Thank you very much, Ben, for your useful answer from long ago.
I still can't figure out a way to extract the Residual variance (sigma^2)
estimate using getME()?

Thanks again,
Asaf


On 15 November 2012 23:04, Ben Bolker <bbolker@gmail.com> wrote:

> Asaf Weinstein <asafw.at.wharton@...> writes:
>
> >
> > Hello again,
> >
> > Is there an easy way of obtaining the X and Z model matrices in
> >
> > *y = X*Beta + Z*u + eps*
> >
> > with the lmer function? I am trying to extract these because I want to
> > obtain maximum likelihood estimates for the case where sigma sq (error
> > variance) is known.
>
>
> See
>
> ?getME
>
> As shown in the examples:
>
>    (nmME <- eval(formals(getME)$name))
>  [1] "X"       "Z"       "Zt"      "u"       "Gp"      "L"       "Lambda"
>  [8] "Lambdat" "A"       "flist"   "RX"      "RZX"     "beta"    "theta"
> [15] "REML"    "n_rtrms" "is_REML"
>
>
> so getME(model,"X") and getME(model,"Z") should do what you want.
>
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