MULTIPLE SCALING MODELS FOR ANALYZING AND REPRESENTING MULTIDIMENSIONAL CONCEPTS

Course Description
Complex behavioral systems may be modeled by multiple scaling and lattice space analysis. Such models have been applied in intelligence research, inductive ability, knowledge systems, marketing, motivation research, quality of life research, among other domains. In this research seminar nonmetric procedures (incl. Faceted SSA, POSAC/LSA) for organizing and analyzing data are presented. Theory construction and structural hypothesis testing are demonstrated in uncontrolled experiments, where (as e.g. in clinical research) there are no "independent variables". Students are guided in planning and carrying out an original application of the models in a topic of their choice. The seminar is open to M.A. and PhD students and is limited to ten participants.

Bibliography

Borg, I. & Shye, S. (1995). Facet Theory: Form and Content. Thousand Oaks CA: Sage.

Shye, S. (1985). Nonmetric multivariate models for behavioral action systems. In D. Canter (ed.) Facet Theory: Approaches to Social Research (97-148). New York: Springer.

Shye, S. (1985). Multiple Scaling: The Theory and Application of Partial Order Scalogram Analysis. Amsterdam: North-Holland.
Reviews of the book

Shye, S. & Elizur, D. (1994). Introduction to Facet Theory: Content Design and Intrinsic Data Analysis in Behavioral Research. Thousand Oaks, CA: Sage.

Shye, S. Modern facet theory: content design and measurement in behavioral research. European Journal of Psychological Assessment, 14, (2), 160-171, 1998.

Shye, S. Facet Theory. Encyclopedia of Statistical Sciences, Update, Vol. 3. New York: Wiley, 1999, 231-239.