[R-sig-ME] question about an unbalanced design using lmer

Thierry Onkelinx thierry.onkelinx at inbo.be
Mon Oct 17 11:09:45 CEST 2016

Dear Xiyue,

Don't think in terms of cells but in terms of observations. The model tries
to minimise the residuals. So combinations with more observations have more
residuals and thus a stronger impact on the MSE.

Best regards,

ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht

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

2016-10-12 19:48 GMT+02:00 Xiyue Liao <liaoxiyue2011 op gmail.com>:

> Hi,
> I'm using lmer in the R package lme4 to do a one-way anova analysis with a
> fixed effect term and a random effect term. So the fixed effect is about
> four medical conditions and the random effect is about randomly sampled
> donors. Now for some combinations of donors and medical conditions, there
> are more than one measurement, which makes the whole design unbalanced. I
> think that lmer can handle such a case, and I have run the code without any
> error message. However, I don't understand how this routine put weight on
> the cells with more measurements than other cells. Could you give me some
> hint?
> Thanks in advance for your help.
> Sincerely,
> Xiyue
>         [[alternative HTML version deleted]]
> _______________________________________________
> R-sig-mixed-models op r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

	[[alternative HTML version deleted]]

More information about the R-sig-mixed-models mailing list