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 at r-project.org [mailto:r-sig-mixed-models-
bounces at r-project.org] On Behalf Of Asaf Weinstein
Sent: Sunday, November 11, 2012 11:08 PM
To: r-sig-mixed-models at 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]]

_______________________________________________
R-sig-mixed-models at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

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 at inbo.be
www.inbo.be

To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey


-----Oorspronkelijk bericht-----
Van: r-sig-mixed-models-bounces at r-project.org [mailto:r-sig-mixed-models-bounces at r-project.org] Namens Doran, Harold
Verzonden: maandag 12 november 2012 21:45
Aan: Asaf Weinstein; r-sig-mixed-models at 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 at r-project.org
[mailto:r-sig-mixed-models- bounces at r-project.org] On Behalf Of Asaf
Weinstein
Sent: Sunday, November 11, 2012 11:08 PM
To: r-sig-mixed-models at 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]]

_______________________________________________
R-sig-mixed-models at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

_______________________________________________
R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
* * * * * * * * * * * * * D I S C L A I M E R * * * * * * * * * * * * *
Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is door een geldig ondertekend document.
The views expressed in this message and any annex are purely those of the writer and may not be regarded as stating an official position of INBO, as long as the message is not confirmed by a duly signed document.