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| The GLMSELECT Procedure |
| SCORE Statement |
- SCORE <DATA=SAS-data-set> <OUT=SAS-data-set> <keyword <=name> > ...<keyword <=name> > ;
The SCORE statement creates a new SAS data set containing predicted values and optionally residuals for data in a new data set that you name. If you do not specify a DATA= data set, then the input data are scored. If you have multiple data sets to predict, you can specify multiple SCORE statements. If you want to create a permanent SAS data set, you must specify a two-level name (for example, libref.data-set-name) in the OUT= option. For more information on permanent SAS data sets, refer to the section "SAS Files" in SAS Language Reference: Concepts.
When a BY statement is used, the score data set must either contain all the BY variables sorted in the order of the BY variables or contain none of the BY variables. If the score data set contains all of the BY variables, then the model selected for a given BY group is used to score just the matching observations in the score data set. If the score data set contains none of the BY variables, then the entire score data set is scored for each BY group.
All observations in the score data set are retained in the output data set. However, only those observations that contain nonmissing values for all the continuous regressors in the selected model and whose levels of the class variables appearing in effects of the selected model are represented in the corresponding class variable in the procedure’s input data set are scored. All the variables in the input data set are included in the output data set, along with variables containing predicted values and optionally residuals.
Details on the specifications in the SCORE statement follow:
- DATA=SAS data set
names the data set to be scored. If you omit this option, then the input data set named in the DATA= option in the PROC GLMSELECT statement is scored.
- keyword <=name>
specifies the statistics to include in the output data set and optionally names the new variables that contain the statistics. Specify a keyword for each desired statistic (see the following list of keywords), followed optionally by an equal sign, and a variable to contain the statistic.
If you specify keyword=name, the new variable that contains the requested statistic has the specified name. If you omit the optional =name after a keyword, then the new variable name is formed by using a prefix of one or more characters that identify the statistic, followed by an underscore (_), followed by the dependent variable name.
The keywords allowed and the statistics they represent are as follows:
- OUT=SAS data set
gives the name of the new output data set. By default, the procedure uses the DATAn convention to name the new data set.
PREDICTED. The prefix for the default name is r. |
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