Fellow ASREML users,
I have a data set for a RBD with 5 levels of lime as treatment and 4
blocks. When I analyse this using ANOVA or REML I get the same RMS
and Log Likelihood whether I consider the treatments as discrete or
continuous(ie use orthogonal polynomials( OPs))(as you'd expect)..
When I fit the model using ASREML, the RMS is 6% lower than that
from ANOVA or REML. LogL is reduced by 10% when treatment is fitted as
discrete levels, and increased by 1% when treatment is fitted as OP's.
I don't think I've made any programming mistakes.
Can anybody see the explanation for this?
Leigh Callinan