How to Conduct Column Comparisons between variables in a Number - Multi question

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The Column Comparisons statistical testing is not available for crosstabs where the question that is selected in the Brown menu is a Number - Multi question, and it is not possible to create a SUMMARY table for a Number - Multi question such that the variables are shown along the columns to facilitate the Column Comparisons. The methods below work around these restrictions by converting the question to a Pick One - Multi and showing the Column Comparisons and Average in the Statistics - Below.

Note that if your crosstab has the Number - Multi question in the Blue menu and a categorical question in the Brown menu then you can use the column comparisons as normal and you do not need to consider the methods discussed here.

Column Comparisons for a Number - Multi SUMMARY

  1. Highlight the variables for the Number - Multi question in the Variables and Questions tab.
  2. Right-click and select Copy and Paste Questions > Exact Copy.
  3. Click in the Question Type column for one of the copied variables and select Pick One - Multi.
  4. Make a new table and show the new question in the Blue drop-down menu.
  5. Ensure that the variables are placed in the columns of the table by right-clicking on the row labels and selecting Swap Rows and Columns.
  6. Right-click on the table and select Average, Column Comparisons, and Column Names from the Statistics - Below.
  7. Highlight all but one of the row labels in the table, right-click, and select Hide.

The Column Comparisons below the table show the results of the comparisons between the Averages shown below the table.

Column Comparisons for a Number - Multi Crosstab

It is not possible to have all of the results in a single table, and they must instead be spread across several tables where each table has an appropriate filter applied.

  1. Perform the steps above.
  2. Make a copy of the table for each category you would ordinarily place in the rows of the table.
  3. Apply the appropriate filter to each table.