biomLevel: Compute the biomarker level for a given dose, given model and...

Description Usage Arguments Methods (by class) Examples

Description

Compute the biomarker level for a given dose, given model and samples

Usage

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biomLevel(dose, model, samples, ...)

## S4 method for signature 'numeric,DualEndpoint,Samples'
biomLevel(dose, model, samples,
  xLevel, ...)

Arguments

dose

the dose

model

the DualEndpoint object

samples

the Samples object

...

unused

xLevel

the grid index of dose

Methods (by class)

Examples

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# Create the data
data <- DataDual(
  x=c(0.1, 0.5, 1.5, 3, 6, 10, 10, 10,
      20, 20, 20, 40, 40, 40, 50, 50, 50),
  y=c(0, 0, 0, 0, 0, 0, 1, 0,
      0, 1, 1, 0, 0, 1, 0, 1, 1),
  w=c(0.31, 0.42, 0.59, 0.45, 0.6, 0.7, 0.55, 0.6,
      0.52, 0.54, 0.56, 0.43, 0.41, 0.39, 0.34, 0.38, 0.21),
  doseGrid=c(0.1, 0.5, 1.5, 3, 6,
             seq(from=10, to=80, by=2)))

# Initialize the Dual-Endpoint model (in this case RW1)
model <- DualEndpointRW(mu = c(0, 1),
                        Sigma = matrix(c(1, 0, 0, 1), nrow=2),
                        sigma2betaW = 0.01,
                        sigma2W = c(a=0.1, b=0.1),
                        rho = c(a=1, b=1),
                        smooth = "RW1")

# Set-up some MCMC parameters and generate samples from the posterior
options <- McmcOptions(burnin=100,
                       step=2,
                       samples=500)
set.seed(94)
samples <- mcmc(data, model, options)

# Obtain the biomarker level for a given dose, given model and samples
biomLevel(dose = 0.5,
          model = model,
          samples = samples,
          xLevel = 2)

crmPack documentation built on June 13, 2019, 9:02 a.m.