Dear R users
I have built the following model
m1<-lmer(y~harn+foodn+(1|ass%in%pop%in%fam),family = "quasibinomial")
where y<-cbind(alive,dead)
where harn and foodn are categorical factors and the random effect is a
nested term to represent experimental structure
e.g. Day/Block/Replicate
ass= 5 level factor, pop= 2 populations per treatment factor in each
assay, 7 reps per population
The model can be family = quasibinomial or binomial
My complete lack of understanding is in retrieving the coefficients for
the fixed effects to back-transform the effects of my factors on
proportional survival
I get the following output:
> coef(m1)
$`ass %in% pop %in% fam`
(Intercept) harn1 harn2 foodn2
FALSE 1.0322375 -0.1939521 0.0310434 0.810084
TRUE 0.5997679 -0.1939521 0.0310434 0.810084
Where FALSE and TRUE refer to some attribute of the random effect
My hunch is that it refers to the Coefficients with (=TRUE) and without
(=FALSE) the random effects?
Any help appreciated
........................................................................
............
Dr Tom C Cameron
Genetics, Ecology and Evolution
IICB, University of Leeds
Leeds, UK
Office: +44 (0)113 343 2837
Lab: +44 (0)113 343 2854
Fax: +44 (0)113 343 2835
Email: [EMAIL PROTECTED]
Webpage: click here
<http://www.fbs.leeds.ac.uk/staff/profile.php?tag=Cameron_TC>
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