The data set containing scoring coefficients must contain two special variables: the _TYPE_
variable and the _NAME_
or _MODEL_
variable.
The _TYPE_
variable identifies the observations that contain scoring coefficients.
The _NAME_
or _MODEL_
variable provides a SAS name for the new score variable.
PROC SCORE first looks for a _NAME_
variable in the SCORE= input data set. If there is such a variable, the variable’s value is what SCORE uses to name the new
score variable. If the SCORE= data set does not have a _NAME_
variable, then PROC SCORE looks for a _MODEL_
variable.
For example, PROC FACTOR produces an output data set that contains factor-scoring coefficients. In this output data set, the
scoring coefficients are identified by _TYPE_
=’SCORE’. For _TYPE_
=’SCORE’, the _NAME_
variable has values of ’Factor1’, ’Factor2’, and so forth. PROC SCORE gives the new score variables the names Factor1
, Factor2
, and so forth.
As another example, the REG procedure produces an output data set that contains parameter estimates. In this output data set,
the parameter estimates are identified by _TYPE_
=’PARMS’. The _MODEL_
variable contains the label used in the MODEL statement in PROC REG, or it uses MODELn if no label is specified. This label is the name PROC SCORE gives to the new score variable.