Dear ROdney,
I don't understand all your question.
>
> When running a mixed model analysis for the combined analysis of MET with
> the variables year, district, and year ( district as fixed with constraints
> to zero
> and varieties, varieties ( district, varieties ( year, and varieties (
> district ( year as random is this the proper model to use?
>
> X !WT=T~mu c(Year) c(District) District.Year !r Variety District.Variety
> District.Year Variety.District.Year !f mv
>
This is a reasonable model although I would normally include 'Trial'
as a fixed effect (which may equate in your case to Year.District
if there is only one trial in each district in a given year.)
This model is based on equal variances across trials and years
which for some crops is not common. Wheat can easily generate
a 10 fold difference in means and 100 fold difference in variances.
Therefore, I would be looking at fitting more sophisticated variance
structurtes.
> I did run a similar analysis using c(Year)*c(District), but for some reason
> dumped the error in the Blup-se for the last year. Is there an explanation
> for this?
I have no idea what this means. You should bet the same variance
components and residual degrees of freedom. The only difference should be
the fixed effects because they are parameterised differently. If there
are holes in the Year.District table, especially in the 'last' Year or District,
singularities will make the solutons for c(Year), c(District) and
c(Year).c(District) almost uninterpretable. The unconstrained
terms are preferred in this situation.
Arthur
>
>
> Rodney
>
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Arthur Gilmour PhD mailto:Arthur.Gilmour@agric.nsw.gov.au
Principal Research Scientist (Biometrics) fax: <61> 2 6391 3899
NSW Agriculture <61> 2 6391 3922
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