This study aims to analyze the differential bundle functioning in multidimensional tests with a specific purpose to detect this effect through differentiating the location of the item with DIF in the test, the correlation between the dimensions, the sample size, and the ratio of reference to focal group size. The first 10 items of the test that is…

Positioning and repositioning continue to be critical topics in business strategy, and yet a review of current business research syllabi from several institutions showed that very few institutions teach the analytical underpinnings of how perceptual maps can be created using multidimensional scaling and how they should be interpreted. At the…

Researchers in many disciplines work with ranking data. This data type is unique in that it is often deterministic in nature (the ranks of items "k"-1 determine the rank of item "k"), and the difference in a pair of rank scores separated by "k" units is equivalent regardless of the actual values of the two ranks in…

Assessments of new pedagogical practices usually rely on instructor oriented surveys and questionnaires to measure student perceptions of teaching methods; however, fixed response categories in structured questionnaires might bias results. This paper demonstrates a mixed methods approach using open and multi-dimensional scaling (MDS) for a…

The authors discuss empirically determined competence areas to K-12 computer science education, emphasizing the cognitive level of competence. The results of a questionnaire with 120 professors of computer science serve as a database. By using multi-dimensional scaling and cluster analysis, four competence areas to computer science education…

Bayesian multidimensional scaling (MDS) has attracted a great deal of attention because: (1) it provides a better fit than do classical MDS and ALSCAL; (2) it provides estimation errors of the distances; and (3) the Bayesian dimension selection criterion, MDSIC, provides a direct indication of optimal dimensionality. However, Bayesian MDS is not…

A multidimensional unfolding technique that is not prone to degenerate solutions and is based on multidimensional scaling of a complete data matrix is proposed: distance information about the unfolding data and about the distances both among judges and among objects is included in the complete matrix. The latter information is derived from the…

Describes several salient features of multidimensional scaling (MDS) for spatial distance models including proximity measures, interpoint distances, goodness-of-fit, and distinctions between metric and nonmetric scaling. Four commonly used MDS computer programs are described, and a section on applications of MDS selected from the counseling…

This paper discusses how a seldom-used statistical procedure, recursive regression (RR), can numerically and graphically illustrate data-driven nonlinear relationships and interaction of variables. This routine falls into the family of exploratory techniques, yet a few interesting features make it a valuable compliment to factor analysis and…

The usefulness of L. Guttman's partial order scalogram analysis is investigated in this study of the structure of a set of items that measure attitudes toward legal abortion. These items, drawn from the National Opinion Research Center's "General Social Survey," have been the focus of considerable applied research investigating…

Describes the use of ALSCAL, a computer program for multidimensional scaling, to map enrollment in 49 electives at Drexel University's College of Information Studies during two time periods. The results for this department are presented, and the explanatory power of this evaluation technique for any curriculum is discussed. (6 references) (CLB)