General question about GLMM and heterogeneity of variance
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 Tricky Solutions 4 Tricky Problems Evidence Based Strategic Development, IP Commercialisation and Innovation, Data Analysis, Modelling and Training (mobile) 0410 689 945 (fax / office) chris at trickysolutions.com.au Disclaimer: The information in this email and any attachments to it are confidential and may contain legally privileged information. If you are not the named or intended recipient, please delete this communication and contact us immediately. Please note you are not authorised to copy, use or disclose this communication or any attachments without our consent. Although this email has been checked by anti-virus software, there is a risk that email messages may be corrupted or infected by viruses or other interferences. No responsibility is accepted for such interference. Unless expressly stated, the views of the writer are not those of the company. Tricky Solutions always does our best to provide accurate forecasts and analyses based on the data supplied, however it is possible that some important predictors were not included in the data sent to us. Information provided by us should not be solely relied upon when making decisions and clients should use their own judgement.
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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