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The paired preference test is not suitable for all tables. It is up to you to make sure that the data in the table is generally suitable for testing, that the sample size is suitable, etc.
The paired preference element is usually specified in a row to compare two rows for each column independently. However, you can specify it in a column to compare two columns for each row independently. The following information assumes specification as a row.
Hierarchical data. This test is unsuitable for running on lower level data when you are working with hierarchical data. See the topic Hierarchical Data for more information.
Rows. The test searches for the nearest two categories preceding the paired preference row (or column) to perform the test on, but it stops searching at a base or another paired preference item, and if it has not found two categories by then it does not perform the test. The test ignores categories at a different net level.
Columns. The test works independently on all columns.
Sample size. This test relies on a large sample, which means that it may not be valid for a small sample--for example, fewer than about 30 cases. IBM® SPSS® Data Collection Survey Reporter checks for small sample sizes, and does not carry out the test on columns with a base below 30. You can change the minimum sample size if required, by entering a new value in the Minimum Base field in the Statistics tab.
Multiple response variables. The test is invalid if the two rows being tested can have overlap (that is, one person can belong in both of them). However, there is no way that Survey Reporter can check for this.
Two-tailed test. This is a two-tailed test, which means that it reports all significant differences between the proportions in all of the columns regardless of which row contains the greater proportions.