See the following articles for more information:
Multiple response data can sometimes be stored in a format of fixed columns. This is where the multiple response information is encoded in the categories rather than in dichotomous variables. Multiple response variables in Crunch must be in a dichotomous format and the CREATE MULTIPLE SELECTION command can do this transformation.
Given a set of multiple categorical variables as input, the CREATE MULTIPLE SELECTION command returns a multiple response. Each of the resultant subvariables has one of the input categories as the selected value, which takes into consideration the combined responses of all the input rows. In other words, the "net" of each category across the input variables is transformed into a multiple response subvariable.
For example, you may have 10 input variables with the same 300 categories in each. The use of the CREATE MULTIPLE SELECTION command transforms it into one multiple response variable as an output that has 300 subvariables. Each of the output subvariables is named from the corresponding category label.
- NOT SELECTED — if there are categories you don’t wish to include as a subvariable in the multiple response variable output, then you can specify the categories to exclude. For example, 'None of these' might be a category you want to exclude. They can be referred to by category id (which is not the numeric value) or by label.
- EXCLUDE EMPTY — if any case (row of the dataset) does not have any responses across any of the resultant subvariables, then that case will have missing data in the output variable. In other words, the numeric tally for every case will be at least one.
CREATE MULTIPLE SELECTION alias, ..., alias [NOT SELECTED label|code, ..., label|code] [EXCLUDE EMPTY] AS alias [TITLE "string"] [DESCRIPTION "string"] [NOTES "string"];
In the Core Trends Mobile Broadband example, there are four categorical variables that encode race/ethnicity. The first variable captures the first response (hence no missing data) and then successively for the 2nd, 3rd, or even the 4th responses (e.g., if someone identifies with four different races):
The following script turns it into a single multiple response. In doing so, it optionally chooses to exclude the 'Don’t know' and 'Refused' categories, which become missing data in the result (n=59):
CREATE MULTIPLE SELECTION racem1, racem2, racem3, racem4 NOT SELECTED label|code, ..., label|code] AS race_mr [TITLE "Race”] [DESCRIPTION "Which of the following ethnicities do you identify with?"];
which results in the following: