Introduction to Multidimensional Scaling and Its Applications

Although Richardson (1938) and Young and (1938) may have officially initiated multidimensional scaling (MDS) literature in, frequent applications did not begin to until the seminal papers on nonmetric MDS by Shepard (1962) and Kruskal (1964). Twenty later, it is time to critically examine the MDS and its contribution to psychology. The two papers in this special issue review statistical in MDS with an emphasis on design of MDS studies. The last four papers the MDS research in four areas of common: consumer, social, cognitive, and psychology. and Arabie (1980) have described two to define MDS. According to the broader of two definitions, MDS means a set of techniques estimating parameters in geometric models so to yield a representation of data structure. Such broad definition would encompass cluster, discriminant, factor analysis. These techniques treated here as alternatives to MDS, rather than methods included within it. In this special issue, MDS literature refers to a body of knowledge (1) a set of statistical techniques for estimating parameters in and assessing the fit of spatial distance models for proximity or preference data and (2) the coordinate representations stimulus structure that result from such techniques. introduction first briefly reviews the past 50 years of developments in MDS, developments more extensively by Coxon (1982), Davison (1993), Kruskal and Wish (1978), and Schiffman, , and Young (1981). Then it summarizes six papers that follow.