[R-sig-ME] warnings when using binomial models and offset

Ben Bolker bbolker @ending from gm@il@com
Fri Nov 23 22:53:43 CET 2018


  This is a pretty common error, which I've now added to the GLMM FAQ.
You should be using log(density), not density, as your offset term; if
you use density, then you end up specifying that your capture counts are
proportional to exp(density), which is often a ridiculously huge number.

 cheers
   Ben Bolker

On 2018-11-23 12:26 p.m., Joana Martelo wrote:
> Hello everyone
> 
>  
> 
> I'm trying to model fish capture success using length, velocity and group
> composition as explanatory variables, density as an offset variable, and
> fish.id. as random effect. I'm getting the follow warnings:
> 
>  
> 
> Model1<-glmer(capture~length+offset(density)+(1|fish.id),family=binomial,dat
> a=cap)
> 
>  
> 
> Warning messages:
> 
> 1: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
> 
>   Model failed to converge with max|grad| = 0.260123 (tol = 0.001, component
> 1)
> 
> 2: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
> 
>   Model is nearly unidentifiable: very large eigenvalue
> 
> - Rescale variables?
> 
>  
> 
>  
> 
> -          I only get the warnings when I use length and group composition,
> not with velocity.
> 
> -          I don't get any warning if I don't use the offset.
> 
>  
> 
> I've tried:
> 
> Model1<-glmer(capture~length+offset(log(density))+(1|fish.id.c),family=binom
> ial(link="cloglog"),data=cap)
> 
>  
> 
> But still get the warning.
> 
>  
> 
> Any ideas of what might be the problem?
> 
>  
> 
> Many thanks!
> 
>  
> 
>  
> 
> Joana Martelo
> 
>  
> 
>  
> 
>  
> 
>  
> 
> Melhores cumprimentos,
> 
>  
> 
> Joana Martins
> 
>  
> 
>  
> 
>  
> 
> 
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> 
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