model {
# Define likelihood model for data:
# Carbapenem resistance in hospital (gp, volunteer, and outpatient) samples
# is Bernoulli distributed with probability h.prob (gp.prob, v.prob,
# and o.prob)
for (p in 1:N_patients)
{
h_resist[p] ~ dbern(h.prob)
}
for (gp in 1:N_gp)
{
gp_resist[gp] ~ dbern(gp.prob)
}
for (v in 1:N_volunteers)
{
v_resist[v] ~ dbern(v.prob)
}
for (o in 1:N_outpatients)
{
o_resist[o] ~ dbern(o.prob)
}
# ------------------------
# Define the priors:
logit(h.prob) <- intercept
logit(o.prob) <- intercept
logit(gp.prob) <- intercept
logit(v.prob) <- intercept
# ------------------------
# Prior value for intercept
intercept ~ dnorm(0, tau)
# Prior values for precision
tau ~ dgamma(0.001, 0.001)
# Convert precisions to sd
sd <- sqrt(1/tau)
#monitor# full.pd, dic, deviance, h.prob, intercept, sd
}
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