[R-sig-ME] MCMCglmm parameter expansion prior for binary model?
Jose Valdebenito Chavez
jov23 @end|ng |rom b@th@@c@uk
Sat Apr 20 14:53:21 CEST 2019
Hello all,
I am having troubles with the convergence of a binary model using MCMCglmm.
It�s a relatively simple model but it only has binary variables (0,1):
The response variable "camply_1" represents presence or absence of bacteria in several individuals.
�wmi_campy_1� is whether the couple of this individual was infected or not.
�quality� is either the individual was came from place A or B, and �sex� is the sex of the individual.
mc1 <- MCMCglmm(campy_1 ~ wmi_campy_1 + quality + sex,
random = ~id + population,
prior=prior.ex,
family = "categorical",
data = mated,
nitt=1000000,burnin=1000,thin=500)
I struggled a bit to set the priors for the model, actually I tried several online but they did not work for me. However after fiddling with other examples (like this one: https://stat.ethz.ch/pipermail/r-sig-mixed-models/2017q4/026115.html) and reading Hadfield Course notes I ended up with this:
prior.ex<- list(G = list(
G1 = list(V = 1, nu = 1000, alpha.mu = 0, alpha.V = 1),
G2 = list(V = 1, nu = 1000, alpha.mu = 0, alpha.V = 1)),
R = list(V=1, fix = TRUE))
When I run my previous models with this prior it gave me very good results. But then when I run this model (�mc1�), which was basically very similar, the diagnostic plots showed that the variable �wmi_campy_1� was not converging properly. Also in the outcome I could see the posterior going wrong.
post.mean l-95% CI u-95% CI eff.samp pMCMC
(Intercept) -2.5012 -4.7919 -0.2275 1502.426 0.028 *
wmi_campy_1 -200.9957 -410.5838 -1.0065 3.155 0.001 **
qualityisland -3.9733 -8.2205 -0.4725 1770.965 0.024 *
sexM 0.4699 -1.4708 2.2580 1830.226 0.604
I think this can be solved modifying the parameter expansion (alpha.mu, alpha.V) of the prior but I am out of ideas at this point. Any recommendations?
Many thanks.
Jose
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