Hello,

I am using MCMCglmm to model a time to event outcome where individuals can
be either left or right censored so I am using the "cengaussian" family. I
have successfully run the model

test <- MCMCglmm(cbind(low, up) ~ g0 + age0,
         family="cengaussian", data=sex, tune=NULL,
         prior = list(R = list(V=1, n=0.002),
                      B = list(mu=rep(0,3), V=diag(3))))

Looking at the form of the density function from the MCMC Overview
documentation, I don't see liabilities. Combine that with having no random
effects, leads me to think that the program would use Gibbs sampling.

However, when I add a "pl=TRUE" to the above code, I get a posterior
distribution of liabilities, and the program displays the acceptance ratio
for latent scores (this is displayed regardless of the value of pl). Both
seem to indicate that MH sampling is being used.

So my questions are
1) Where are the liabilities being used in the density?
2) Does the display of the acceptance ratio for latent scores definitively
mean that MH sampling is being used?
3) If MH is being used, how can I extract the covariance matrix for the
proposal distribution that was used?


Thank you,
-Robin


Robin Jeffries
MS, DrPH Candidate
Department of Biostatistics,
UCLA

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