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Building CLEM Expressions
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, an d third
most important reasons for deciding on a particular purchase (for example, price, pers onal
recommendation, review, local supplier, other). In this case, you might determine t he importance
of price by deriving the index of the field in which it was first included:
first_index("price",[Reason1 Reason2 Reason3])
Similarly,suppos ey ou have asked customers to rank three cars in order of likelihood to purchase
and coded the responses in three 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 most (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 Chapter 8 on p. 135.
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 fie lds 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"))
The Expression Builder
Youcan 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 the current stream,
allowing you to quickly build expressions without memorizing the exact names of fields or