bmd.plot {CoMiRe}

Benchmark dose plot

Description

Posterior mean (continuous lines) and pointwise credible bands (shaded areas) for the benchmark dose in function of the increase in risk.

Usage

bmd.plot(bmd.data)

Arguments

bmd.data

output of BMD function.

Author(s)

Antonio Canale

Examples

{
data(CPP)
attach(CPP)

n <- NROW(CPP)
J <- H <- 10

premature <- as.numeric(gestage<=37)

mcmc <- list(nrep=5000, nb=2000, thin=5, ndisplay=4)

## too few iterations to be meaningful. see below for safer and more comprehensive results

mcmc <- list(nrep=10, nb=2, thin=1, ndisplay=4) 

prior <- list(mu.theta=mean(gestage), k.theta=10, eta=rep(1, J)/J, 
              alpha=rep(1,H)/H, a=2, b=2, J=J, H=H)
              
fit.dummy <- comire.gibbs(gestage, dde, family="continuous", 
                     mcmc=mcmc, prior=prior, seed=1, max.x=180)
                     
risk.data <- add.risk(y = gestage, x = dde, fit = fit.dummy, mcmc = mcmc, 
    a = 37, x.grid = seq(0, max(dde), length = 100))
bmd.data <- BMD(seq(0,.20, length=50), risk.data$mcmc.risk, 
x=seq(0,max(dde), length=100), alpha=0.05)
bmd.plot(bmd.data)       


## safer procedure with more iterations (it may take some time)

mcmc <- list(nrep=5000, nb=2000, thin=5, ndisplay=4)

## Fit the model for continuous y 

prior <- list(mu.theta=mean(gestage), k.theta=10, eta=rep(1, J)/J, 
              alpha=rep(1,H)/H, a=2, b=2, J=J, H=H)
              
fit <- comire.gibbs(gestage, dde, family="continuous", 
                     mcmc=mcmc, prior=prior, seed=5, max.x=180)
                     
risk.data <- add.risk(y = gestage, x = dde, fit = fit, mcmc = mcmc, 
a = 37, x.grid = seq(0, max(dde), length = 100))
bmd.data <- BMD(seq(0,.20, length=50), risk.data$mcmc.risk, 
x=seq(0,max(dde), length=100), alpha=0.05)
bmd.plot(bmd.data)       


}