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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