Journal of Applied Statistics, 30, 10, (2004), pp. 1101-1113
Abstract
We consider the joint visualization of two matrices which have common rows
and columns, for example multivariate data observed at two time points
or split accord-ing to a dichotomous variable. Methods of interest include
principal components analysis for interval-scaled data, or correspondence
analysis for frequency data or ratio-scaled variables on commensurate
scales. A simple result in matrix algebra shows that by setting up the
matrices in a particular block format, matrix sum and difference components
can be visualized. The case when we have more than two matrices is also
discussed and the methodology is applied to data from the International
Social Survey Program.
Other authors
Universitat Pompeu Fabra. Departament d'Economia i Empresa