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: t.c.cameron@leeds.ac.uk
Webpage: click here
<http://www.fbs.leeds.ac.uk/staff/profile.php?tag=Cameron_TC> 

 

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