Two basic procedures exist for producing factor scores in SAS: 1) a predefined SAS option and 2) a program-it-yourself option. As you might imagine, the predefined SAS option is by far the easier. When you include the OUT=output-data-set-name option on the FACTOR statement (SAS, 2015), SAS will automatically output a data set that contains all of your original data along with an estimate of weighted factor scores (e.g., Factor1, Factor2, etc.). SAS computes the factor scores as a linear combination of a standardized version of our variables (i.e., with a mean of 0 and a standard deviation of 1) and something called the standardized scoring coefficients.[3] The scoring coefficients are essentially the regression coefficients used in the computation of the factor scores. Note that these are different from the pattern matrix loadings, which are viewed as the regression coefficients for computing the communalities.[4] It is important that you specify the desired number of factors to extract and the extraction and rotation methods when using this method; if you do not, SAS will use the default options of extracting the minimum number of factors recommended by the proportion of variance and the minimum eigenvalue criteria (see Factor Extraction Criteria) and performing principal components analysis with no rotation. An example of the syntax to estimate factor scores, using this method for the engineering data, is presented below.

proc factor data = engdata  nfactors = 2  method = prinit  priors = SMC 
      rotate = OBLIMIN  out=factor_scores1;
   var EngProb: INTERESTeng: ;
run;

An example of the data set output by the above syntax is presented in Figure 9.1 Factor scores output by the OUT statement. Note the factor scores are always appended to the end of the data set.

The other way of estimating factor scores—the program-it-yourself way—is often more complex. You will need to write your own code, which might contain a number of procedures or DATA steps. Some options that might be useful for this are the SCORE and OUTSTAT=output-data-set-name options. Both options are added to the FACTOR step. The SCORE option will print the standardized scoring coefficients, and the OUTSTAT option will output a data set that contains the various results (e.g., pattern loadings, communalities, etc.) from the analysis. The standardized scoring coefficients are also included in this data set when the SCORE option is used in conjunction with the OUTSTAT option. This information can be useful in the various calculations of factor scores. A simple example of the syntax to estimate equally weighted improper factor scores (discussed in the next section) is presented below.

data factor_scores2;
   set engdata;
   Factor1=mean(of EngProbSolv:); *compute mean of all items in the 
      engineer problem solving scale;
   Factor2=mean(of INTERESTeng:); *compute mean of items in the 
      interest in engineering scale;
run;