[R-sig-ME] comparing treatment with different skewness

[ONKELINX, Thierry]

Dear Maarten,

The assumption of normality does not apply to the response (y) but to the residuals of the model. 
Some more information on what y is (maybe counts?) and the design might help us to formulate a better solution for your problem.

Best regards,

Thierry

----------------------------------------------------------------------------
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek
team Biometrie & Kwaliteitszorg
Gaverstraat 4
9500 Geraardsbergen
Belgium

Research Institute for Nature and Forest
team Biometrics & Quality Assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium

tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be
www.inbo.be

To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey
  

> -----Oorspronkelijk bericht-----
> Van: r-sig-mixed-models-bounces at r-project.org 
> [mailto:r-sig-mixed-models-bounces at r-project.org] Namens 
> Maarten de Groot
> Verzonden: vrijdag 4 maart 2011 10:35
> Aan: Nicholas Lewin-Koh
> CC: r-sig-mixed-models at r-project.org
> Onderwerp: Re: [R-sig-ME] comparing treatment with different skewness
> 
> Hi Nicholas and list,
> 
> Sorry to be so short in explanation about my problem. I am 
> working on the effect of five different acoustic signals 
> (=treatments) on the response of one insect species. The 
> animals I used I presented with the signals on different 
> days. When I plotted the response variable y with the 
> treatments I realized that within the treatments y was not 
> normally distributed, and even worse y was not distributed 
> equally for every treatment. With other words, for treatment 
> 1 the response variable was more skewed to the lower region 
> of the boxplot and in treatment 2 to the higher region, etc.
> I tried to incorporate the variance into the model as 
> suggested by Nicholas:
> 
> mod1<-lme(y~treatment,
> weights=varPower(form=~1|treatment),random=~1|animal,data=mydata)
> 
> However this did not work. There is one question I have. 
> Nicholas, you are talking about "group" and I do not really 
> understand what you mean with this.
> 
> Hopefully this gives you a better insight and will help me to 
> solve the problem.
> 
> Kind regards,
> 
> Maarten
> 
> On 3/3/2011 10:40 PM, Nicholas Lewin-Koh wrote:
> > Hi Maarten,
> > Without the random effects, you are basically asking can you fit a 
> > model where the variance is a function of the group.
> > So I would think you could do this using nlme, ie somehthing like
> > library(nlme)
> > lme(y~T + X1, data=mydat,
> > weights=varPower(form=~1|group),random=~1|whatever)
> >
> > However, without more information it is hard to say more than that.
> >
> > Nicholas
> >
> >
> >> Message: 2
> >> Date: Thu, 3 Mar 2011 11:11:51 +0100
> >> From: Maarten de Groot<Maarten.deGroot at nib.si> 
> >> To:<r-sig-mixed-models at r-project.org>
> >> Subject: [R-sig-ME] comparing treatment with different skewness 
> >> Message-ID:<4D6F6967.8010303 at nib.si>
> >> Content-Type: text/plain; charset="ISO-8859-1"; format=flowed
> >>
> >> Dear list,
> >>
> >> I have a problem regarding choosing the distribution family for a 
> >> mixed model. I want to compare my response variable y with 
> treatment 
> >> A,B,C and D. In each of the treatments the distribution of y is 
> >> differently. Is there a way to implement this in a mixed model?
> >>
> >> Kind regards,
> >>
> >> Maarten
> >>
> >>
> >>
> > .
> >
> 
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