[R] linear mixed model for non-normal negative and continous data

ONKELINX, Thierry Thierry.ONKELINX at inbo.be
Mon Apr 28 13:19:01 CEST 2014

Dear Caroline,

Check the homogeneity of the variances. If they are inhomogeneous, you can add a variance function to deal with it. However, you will need to switch to the lme() from the nlme package.

Best regards,


PS R-Sig-mixed-models is a better list for this kind of questions.

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
+ 32 2 525 02 51
+ 32 54 43 61 85
Thierry.Onkelinx op inbo.be

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-----Oorspronkelijk bericht-----
Van: r-help-bounces op r-project.org [mailto:r-help-bounces op r-project.org] Namens Caroline Lustenberger
Verzonden: maandag 28 april 2014 12:04
Aan: r-help op r-project.org
Onderwerp: [R] linear mixed model for non-normal negative and continous data

Dear all

I try to fit a linear mixed model to my data. In short, my dependent variable reflects changes of the bone level (Knmn, in mm), thus this variable is continous and provides negative values. I have two different groups (factor Group) that were measured 3 times each (thus repeated measures, factor Timepoint). I used the following model:


When performing a qq-plot my residuals are clearly deviant from the norm (long-tailed). Due to negative values I cannot perform classical transformation methods (e.g. log transformation). How could I proccede with this data. Is there a possibility to use a generalized linear model?

Thanks and all the best


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