[NA] is a special value which represents "Not available", "Not applicable", or "No answer". It can happen when:
- Someone skips a question due to a skip pattern
- Survey logic doesn't force an answer
- A profile variable has no recorded value
- The analyst removes outliers for individual questions
E.g. Here's a hypothetical survey with two questions:
- Question 2: Did you eat breakfast today? [YES/NO]
- Question 2A: [IF Q2=Yes] What did you eat for breakfast today?
Below, respondents who answer 'No' to Question 2 skip Question 2A. This makes sense -- if we know they did not eat breakfast, then let's not ask what they ate.
Try toggling the [NA] button and see how the percentages in Question 2A change below:
There are two ways we can look at the data for such questions:
- SHIFT+Click on the [NA] value in the element to filter out all people who didn't answer the question.
This will reduce the subset size (e.g.
rom N=400 to N=104), and All other elements will update to reflect just those respondents.
- Click the [NA] button in the toolbar to toggle how [blank] values are handled This will remove [blank] values from percent calculations. But it does not actually drill in or change the active subset, so frequency counts are unchanged, and we still see all the data for other elements.