[R-sig-ME] Meta-analysis for heritability using MCMCglmm?

Ken Beath ken.beath at mq.edu.au
Wed Dec 24 02:30:03 CET 2014

If you have the original data giving the numerator and denominator for the
proportion then it is binomial data, and can be modelled in a met-analysis.
I don't know if this can be done with MCMCglmm but should be possible with
STAN, JAGS or BUGS. All will require a bit of effort in setting up the

On 24 December 2014 at 07:17, Jackie Wood <jackiewood7 at gmail.com> wrote:

> Dear R-users,
> I am attempting to conduct a meta-analysis to investigate the relationship
> of narrow-sense heritability with population size. In previous work, I have
> used MCMCglmm to conduct a formal meta-analysis which allowed me to account
> for the effect of sampling error through the argument "mev". This was
> relatively easy to do for a continuous response variable, however,
> heritability is presented as a proportion and is therefore bounded by 0 and
> 1 which clearly changes the situation.
> In fact, I am not actually certain if it possible to conduct a formal
> weighted meta-analysis on the heritability data using MCMCglmm. I have seen
> elsewhere where data presented as a proportion (survival, yolk-conversion
> efficiency for example) has been logit transformed and fitted using a
> Gaussian error distribution (though this was done using REML rather than
> Bayesian modelling) but I don't know if this is a legitimate strategy for a
> formal meta-analysis using heritability as a response variable since any
> transformation applied to the heritability data would also need to be
> applied to the standard errors?
> I would greatly appreciate any advice on this matter!
> Cheers,
> Jackie
> --
> Jacquelyn L.A. Wood, PhD.
> Biology Department
> Concordia University
> 7141 Sherbrooke St. West
> Montreal, QC
> H4B 1R6
> Phone: (514) 293-7255
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*Ken Beath*
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