Working with Multiple-Response Data

A number of comparison functions can be used to analyze multiple-response data, including:

• value_at
• first_index / last_index
• first_non_null / last_non_null
• first_non_null_index / last_non_null_index
• min_index / max_index

For example, suppose a multiple-response question asked for the first, second, and third most important reasons for deciding on a particular purchase (for example, price, personal recommendation, review, local supplier, other). In this case, you might determine the importance of price by deriving the index of the field in which it was first included:

first_index("price", [Reason1 Reason2 Reason3])

Similarly, suppose you have asked customers to rank three cars in order of likelihood to purchase and coded the responses in three separate fields, as follows:

In this case, you could determine the index of the field for the car they like most (ranked #1, or the lowest rank) using the min_index function:

min_index(['car1' 'car2' 'car3'])

See the topic Comparison Functions for more information.

Referencing Multiple-Response Sets

The special @MULTI_RESPONSE_SET function can be used to reference all of the fields in a multiple-response set. For example, if the three car fields in the previous example are included in a multiple-response set named car_rankings, the following would return the same result:

max_index(@MULTI_RESPONSE_SET("car_rankings"))