Introduces a new approach for partitioning test items into dimensionally distinct item clusters. The core of this approach is a new item-pair conditional-covariance-based proximity measure that can be used with hierarchical cluster analysis. The procedure can correctly classify, on average, over 90% of the items for correlations as high as 0.9.…

The purpose of this paper is to examine the capabilities of various procedures for sorting dichotomously-scored items into unidimensional subjects. The procedures include: factor analysis, nonmetric multidimensional scaling, cluster analysis, and latent trait analysis. Both simulated and real data sets of known structure were used to evaluate the…

The technique of nonmetric multidimensional scaling (MDS) was applied to real item response data obtained from a multiple-choice achievement test of unknown dimensionality. The goal was to classify the 50 items into the various subtests from which they were drawn originally, the latter being unknown to the investigator. Issues addressed in the…

Cliff's Index "c" derived from an item dominance matrix is utilized in a clustering approach, termed extracting Reliable Guttman Orders (ERGO), to isolate Guttman-type item hierarchies. A comparison of factor analysis to the ERGO is made on social distance data involving multiple ethnic groups. (Author/BW)

A new method for evaluating the content representation of a test is illustrated. Item similarity ratings were obtained from three content domain experts to assess whether ratings corresponded to item groupings specified in the test blueprint. Multidimensional scaling and cluster analysis provided substantial information about the test's content…

A few multi-dimensional items were found to be more efficient than a larger number of uni-dimensional items in tests for participant selection and evaluation of such compensatory educational programs as Title I. A multi-dimensional scaling technique is described which derives scores for each item on three dimensions, and allows multiple scores to…

A comparison was made of responses to two types of personality inventory items, either sentence-type items or adjective-type items. Three methods of analysis were applied. It was concluded that the two item types give approximately equal results. (CTM)

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…

An expanded version of the method of content evaluation proposed by S. G. Sireci and K. F. Giesinger (1992) was evaluated with respect to a national licensure examination and a nationally standardized social studies achievement test. Two groups of 15 subject-matter experts rated the similarity and content relevance of the items. (SLD)

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…

A procedure for interpreting multiple-discrimination indices from a multidimensional item-response theory analysis is described and demonstrated with responses of 1,635 high school students to a multiple-choice test. The procedure consists of converting discrimination parameter estimates to direction cosines and analyzing the angular distances…

Various methods used to assess the content of a test are reviewed, and a new procedure designed to improve on these methods is presented. The two tests considered are a professional licensure examination, the auditing section of the Uniform Certified Public Accountant Examination, and an educational achievement test, a nationally standardized…