15.7.1.1 Categorical Variables

An axis expression that names a categorical variable divides the data into cells according to the values of that variable. When all the variables named on TABLE are categorical, by default each cell displays the number of cases that it contains, so specifying a single variable yields a frequency table, much like the output of the FREQUENCIES command (see FREQUENCIES):

CTABLES /TABLE=ageGroup.
Custom Tables
Count
Age group 15 or younger 0
16 to 25 1099
26 to 35 967
36 to 45 1037
46 to 55 1175
56 to 65 1247
66 or older 1474

Specifying a row and a column categorical variable yields a crosstabulation, much like the output of the CROSSTABS command (see CROSSTABS):

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

The ‘>’ “nesting” operator nests multiple variables on a single axis, e.g.:

CTABLES /TABLE likelihoodOfBeingStoppedByPolice BY ageGroup > gender.
Custom Tables
86. In the past year, have you hosted a social event or party where alcohol was served to adults?
Yes No
Count Count
Age group 15 or younger S3a. GENDER: Male 0 0
Female 0 0
16 to 25 S3a. GENDER: Male 208 386
Female 202 303
26 to 35 S3a. GENDER: Male 225 251
Female 242 249
36 to 45 S3a. GENDER: Male 223 266
Female 240 307
46 to 55 S3a. GENDER: Male 201 325
Female 282 366
56 to 65 S3a. GENDER: Male 196 320
Female 279 452
66 or older S3a. GENDER: Male 162 367
Female 243 700

The ‘+’ “stacking” operator allows a single output table to include multiple data analyses. With ‘+’, CTABLES divides the output table into multiple sections, each of which includes an analysis of the full data set. For example, the following command separately tabulates age group and driving frequency by gender:

CTABLES /TABLE ageGroup + freqOfDriving 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
1. How often do you usually drive a car or other motor vehicle? Every day 2305 2362
Several days a week 440 834
Once a week or less 125 236
Only certain times a year 58 72
Never 192 348

When ‘+’ and ‘>’ are used together, ‘>’ binds more tightly. Use parentheses to override operator precedence. Thus:

CTABLES /TABLE hasConsideredReduction + hasBeenCriticized > gender.
CTABLES /TABLE (hasConsideredReduction + hasBeenCriticized) > gender.
Custom Tables
Count
26. During the last 12 months, has there been a time when you felt you should cut down on your drinking? Yes 513
No 3710
27. During the last 12 months, has there been a time when people criticized your drinking? Yes S3a. GENDER: Male 135
Female 49
No S3a. GENDER: Male 1916
Female 2126
Custom Tables
Count
26. During the last 12 months, has there been a time when you felt you should cut down on your drinking? Yes S3a. GENDER: Male 333
Female 180
No S3a. GENDER: Male 1719
Female 1991
27. During the last 12 months, has there been a time when people criticized your drinking? Yes S3a. GENDER: Male 135
Female 49
No S3a. GENDER: Male 1916
Female 2126