[R-sig-ME] Setting priors for binary fixed effects

[Pierre de Villemereuil]

Dear Yannis,

> I have a comparative phylogenetic model with a binary response variable, 5
> binary explanatory variables as fixed effects and the phylogeny as a random
> effect

Which family are you using? In my experience, the family "threshold" tend to yield the best results in terms of MCMC mixing in MCMCglmm.

>All the variables pass the Stationarity test but 2 of them fail the Halfwidth test.

The Halfwidth test is not a test of convergence. It tests whether the sampling was "large enough", but in my experience, it's not a very robust test and I tend to rely on effective sample size to evaluate whether the MCMC was long enough or not. So, if you do not see trends in your traceplots, I would say that convergence is not a problem here.

> Should I change them, due to the binary nature of my fixed effects? What's
> the best priors for binary fixed effects?

More informative priors for the fixed effect can help the mixing of the MCMC (at the cost of possible underestimation and issues with CI coverage if the priors are too informative), but as I said above, I'm unsure whether there is a problem here.

Hope this helps,
Pierre.

Le mardi 8 septembre 2020, 08:48:01 CEST Yannis Dim. a écrit :
> Dear everyone,
> 
> I have a comparative phylogenetic model with a binary response variable, 5
> binary explanatory variables as fixed effects and the phylogeny as a random
> effect. The issue I have is that with a nitt=300,000,000, I check the
> heidel.diag(mcmc.list(model$Sol)) and the plot(model) and  the model does
> not converge. All the variables pass the Stationarity test but 2 of them
> fail the Halfwidth test. The same 2 variables also have bad trace plots.
> I wonder if changing the priors will improve the convergence.Currently I
> use these priors:
> prior<-list(R=list(V=1, fix=1),G=list(G1=list(V=1, nu=1000, alpha.mu=0,
> alpha.V=1)))
> 
> As you can see, I am using the default priors for the fixed effects.
> 
> Should I change them, due to the binary nature of my fixed effects? What's
> the best priors for binary fixed effects?
> 
> I will be immensely grateful if someone could help, as this issue's been
> bothering me for some time now.
> 
> Kind regards,
> Yannis Dimopoulos
> PhD Student - The University of Hull
> 
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