The SPSS Statistics Crosstabs procedure forms two-way and multi-way tables (and provides a variety of tests and measures of association for the two-way tables). The structure of the table and whether categories are ordered determine what test or measure to use.
Crosstabs’ statistics and measures of association are computed for two-way tables only.
If you specify:
- a row,
- a column, and
- a layer factor (control variable),
The Crosstabs procedure forms one panel of associated statistics and measures for each value of the layer factor.
Here is a simple Example
If gender is a layer factor for a table of married (yes, no) against life (is life happy, sad or dull), the results for a two-way table for the females are computed separately from those for the males and printed as panels following one another.
The cross tabulation table is the basic technique for examining the relationship between two categorical variables. In the above example, the question might be “what bearing does gender have on how married life is perceived?”
Our example data is defined with only 3 variables:
- Gender (1 = male, 2 = female)
- Married (1 = yes, 2 = no)
- Happy (1 = happy, 2 = sad or 3 = bored)
Now, to run a quick crosstab on this data pool, from the Data Viewer menu, you choose Analyze > Descriptive Statistics > Crosstabs…
On the “Crosstabs” dialog I select “Gender” as my layer factor and “Married” and “Happy” as columns for my table. For this simple exercise I just click “OK”.
These selections generate a “Case Processing Summary Table” and a “Layer Factor Count” and, as I’d hoped a “Gender Happy” cross tabulation:
Based upon my very small data pool it would appear that most married male respondents are “Bored” while most married female respondents are “Happy”.
“Dare to wear the foolish clown face.” – Frank Sinatra
