SPSS® 12.0 Command Syntax Reference

CORRESPONDENCE 289
DIM1...DIMn Numerical variables containing the row and column scores for each
dimension. Each variable is labeled DIMn, where n represents the
dimension number.
The variables in the VARIANCE matrix data file and their values are:
ROWTYPE_ String variable containing the value COV for all of the cases in the file.
SCORE_ String variable containing the value SINGULAR, the row variable’s
name (or label), and the column variable’s name (or label).
LEVEL_ String variable containing the row variable’s values (or labels), the
column variable’s values (or labels), and a blank value for score_ =
SINGULAR.
VARNAME_ String variable containing the dimension number.
DIM1...DIMn Numerical variables containing the variances and covariances for
each dimension. Each variable is named DIMn, where n represents the
dimension number.
See the SPSS Syntax Reference Guide for more information on matrix data files.
Analyzing Aggregated Data
To analyze aggregated data, such as data from a crosstabulation where cell counts are
available but the original raw data are not, you can use the WEIGHT command before
CORRESPONDENCE.
Example
To analyze a 3 ×
3 table such as the one shown in Table 1, you could use these commands:
DATA LIST FREE/ BIRTHORD ANXIETY COUNT.
BEGIN DATA
1 1 48
1 2 27
1 3 22
2 1 33
2 2 20
2 3 39
3 1 29
3 2 42
3 3 47
END DATA.
WEIGHT BY COUNT.
CORRESPONDENCE TABLE=BIRTHORD (1,3) BY ANXIETY (1,3).
• The WEIGHT command weights each case by the value of COUNT, as if there are 48 subjects
with BIRTHORD=1 and ANXIETY=1, 27 subjects with BIRTHORD=1 and ANXIETY=2,
and so on.
• CORRESPONDENCE can then be used to analyze the data.
• If any of the table cell values equals 0, the WEIGHT command issues a warning, but the
CORRESPONDENCE analysis is done correctly.