warnings when using binomial models and offset (log(x))

Thanks for your help!

However, I still get the warnings when using offset(log(density)

Model1<-glmer(capture~length+offset(log(density+2))+(1|fish.id.c),family=binomial,data=cap)

Warning messages:
1: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
  Model failed to converge with max|grad| = 0.258231 (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?


Any suggestion?

Thanks
Joana



-----Mensagem original-----
De: Mollie Brooks [mailto:mollieebrooks at gmail.com] 
Enviada: segunda-feira, 26 de Novembro de 2018 12:36
Para: Joana Martelo
Cc: R SIG Mixed Models
Assunto: Re: [R-sig-ME] warnings when using binomial models and offset - NaNs

If you?re using the scale() function to standardize your density values, you could use the argument, center=FALSE, to avoid subtracting the mean and thus avoid negative densities. 

cheers,
Mollie

On 26Nov 2018, at 13:33, Joana Martelo <joanamartelo at gmail.com> wrote:

Thanks for your email!

Warnings' problem is solved, however, when I use log(density) or 
log(density+1) I got NaNs because density has negative numbers. 
Density is 2,4,6 which standardized gives -1.793073717, -0.450015136, 
0.893043446. So, log(-1.793073717+1)= NaN

Any suggestions?

Many thanks!
Joana


-----Mensagem original-----
De: R-sig-mixed-models 
[mailto:r-sig-mixed-models-bounces at r-project.org] Em nome de Ben 
Bolker
Enviada: sexta-feira, 23 de Novembro de 2018 21:54
Para: r-sig-mixed-models at r-project.org
Assunto: Re: [R-sig-ME] warnings when using binomial models and offset


 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=binom
i
al,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),famil
y
=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








	[[alternative HTML version deleted]]