Re: using !MVINCLUDE with missing random effects

Dear Craig,
(NB. Arthur is away at present)

I think in the first model you mean "SOME MISSING MUM VALUES AND !MVINCLUDE SPECIFIED" ?

If so, then I think I know where the problem is.

From the V3 user guide http://www.vsni.co.uk/downloads/asreml/release3/UserGuide.pdf , p113 (p139)
"Where the factor level is zero (or missing and the !MVINCLUDE qualifier is specified), no level is assigned to the factor for that record. These effectively defines an extra level (class) in the factor which becomes a reference level."

In your first model, using !mvinclude, ASReml effectively imputes one extra "mum" (class) for *all* the missing values.

In your second model, you have imputed your own unique dummy codes, a separate one for each missing value.

So the first model fits one additional level of mum, the second model fits m additional levels of mum (where m here is the number of missing values). I think this explains the difference between the two outputs.

Hope this helps,
Damian

Damian Collins, Biometrician, I&I NSW
damian.collins_at_industry.nsw.gov.au
ph: 02 4640 6451

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Received on Fri Jan 29 2010 - 09:10:13 EST