More often than not, a market research survey consists of at least one multiple-response question. A multi-response question allows respondents to give more than one answer. This type of question usually appears in Dispalyr as a Binary - Multi or Binary - Grid variable set. This article describes how you should configure the Value Attributes.
- Familiarity with the Structure and Value Attributes of Variable Sets.
- A data set loaded into a Displayr document.
Binary - Multi or Binary - Grid questions have a different Value Attributes window from other question types. There is a column called Count this Value which is used to indicate which response code should be counted (in the Count statistic) in the table for a particular question. There is no Value column, as the numeric values do not play a role for this kind of data.
To access the Value Attributes dialog box:
- Select a Binary - Multi or Binary - Grid variable set in the Data Sets tree.
- In the object inspector on the right of your screen, click Properties > DATA VALUES > Select categories.
- You will see a window pop-up similar to above with two columns, one for Count this Value and one for Missing Values. The Count this Value checkbox tells Displayr which responses you want to count. The Missing Values dropdown tells Displayr which codes should be ignored from the question and should be excluded from the Sample Size. More detail is in our Variable Sets article.
The following examples show you what the Value Attributes should look like for the different scenarios.
Your variable is coded as: selected, not selected, and missing data
The following Binary Multi question is by far the best way to set up a Binary Multi question.
Your variable is coded as: selected and not selected codes OR selected and missing
The Value Attributes for this question has two possible response codes for each option: Yes and No or Missing and No. Therefore, the selections in the Count This Value column will indicate that when calculating the percentages and other statistics.
Your variable is coded as: No to option and option OR missing and option
You can see that the Value Attributes are set up similarly to the selected and not selected variables above.
How to Turn Off Missing Data Selection for Specific Values
Watch our Understanding Variable Sets video
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