proc glm data=mydata;
absorb isin;
class year;
model tq = year
a b c /solution noint;
run;quit;
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.
ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.