Joint correspondence analysis (JCA) is an adaptation of multiple correspondence analysis to fit only the off-diagonal blocks of the Burt matrix, assuming the diagonal blocks are missing. In this talk we review the properties of JCA and show how it improves the graphical display of the set of two-way associations of a set of categorical variables. We also discuss the dimensionality of the solution, measures of fit and the role of the numerical contributions in the interpretation of the solution.

Key words: correspondence analysis, graphical display

See also: The Millennium Song