proc glm data=mydata;
model tq = year
a b c /solution noint;
Among others, SAS gives me the Rsquare for the regression, which is really high. That is, as far as I understand it, because of the fixed effects I am using here. How could I exclude the impact of my fixed effects on the Rsquare?
The usual test is to see if the enhanced model (with d in the equation) performs better than the first model (with only a b c in the equation) via the extra sum of squares principle (http://www.jerrydallal.com/LHSP/extra.htm).
Thank you so much for your answer (which is the answer to my question I mistakenly posted in the other forum, I think). Anyway, that really helped me, although as far as I understand, a log likelihood ratio test is the test to utilize for the logistic regression which can be done by hand with the output provided by SAS.