Sorry about re-posting this, it never went out to the mailing list when I
posted this to r-help forum on Nabble and was pending for a few days, now
that I am subscribe to the mailing list I hope that this goes out:
I've been a viewer of this forum for a while and it has helped out a lot,
but this is my first time posting something.
I am running glm models for richness and abundances. For example, my beetle
richness is overdispersed:
> qcc.overdispersion.test(beetle.richness)
Overdispersion test Obs.Var/Theor.Var Statistic p-value
poisson data 2.628131 23.65318 0.0048847
So, I am running a simple glm with my distribution as quasipoisson
> glm.richness1<-glm(beetle.richness~log.area, family = quasipoisson)
Now I want to calculate a qAIC and qAICc. I was trying to modify the
equation that I found in Bolker et al 2009 supplemental material:
QAICc <- function(mod, scale, QAICc=TRUE){
LL <- logLik(mod)
ll <- as.numeric(LL)
df <- attr(LL, "df")
n <- length(mod$y) #used $ to replace @ to make a S3 object
if(QAICc)
qaic = as.numeric( -2*ll/scale + 2*df +
2*df*(df+1)/(n-df-1))
else qaic =as.numeric( -2*ll/scale + 2*df)
qaic
}
The only problem is that I have no idea how to scale it. In Bolker at al.
2009 it is scaled to "phi":
phi = lme4:::sigma(model)
But I am not running a mixed model and I cannot run the qAICc function
without scaling it. I am comparing models to each other trying to find the
best model for both landscape land use land cover data and patch variables.
How would I set the scale if I run this function?
QAICc(glm.richness1, scale = ?)
Should I set the scale to the square root of the deviance? phi =
sqrt(glm.richness1$deviance)
Your help is much appreciated.
Regards,
Jason
--
Jason M. Nelson
Master Candidate
Department of Zoology
Miami University
PSN 167F (Lab): 513.529.3391
PSN 149 (office)
Cell: 616.901.5923
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