Ludovico Frate píše v St 29. 10. 2014 v 16:27 +0100:
> Dear all,I'am trying to fit a very simple linear model. I am analyzing the 
> differences in the number of species (DS) found in several permanent plots in 
> two year of observations.
>  Firstly, I have calculated the differences per plot (i.e. number of species 
> in Plot 1 in Time A - number of species in Plot 1 in Time B and so on for all 
> the plots).Secondly, those differences were tested for deviation from zero by 
> means of a linear model
> M2<-lm(DC~1, data = gransasso)summary(M2)E2<-residuals(M2)qqnorm(E2, pch = 
> 19, col = "blue"); qqline(E2, col = "red")
> The qqnorm has shown that residuals were not normally distributed, thus I 
> need to use a GLM. However GLM (poisson family) does not work with negative 
> values (DS has negative values).I've tried to add a constant value to these 
> differences (i.e. +100) but the result is misleading  since I am testing for 
> deviation from zero.
> Do you have any suggestions?
> Regards,Ludovico
> 
>                                                                               
>                                                
> Ludovico
> Frate
> 
> PhD student (University of Molise - Italy)
> Environmetrics Lab
> http://www.distat.unimol.it/STAT/environmetrica/organico/collaboratori/ludovico-frate-1
> Department of Biosciences and Territory - DiBT
> Universit del Molise.
> Contrada Fonte
> Lappone, 
> 86090 -  Pesche (IS)
> ITALIA.
> Cel: ++39
> 3333767557
> Fax: ++39 (0874) 404123
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Hi Ludovico,

correct me if I am wrong, but I think you want to say something like:
"In X out of Y plots, number of species did substantially (statistically
significantly?) changed".
For this, I would separate the plots where number of species is bigger
and those where opposite is true in the second census and perform
binomial test:
binom.test(x=abs(difference), n=more.species.i.e.bigger.of.the.numbers,
p=0.5) per each plot. Maybe you need better p (something like mean
probability of species to disappear,...)

HTH.
Martin






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