[R-sig-ME] General question about GLMM and heterogeneity of variance

[Chris Howden]

How bad is it? And do u have equal sample size in each cat group?

I ask because if the sample sizes are very different it may look like
the larger sample sizes have greater variance but this is only because
they have more sample and it's therefore more likely u will see
extreme values.

Chris Howden
Founding Partner
Tricky Solutions
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On 02/03/2012, at 1:45, RH Gibson <Rachel.Gibson at bristol.ac.uk> wrote:

> GibsonR <rachel.gibson <at> bristol.ac.uk> writes:
>
>>
>> My data have heterogeneity of variance (in a categorical variable), do I
> need
>> to specify a variance structure accounting for this in my model or do GLMMs
>> by their nature account for such heterogeneity (as a result of using
>> deviances rather than variances)? And if I do need to do this, how do I do
>> it (e.g. using something like the VarIdent function in nlme) and in what
>> package?
>
>
> Added 29.02.2012
>
>
> Sorry, I was not particularly clear.
>
> I ran my data through a GLM (the response variable is a proportion, and I
> ignored the random effects for the purposes of data exploration), and
> plotted the residuals against each of my predictor variables (some of
> which are continuous, some categorical). The heterogeneity showed up in
> the residuals of the response variable plotted against a categorical
> predictor variable (Insect functional group).
>
> Do I need to use something other than the GLMM in this case?
>
> Thank you very much for your help.
>
> --
>
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