamental concepts required when considering multidimensional models for the…
Descriptors: Estimation (Mathematics), Higher Education, Latent Trait Theory, Mathematical Models
Reckase, Mark D. – 1981
One of the major assumptions of latent trait theory is that the items in a test measure a single dimension. This report describes an investigation of procedures for forming a set of items that meet this assumption. Factor analysis, nonmetric multidimensional scaling, cluster analysis and latent trait analysis were applied to simulated and real…
Descriptors: Cluster Analysis, Difficulty Level, Factor Analysis, Guessing (Tests)