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SHS Lite - User Guide: A guide to using the Scottish Household Survey simplified dataset
6.3 Crosstabs
Crosstabulation tables can be used to show the relationship between two or more variables. Unlike frequencies, we can display variables in both the rows and columns of the table.
An illustrative example can be found in Section 8.4 on page . For easy reference however, the basic steps that you would need to take are given below.
6.3.1 Creating a Crosstab Table
Figure 21 - Crosstabs dialog box
Figure 22 - Housing Tenure by Property Type Crosstab
6.3.2 Creating a Three-Way Crosstab Table
You can add a layer variable to create a three-way table in which categories of the row and column variables are further subdivided by categories of the layer variable.
This variable is sometimes referred to as the control variable because it may reveal how the relationship between the row and column variables changes when you "control" for the effects of the third variable.
An illustrative example can be found in Section 8.10 on page . For easy reference however, the basic steps you would need to take are given below.
Figure 23 - Crosstabs dialog box showing layer variable
Figure 24 - Cell Display dialog box
Figure 25 - Number of Cars by Housing Tenure by Property Type Crosstab
While a two-way crosstabulation would allow you to say that owner-occupiers are more likely than people in rented tenure to have one or more cars, the three-way crosstabulation shows that while this relationship is generally true, the difference is less among people who have detached and semi-detached houses. Also, owner-occupiers in flats are more likely than other owner-occupiers to have no cars, probably reflecting less need for a car in towns and cities and the difficulty of parking.
6.3.3 Splitting the File
This procedure splits the data file into separate groups for analysis based on the values of a grouping variable. This has a similar effect to running a three-way crosstab, splitting analysis by the specified variable, but Split File stays on until you switch it off and it applies to all analysis. It is useful if you want to carry out a lot of comparative analysis, comparing, for example, people who recycle and those who don't or people in different tenure groups.
An example of analysis after splitting the file can be found in Section 8.6 on page .
Figure 26 - Split File dialog box
! Note | All further analyses carried out on the data will use the separate groups created by splitting the file as we have done above. For example, the results of frequencies and crosstabs will be grouped by the variables used to split the file. |
! Note | To 'un-split' your file, select Data, Split File… from the menu bar, and click 'Analyse all cases, do not create groups'. |
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