species richness, GLM and negative values
Ludovico Frate p??e 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.
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E-mail ludovico.frate at unimol.it
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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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