I have a question about Bayesian p-value in WinBUGS.

I'm trying to fit a Bayesian Beta Regression according to Branscum et al. (2007). But I don't know what I must to do to obtain the bayesian p-value to validate the model. Suppose that

**y**is the response variable (with 0 <

**y**< 1) and

**x**is the independent variable. Then my code in WinBUGS is the following:

model{

for(i in 1:N){

y

*~ dbeta(a*

*, b**)*

aa

*<- mu*** phi*

bb

*<- (1 - mu**) * phi*

logit(mulogit(mu

*) <- Beta1 + Beta2 * x*

}

phi ~ dgamma(1, 1)

Beta1 ~ dnorm(0, 1)

Beta2 ~ dnorm(0, 1)

}

In advance, thanks a lot for your help!

Kind regards,

Rodrigo.}

phi ~ dgamma(1, 1)

Beta1 ~ dnorm(0, 1)

Beta2 ~ dnorm(0, 1)

}

In advance, thanks a lot for your help!

Kind regards,

Rodrigo.