Clustering Rows and Columns

Up to now we have been transforming data matrices to maps or biplots where the rows and columns are displayed as points in a continuous space, usually a two-dimensional plane. An alternative way of displaying structure consists in performing separate cluster analyses on the row and column profiles. This approach has close connections to correspondence analysis (CA) and decomposes the inertia according to the discrete groupings of the profiles rather than along continuous axes. In the case of a contingency table there is an interesting spin-off of this analysis in the form of a statistical test for significant clustering of the rows or columns.