-----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
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