All commonly-used statistics on tables, such as %, Column %, and Average, are computed using the base. It is often necessary to rebase tables (i.e., modifying the sample size used in the calculation of statistics). For example, tables may be rebased to address data integrity issues or to see results among a particular sub-group. This can be done using a range of different methods, as follows.
The most straightforward approach to rebasing a table is to create and apply a Filter.
On tables where there is a desire to rebase the table using data on that table (e.g., re-basing to only show people that have purchased a subset of brands), you can do this by:
- Selecting the cells that you wish to include in the base.
- Right-clicking on the cell and selecting Create filter.
- Ensure that Apply filter to the current table is selected.
- Give the filter a useful question name.
- Press OK.
Where there is grid data, Q will not let you create a filter directly from the table itself (because the cells in the table all have the same sample size, so most of the time when a user would attempt to do this it would be because they did not understand the structure of the data). This can be worked around by creating a filter on the Variables and Questions tab, by right-clicking on a row and select Insert Variable(s) > Binary - Complicated Filter.
Note also that where you have multiple response data (e.g., Pick Any questions), it is not guaranteed that the categories not selected end up with only 0s on the table.
Modifying the Value Attributes
The base used in computations on a table can be adjusted by right-clicking on the rows or column headings on the table, and selecting Values and modifying the Value Attributes, by either:
- Changing which categories have Missing Data selected (if it is selected for a value, cases with that value are excluded).
- Changing which categories have a Value of NaN. This works the same way as Missing Data but is only applicable for numeric questions, and thus it is possible, for example, to have Don't Know responses included in percentages selected in Statistics - Cells but excluded from the Average calculations in Statistics - Below and Statistics - Right.
A short-cut to excluding categories is to right-click on their row or column headings on the table and select Remove.
While modifying Value Attributes is generally the preferred approach if addressing data integrity issues, it is only possible in situations where the original data file contains useful missing values. In particular, if the data file uses the same value to indicate a respondent saw but did not choose an option as is used to indicate that they did not see an option, it becomes impossible to rebase by using the value attributes.
Creating new variables that are filtered
A new version of a question can be created in which the underlying data has been modified such that certain cases are excluded. The most straightforward approach to doing this is to use Filtering - Filter One Question by Another.
Where there is a desire to rebase all the data in the project by removing some respondents, this is best achieved by deleting cases.
For example, Filtering - Apply Filters to Columns or Rows.