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Variance structure in mixed models

Dear all,

I modelled my data with a quasi-poisson error distribution using glm: glm(response~variable1 + factor1 , family=quasipoisson). Looking at the plot of residuals vs 
factor 1, I noticed a large heterogeneity in residual variance between the different levels of my factor. With a linear regression, there is the option of using a 
different variance structure for different levels using the option "varIdent" (funtion gls, package nlme). I could not find any equivalent for mixed models. Could 
anybody explain me why and if there is another possibilty to account for variance heterogeneity?

Thank you very much 
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