[R-sig-ME] FW: linear mixed model for non-normal negative and continous data

Simon Blomberg s.blomberg1 at uq.edu.au
Tue Apr 29 03:56:37 CEST 2014

You could try using the Yeo-Johnson transformation in the car package.



On 28/04/14 21:31, Caroline Lustenberger wrote:
> 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:
> mod_Knmn<-lmer(Knmn~Group*Timepoint+(1|VPnr),data=data)
> 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
> Caroline
> 	[[alternative HTML version deleted]]
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Simon Blomberg, BSc (Hons), PhD, MAppStat, AStat.
Senior Lecturer and Consultant Statistician
School of Biological Sciences
The University of Queensland
St. Lucia Queensland 4072
T: +61 7 3365 2506
email: S.Blomberg1_at_uq.edu.au

1.  I will NOT analyse your data for you.
2.  Your deadline is your problem.

Statistics is the grammar of science - Karl Pearson.

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