| Summary: | This text provides a comprehensive treatment of multidimensional scaling (MDS), a statistical technique used to anlayze the structure of similarity or dissimilarity data in multidimensional space. Such data are widespread, for example, intercorrelations of attitude items, direct ratings of similarity on choice objects, or trade indices for a set of countries. MDS models such data as distances among points in a geometric space of low dimensionality; this makes complex data sets accessible to visual exploration and thus aids in seeing structures not obvious from the numbers. Other uses of MDS interpret the geometry and, in particular, the distance function as a psychological composition rule.
|
|---|
