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Spence, Ian; Lewandowsky, Stephan – Psychometrika, 1989
A method for multidimensional scaling that is highly resistant to the effects of outliers is described. Some Monte Carlo simulations illustrate the efficacy of the procedure, which performs well with or without outliers. (SLD)
Descriptors: Estimation (Mathematics), Mathematical Models, Monte Carlo Methods, Multidimensional Scaling
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)
Jones, Patricia B.; And Others – 1987
In order to determine the effectiveness of multidimensional scaling (MDS) in recovering the dimensionality of a set of dichotomously-scored items, data were simulated in one, two, and three dimensions for a variety of correlations with the underlying latent trait. Similarity matrices were constructed from these data using three margin-sensitive…
Descriptors: Cluster Analysis, Correlation, Difficulty Level, Error of Measurement