User's Manual

117

Building CLEM Expressions

Working with Multiple-Response Data

A n umber of comparison functions can be used to analyze multiple-response da ta, 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 exa mple, suppose a multiple-response q uestion 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, y ou might determine the imp ortance

of price by derivi ng the index of the ﬁeld in which it was ﬁrs t included :

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

Similarl y, suppose you have asked customers to rank three cars in order of likelihood to purchase

and c oded the responses in thre e separate ﬁelds, as follows:

customer id

car1 car2 car3

101 1 3 2

102 3 2 1

103 2 3 1

In this case, you could determine the index of the ﬁeld for the car they like mo st (ranked #1, or

the lowest rank) using the min_index function:

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

For more information, see the topic Comparison Functions in C hapter 8 on p. 135.

Referencing Multiple-Response Sets

The special @MULTI_RESPONSE_SET function can be used to refe r ence all of the ﬁelds in a

multiple-response set. For example , if the three car ﬁelds in the previous example are included in

a m ultiple-r esponse set named car_rankings, the following would return the same result:

max_index(@MULTI_RESPONSE_SET("car_rankings"))

The Expression Builder

You can type CLEM expressions manually or use the Expression Builder, which displays a

complete list of CLEM functions and operators as well as data ﬁelds from th e current stream,

allowing you to quick ly build expressions without memorizing the exact names of ﬁelds or