Multiple Correspondence Analysis (MCA):
Multiple correspondence analysis (MCA) is an extension of correspondence analysis (CA) to the case of more than two variables. The initial data for MCA are three-way or m-way contingency tables.
In case of three variables, a common approach to MCA is to combine the two least interesting variables. Values (categories) of the variable of maximal interest are rows; combinations of values of the remaining two variables are columns. Computations are the same as in CA, but different symbols are used for plotting, depending on the values of one of the two remaining variables.