MCMCglmm and prior specification

Dear all,

I am trying to use the MCMCglmm package to create credibility intervals 
for random variables in my data. I'm having a bit of trouble though 
determining what the best prior to use for each model is, since the 
results seem to differ tremendously depending on which prior I am 
using, for instance, I've tried these three types of priors,

halfFam<-var(data$Family)/2
prior1=list(R=list(V=1,n=1,fix=1),G=list(G1=list(V=1,n=1),G2=list(V=1,n=1)))
prior2=list(R=list(V=1,n=1),G=list(G1=list(V=1,n=1),G2=list(V=1,n=1)))
prior3=list(R=list(V=halfFam,n=1),G=list(G1=list(V=halfFam,n=1),G2=list(V=halfFam,n=1)))

For the model,

model<-MCMCglmm(Length~1,random=~Family+Rep,data=data,verbose=FALSE,prior=prior,burnin=10000,nitt=75000)

Where the random factors are Family and Replicate.
 From these priors, I get intervals for my Family effect,

HPDinterval(model1$VCV[,"Family"])

lower     upper
var1 0.09660338 0.8888039

HPDinterval(model2$VCV[,"Family"])

lower    upper
var1 0.1944570 2.120540

HPDinterval(model3$VCV[,"Family"])

lower    upper
var1 0.2099238 1.529794


I feel bad that I don't understand better how to specify the components 
of these priors, but from what I understand, the model should return 
similar values even if the priors are very different. I've looked 
through the vignette thoroughly, but didn't get a sense of what I was 
supposed to do if alternate priors returned different answers. I'm not 
sure whether this is telling me that all the information is coming from 
my priors (and there is, in fact, no information in the data), or I am 
just incorrectly specifying my priors.

Any insight would be very much appreciated! Happy holidays,

Cristina Ledon-Rettig
UNC-Chapel Hill

*I am using lme4 version 0.99375-28 with Mac OS X version 10.5