Background: I have a categorical variable, X, with four levels that I fit as separate dummy variables. Thus, there are three total dummy variables representing x=1, x=2, x=3 (x=0 is baseline).
Problem/issue: I want to be able to calculate the value of a linear combination (i.e. using SAS as a calculator) of these dummy variables. For example, 2*B1 + 2*B2 + B3.
In Stata, this can be done using the lincom
command, which uses the stored beta estimates to calculate linear combinations of the parameters.
In SAS in a procedure such as PROC GLM, I think I should use the ESTIMATE
statement, but I'm not sure how I would specify the "weights" for each variable in this case.
You are looking for PROC SCORE. This takes output regression or factor estimates and scores a new data set. See here for an example. http://support.sas.com/documentation/cdl/en/statug/66859/HTML/default/viewer.htm#statug_score_examples02.htm
FYI, PROC MODEL
does allow this in the model statement, which may be less work than PROC SCORE
. I know PROC MODEL
can be used readily in place of PROC REG
, but I'm not sure how advanced of modeling PROC MODEL
does, so it may not be an option for more complex models. I was hoping for something with less coding, but given the nature of SAS, I think this and PROC SCORE
are the best I'm going to get.
What if you add your linear combination as a variable in your input dataset?
data myDatasetWithLinCom;
set mydata;
LinComb=2*(x=1)+ 2*(x=2)+(x=3); /*equvilent to 2*B1 + 2*B2 + B3*/
run;
then you can specify LinComb as one of the explanatory variables and you can lookup the coefficient directly from the output.