Functions handling blanks and null values (SPSS Modeler)
Using CLEM, you can specify that certain values in a field are to be regarded as
"blanks," or missing values.
The following functions work with blanks.
Table 1. CLEM blank and null value
functions
Function
Result
Description
@BLANK(FIELD)
Boolean
Returns true for all records whose values are blank according to the blank-handling rules set
in an upstream Type node or Import node (Types tab).
@LAST_NON_BLANK(FIELD)
Any
Returns the last value for FIELD that was not blank, as defined in an upstream Import
or Type node. If there are no nonblank values for FIELD in the records read so far,
$null$ is returned. Note that blank values, also called user-missing values, can be
defined separately for each field.
@NULL(FIELD)
Boolean
Returns true if the value of FIELD is the system-missing $null$.
Returns false for all other values, including user-defined blanks. If you want to check for both,
use @BLANK(FIELD) and@NULL(FIELD).
undef
Any
Used generally in CLEM to enter a $null$ value—for example, to fill blank
values with nulls in the Filler node.
Blank fields may be "filled in" with the Filler node. In both Filler and
Derive nodes (multiple mode only), the special CLEM function @FIELD refers to the
current field(s) being examined.
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