model
{
for (i in 1:m)
{
	# Poisson likelihood for observed counts
	y[i]~dpois(mu[i])
	ypred[i]~dpois(mu[i])
	mu[i]<-e[i]*theta[i]
	probexc[i]<-step(theta[i]-1)
	# Relative Risk
	theta[i]~dgamma(a,b)
	r[i]<-y[i]-mu[i]
	rpred[i]<-y[i]-ypred[i]
}

# Prior distributions for "population" parameters
a~dexp(10)
b~dexp(10)

# Population mean and population variance
mean<-a/b
var<-a/pow(b,2)
}