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

[Thierry Onkelinx]

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
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium

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
>
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