hello,
krebs (1995) states MH as prob., but yes it's rather a ratio of probs.
at each site i had 4 blocks with 2 treatments (treat vs. control) - after
treating i looked for similarity between each of those pairs.
it is of interest if changes in similarity due to treatment differ between
Sorry for this late answer (I've had a seriously nonmaskable interrupt).
Since I have technical questions not related to R, I take the liberty to
follow this up by e-mail.
I might post a followup summary if another R problem arises...
Emmanuel
hello,
it's the Morisita Horn Index, which is an ecological index for similarity
between two multivariate objects (vegetation samples with species and its
abundance) where a value of one indicates completely same relative
importance of species in both samples and 0 denotes total absence of any
hi emmanuel,
thanks a lot for your extensive answer.
do you think using the asin(sqrt()) transf. can be justified for publishing
prurpose or do i have to expect criticism.
naivly i excluded that possibility, because of violated anova-assumptions,
but if i did get you right the finite range
Le lundi 19 avril 2010 à 03:00 -0800, Kay Cichini a écrit :
hi emmanuel,
thanks a lot for your extensive answer.
do you think using the asin(sqrt()) transf. can be justified for publishing
prurpose or do i have to expect criticism.
Hmmm ... depends of your reviewers. But if an half-asleep
Le vendredi 16 avril 2010 à 00:15 -0800, Kay Cichini a écrit :
thanks thierry,
i considered this transformations already, but variance is not stabilized
and/or normality is neither achieved.
i guess i'll have to look out for non-parametrics?
Or (maybe) a model based on a non-Gaussian
Addendum to my previous answer :
In that special case, the limited range of the asin(sqrt())
transformation, which is a shortcoming, turns out to be useful. The
fixed-effect doefficients seem semi-reasonable (except for stageB) :
(sin(coef(lm(asin(sqrt(MH.Index))~0+stage, data=similarity^2
thanks thierry,
i considered this transformations already, but variance is not stabilized
and/or normality is neither achieved.
i guess i'll have to look out for non-parametrics?
best regards,
kay
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thank you thomas for the helpful hint!
yours,
kay
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[mailto:r-help-boun...@r-project.org] Namens Kay Cichini
Verzonden: maandag 12 april 2010 16:12
Aan: r-help@r-project.org
Onderwerp: [R] glmer with non integer
thanks thierry,
my problem is that the index is a propability which is not derived from
incidents per nr. of observations, thus i don't have those numbers but only
the plain index, which i want to test.
greatings,
kay
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: dinsdag 13 april 2010 13:37
Aan: r-help@r-project.org
Onderwerp: Re: [R] glmer with non integer weights
thanks thierry,
my problem is that the index is a propability which is not
derived from incidents per nr. of observations, thus i don't
have those numbers but only the plain index, which i
On Tue, 13 Apr 2010, ONKELINX, Thierry wrote:
So your respons variable behaves like a continuous variable except that
is range is limited to the 0-1 interval. In such a case I would
transform the respons variable (e.g. logit, sqrt(arcsin())) and use a
gaussian model.
A logit-Normal has
hello,
i'd appreciate help with my glmer.
i have a dependent which is an index (MH.index) ranging from 0-1. this index
can also be considered as a propability. as i have a fixed factor (stage)
and a nested random factor (site) i tried to model with glmer. i read that
it's possible to use a
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