Looking at this output, i notice a line for total, one for the one-way factor and one for the error. The total variance is that obtained from a null model (no effects). The error variance is the residual error after fitting the model, and the attributed variance component for the one-way factor is the difference between those two. Now comes the tricky part to think about, and it comes from the usual definition of variance component - the variance that is attributable to some random effect. Now if you assume that SERINDEX is a random effect (and thus that this is a simplified nested model), then that value in the R output is then a random variance component.
But in PROC ANOVA, SERINDEX would be fit as a fixed, non-nested effect. Perhaps PROC NESTED would give you what you want. Without the dataset it is hard to tell.
SteveDenham
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