[R-sig-ME] Random-effects model with known error variance

[ONKELINX, Thierry]

If you are prepared to do it the Bayesian way, then you can fix the variance of the random effect. Have a look at the MCMCglmm package.

Best regards,

ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
+ 32 2 525 02 51
+ 32 54 43 61 85
Thierry.Onkelinx op inbo.be
www.inbo.be

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-----Oorspronkelijk bericht-----
Van: r-sig-mixed-models-bounces op r-project.org [mailto:r-sig-mixed-models-bounces op r-project.org] Namens Doran, Harold
Verzonden: maandag 12 november 2012 21:45
Aan: Asaf Weinstein; r-sig-mixed-models op r-project.org
Onderwerp: Re: [R-sig-ME] Random-effects model with known error variance

Yes, lmer can handle unbalanced data. No, you cannot constrain one of the variances to have a fixed value using lmer. Solutions for linear mixed models are well-known, and so if your grasp of R programming and matrix algebra is decent, then it is very easy to do this.

> -----Original Message-----
> From: r-sig-mixed-models-bounces op r-project.org
> [mailto:r-sig-mixed-models- bounces op r-project.org] On Behalf Of Asaf
> Weinstein
> Sent: Sunday, November 11, 2012 11:08 PM
> To: r-sig-mixed-models op r-project.org
> Subject: [R-sig-ME] Random-effects model with known error variance
>
> Hi there,
>
> I am trying to fit a random effects two-way linear model with
> unbalanced data, and have two questions:
>
>    1. Can someone verify that lmer() can indeed cope with an unbalanced
>    table?
>    2. This might be more difficult: I am looking to fit the same model with
>    a KNOWN value for the error variance (sigma sq). I wonder if this is
>    possible to do with current package, and if not, if it's a good idea to
>    look into the implementation and try to do it myself. I'm curious to know
>    how difficult that would be to a not-too-sophisticated R user.
>
> Thanks so much,
>
> Asaf
>
>       [[alternative HTML version deleted]]
>
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> R-sig-mixed-models op r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

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