Hi !

You should give a look at the R package MCMCglmm for quantitative 
genetics on non normal traits. For survival, the following paper might 
be of interest :

Papaïx, J., Cubaynes, S., Buoro, M., Charmantier, A., Perret, P., and 
Gimenez, O. (2010). Combining capture-recapture data and pedigree 
information to assess heritability of demographic parameters in the 
wild. Journal of Evolutionary Biology /23/, 2176--2184.

Concerning your variance issue, glmer fixes the "residual" variance to 0 
(on the contrary to MCMCglmm for example, which uses 1). However, there 
is stil the "link" variance to take into account which is (pi^2)/3 for a 
logit link and 1 for a probit link, see the following paper :
Nakagawa, Shinichi, et Holger Schielzeth. « Repeatability for Gaussian 
and Non Gaussian Data: a Practical Guide for Biologists ». /Biological 
Reviews/ 85, n^o 4 (novembre 1, 2010): 935-956. 
doi:10.1111/j.1469-185X.2010.00141.x.

Hope this helps !

Pierre de Villemereuil.

Le 07/12/2012 12:40, Rudy Garel a écrit :
> Hi everybody,
>
> I am working on Atlantic salmon embryos and I wondered if anyone knows 
> how to compute heritabilities on binomial response variables like 
> survival?
> Here is the model that I use to extract the variance components on a 
> gaussian response variable (cf R book, p.640):
>
> lmer(Bodylength~1+(1|Fem)+(1|factor(Mal))+(1|Fem:factor(Mal))+(1|factor(Inc))) 
>
>
> ... where "Fem" is the female or mother effect, "Mal" the male or 
> father effect and "Inc" the incubator effect.
> And so I tried to extract the variance components on a binomial 
> response variable drawing inspiration of this model as follows:
>
> glmer(Survival~1+(1|Fem)+(1|factor(Mal))+(1|Fem:factor(Mal))+(1|factor(Inc)),family="binomial") 
>
>
> The problem with this last model is that it does not give me the 
> residual variance (which is normal with binomial data) and so I can 
> not compute heritability.
> Does anyone know an approach on R to compute heritabilities on 
> binomial response variables?
> Thanks in advance for paying attention to this mail.
>
> Cheers,
>
>
>
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