Burt Tables
Multiple
correspondence analysis expects as input (i.e., the program will compute
prior to the analysis) a socalled Burt
table. The Burt table
is the result of the inner product of a design or indicator matrix. If
you denote the data (design or indicator matrix) as matrix X, then matrix
product X'X is a Burt
table); shown below is an example of a Burt
table that one might obtain in this manner.

SURVIVAL 
AGE 
LOCATION 
NO 
YES 
<50 
5069 
69+ 
TOKYO 
BOSTON 
GLAMORGN 
SURVIVAL:NO
SURVIVAL:YES
AGE:UNDER_50
AGE:A_50TO69
AGE:OVER_69
LOCATION:TOKYO
LOCATION:BOSTON
LOCATION:GLAMORGN 
210
0
68
93
49
60
82
68 
0
554
212
258
84
230
171
153 
68
212
280
0
0
151
58
71 
93
258
0
351
0
120
122
109 
49
84
0
0
133
19
73
41 
60
230
151
120
19
290
0
0 
82
171
58
122
73
0
253
0 
68
153
71
109
41
0
0
221 
Overall, the data matrix is symmetrical. In the case of
3 categorical variables (as shown above), the data matrix consists 3 x
3 = 9 partitions, created by each variable being tabulated against itself,
and against the categories of all other variables. Note that the sum of
the diagonal elements in each diagonal partition (i.e., where the respective
variables are tabulated against themselves) is constant (equal to 764
in this case). The offdiagonal elements in each partition in this example
are all 0. If the cases in the design or indicator matrix are assigned
to categories via fuzzy coding, then the offdiagonal elements of the
diagonal partitions are not necessarily equal to 0. For more information,
refer to the description of correspondence
analysis, and to the description of Burt
tables in the context of that module.