Re: how do I predict across regions and deal with aliasing and nesting in ASREML-R?

From: <arthur.gilmour_at_DPI.NSW.GOV.AU>
Date: Fri, 29 Feb 2008 09:44:45 +1100

Dear Scott.

Thanks Arthur. If someone could check my ASREML-R syntax below would
help.... I think it is ok after some 'testing' against raw means...
Taking your example (which is coded the same as my data), I assume that
you take G as random and do not declare Region in the model?

** You do not need to include Region as a main fixed factor in the model
because its degrees of freedom are incorparated in Experiment.
But you could. It would just partition the DF.

PREDICT G Reg !present Reg Exp will predict BLUPs for each G in each
In this model, do we need both Reg and Exp in the !present? Since they are
nested, I think that only Exp is needed?
You need both Reg and Exp in !PRESENT otherwise ASReml will not recognise
the nested structure
So PREDICT G Reg !present Exp
would generate a hypertable of Gen x Reg x Exp, predicting every cell in
the table (i.e. adding every Exp effect to every
Reg effect) and then averaging over all Expt for every region.
!Present means it just forms the cells in the hypertable which exist in
the data (i.e. just adds Exp effects to the Reg effects
to which they pertain) and then averages over those to get the Reg values.

May Jesus Christ be gracious to you in 2008,

Arthur Gilmour, His servant .
Mixed model regression mapping for QTL detection in experimental crosses.
Computational Statistics and Data Analysis 51:3749-3764 at

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Received on Mon Mar 01 2008 - 09:44:45 EST

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