Next: , Previous: , Up: CTABLES   [Contents][Index]

15.7.4 Category Label Positions

/CLABELS {AUTO | {ROWLABELS|COLLABELS}={OPPOSITE|LAYER}}

The CLABELS subcommand controls the position of category labels for the TABLE subcommand that it follows. By default, or if AUTO is specified, category labels for a given variable nest inside the variable’s label on the same axis. For example, the command below results in age categories nesting within the age group variable on the rows axis and gender categories within the gender variable on the columns axis: 

CTABLES /TABLE ageGroup BY gender.
Custom Tables
S3a. GENDER:
Male Female
Count Count
Age group 15 or younger 0 0
16 to 25 594 505
26 to 35 476 491
36 to 45 489 548
46 to 55 526 649
56 to 65 516 731
66 or older 531 943

ROWLABELS=OPPOSITE or COLLABELS=OPPOSITE move row or column variable category labels, respectively, to the opposite axis. The setting affects only the innermost variable or variables, which must be categorical, on the given axis. For example: 

CTABLES /TABLE ageGroup BY gender /CLABELS ROWLABELS=OPPOSITE.
CTABLES /TABLE ageGroup BY gender /CLABELS COLLABELS=OPPOSITE.
Custom Tables
S3a. GENDER:
Male Female
15 or younger 16 to 25 26 to 35 36 to 45 46 to 55 56 to 65 66 or older 15 or younger 16 to 25 26 to 35 36 to 45 46 to 55 56 to 65 66 or older
Count Count Count Count Count Count Count Count Count Count Count Count Count Count
Age group 0 594 476 489 526 516 531 0 505 491 548 649 731 943
Custom Tables
S3a. GENDER:
Count
Age group 15 or younger Male 0
Female 0
16 to 25 Male 594
Female 505
26 to 35 Male 476
Female 491
36 to 45 Male 489
Female 548
46 to 55 Male 526
Female 649
56 to 65 Male 516
Female 731
66 or older Male 531
Female 943

ROWLABELS=LAYER or COLLABELS=LAYER move the innermost row or column variable category labels, respectively, to the layer axis.

Only one axis’s labels may be moved, whether to the opposite axis or to the layer axis.

Effect on Summary Statistics

CLABELS primarily affects the appearance of tables, not the data displayed in them. However, CTABLES can affect the values displayed for statistics that summarize areas of a table, since it can change the definitions of these areas.

For example, consider the following syntax and output: 

CTABLES /TABLE ageGroup BY gender [ROWPCT, COLPCT].
Custom Tables
S3a. GENDER:
Male Female
Row % Column % Row % Column %
Age group 15 or younger . .0% . .0%
16 to 25 54.0% 19.0% 46.0% 13.1%
26 to 35 49.2% 15.2% 50.8% 12.7%
36 to 45 47.2% 15.6% 52.8% 14.2%
46 to 55 44.8% 16.8% 55.2% 16.8%
56 to 65 41.4% 16.5% 58.6% 18.9%
66 or older 36.0% 17.0% 64.0% 24.4%

Using COLLABELS=OPPOSITE changes the definitions of rows and columns, so that column percentages display what were previously row percentages and the new row percentages become meaningless (because there is only one cell per row): 

CTABLES
    /TABLE ageGroup BY gender [ROWPCT, COLPCT]
    /CLABELS COLLABELS=OPPOSITE.
Custom Tables
S3a. GENDER:
Row % Column %
Age group 15 or younger Male . .
Female . .
16 to 25 Male 100.0% 54.0%
Female 100.0% 46.0%
26 to 35 Male 100.0% 49.2%
Female 100.0% 50.8%
36 to 45 Male 100.0% 47.2%
Female 100.0% 52.8%
46 to 55 Male 100.0% 44.8%
Female 100.0% 55.2%
56 to 65 Male 100.0% 41.4%
Female 100.0% 58.6%
66 or older Male 100.0% 36.0%
Female 100.0% 64.0%

Moving Categories for Stacked Variables

If CLABELS moves category labels from an axis with stacked variables, the variables that are moved must have the same category specifications (see Per-Variable Category Options) and the same value labels.

The following shows both moving stacked category variables and adapting to the changing definitions of rows and columns: 

CTABLES /TABLE (likelihoodOfBeingStoppedByPolice
                + likelihoodOfHavingAnAccident) [COLPCT].
CTABLES /TABLE (likelihoodOfBeingStoppedByPolice
                + likelihoodOfHavingAnAccident) [ROWPCT]
  /CLABELS ROW=OPPOSITE.
Custom Tables
Column %
105b. How likely is it that drivers who have had too much to drink to drive safely will A. Get stopped by the police? Almost certain 10.2%
Very likely 21.8%
Somewhat likely 40.2%
Somewhat unlikely 19.0%
Very unlikely 8.9%
105b. How likely is it that drivers who have had too much to drink to drive safely will B. Have an accident? Almost certain 15.9%
Very likely 40.8%
Somewhat likely 35.0%
Somewhat unlikely 6.2%
Very unlikely 2.0%
Custom Tables
Almost certain Very likely Somewhat likely Somewhat unlikely Very unlikely
Row % Row % Row % Row % Row %
105b. How likely is it that drivers who have had too much to drink to drive safely will A. Get stopped by the police? 10.2% 21.8% 40.2% 19.0% 8.9%
105b. How likely is it that drivers who have had too much to drink to drive safely will B. Have an accident? 15.9% 40.8% 35.0% 6.2% 2.0%

Next: Per-Variable Category Options, Previous: Statistics Positions and Labels, Up: CTABLES   [Contents][Index]