[R-sig-ME] R-sig-mixed-models Digest, Vol 71, Issue 34

[Ben Bolker]

Alan Haynes <aghaynes at ...> writes:

> 
> I think that part of what Alain was getting at was that random effects
> require quite a few levels to calculate the variance, so RE such as age are
> generally not recommended - you get a bad estimate of the variance from 2
> points.
> 
> I think he's also suggesting that with only 170 data points, the likelihood
> of overfitting is quite high when you have so many variables in your
> models. If you made a factor with one level for each combination of your
> random effects, how many datapoints would fall into each category? Ive
> heard it suggested that fewer than 10 and you'll probably start running
> into difficulty...dont remember where from though I'm afraid...

  Frank Harrell's _Regression Modeling Strategies_ book has an extensive
discussion of "how much data is enough" -- not in the specific context
of mixed models, but very clear.

  Ben