MVINCLUDE

Dear all,

I am curious about the use of the MVINCLUDE option in ASReml, especially
in univariate analyses, and would like to clarify when/why it can be
helpful.

My understanding is that it can be useful for multivariate analyses when
the design matrix has a missing value, in which case it is set to zero,
which can only work for covariates, which have previously been
mean-centered? Is that correct?

If applied to a simple model with one categorical fixed effect (e.g.
sex) and one random effect, such as x ~ mu sex !r animal, am I right to
assume that in the case of missing values for "sex" the MVREMOVE option
should be always avoided because it would then assign all missing sexes
as males, or all as females?

Thanks in advance for any answer,
Best,
Anne

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Dr Anne Charmantier
  CEFE-CNRS, UMR 5175
  1919, route de Mende
  F34293 Montpellier Cedex 5
  France

 Tel : +33 4 67 61 32 05
 Fax : +33 4 67 41 21 38
 Email : anne.charmantier_at_cefe.cnrs.fr
<mailto:arnaud.gregoire_at_cefe.cnrs.fr>
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