


Hello all,


I am trying to investigate whether there are any trends in
the visit rate of rabbits across 40 farms to the farms’ building types over a
year. For example, if they are visiting the feed store more in the spring than
in summer. As it is a mixed effects model I have been trying to use a GLMER and
loading the package lme4.


The model structure so far is:

> r1<-glmer(rabbitvisit~month+buildingtype+(1|farm),family=binomial)


However, I when I run the model I get this message:

Warning message: glm.fit: algorithm did not converge


I also wish to nest “date” as a random effect within farm to
account for pseudoreplication but am not entirely sure how to proceed without understanding this
warning message. 



I have checked that rabbitvisit (presence/absence data) is
read in as a factor and checked the raw data for any obvious errors.


I tried to see if I could get the model to work with just
month as a fixed effect and got a different warning message:

>
r3<-glmer(rabbitvisit~month+(1|farm),family=binomial)

Warning message:

In mer_finalize(ans) : false convergence (8) 



Any advice would be very gratefully received!  

Sophie Ledger


 		 	   		  
	[[alternative HTML version deleted]]


