That is what I get from the GLIMMIX code I posted as well. The standard errors of the by-genotype residual estimates are at least an order of magnitude greater than the point estimates and the chi-squared test for homogeneity is nonsignificant (pr>chisq = 0.2591). The F test for genotype is also non-significant (pr > F = 0.1851). My conclusion is that there is insufficient data to come to any frequentist conclusion about yield as a function of genotype.
So I tried a quick look at the same design, but using the Bayesian approach provided in PROC BGLIMM. the 95% HPD intervals for the means of the genotypes all overlapped, as did the variance 95% HPD intervals. Same conclusions - insufficient data to come to a conclusion about yield as a function of genotype. My code for this was:
proc bglimm data=yield plots=all seed=12321;
class genotype rep;
model yield = genotype/noint;
random intercept/subject=rep(genotype) group=genotype;
run;
No ESTIMATE statements were used to look at pairwise comparisons as the overlapping intervals covered the whole of possible comparisons. Also, no need for multiple comparison adjustment with this approach.
