doseFunction: Getting the Dose Function for a Given Model Type

In Roche/crmPack: Object-Oriented Implementation of CRM Designs

Getting the Dose Function for a Given Model Type

Description

A function that returns a dose() method that computes the dose reaching a specific target value of a given independent variable, based on the model specific parameters.

Usage

doseFunction(model, ...)

## S4 method for signature 'GeneralModel'
doseFunction(model, ...)

## S4 method for signature 'ModelPseudo'
doseFunction(model, ...)

## S4 method for signature 'LogisticLogNormalOrdinal'
doseFunction(model, grade, ...)

Arguments

model	(GeneralModel or ModelPseudo) the model.
...	model specific parameters.
grade	(integer) the toxicity grade for which the dose function is required

Value

A dose() method that computes doses.

Functions

• doseFunction(GeneralModel):

• doseFunction(ModelPseudo):

• doseFunction(LogisticLogNormalOrdinal):

See Also

dose(), probFunction().

Examples

my_model <- LogisticLogNormal(
  mean = c(-0.85, 1),
  cov = matrix(c(1, -0.5, -0.5, 1), nrow = 2),
  ref_dose = 50
)

dose_fun <- doseFunction(my_model, alpha0 = 2, alpha1 = 3)
dose_fun(0.6)
data_ordinal <- .DefaultDataOrdinal()
model <- .DefaultLogisticLogNormalOrdinal()
options <- .DefaultMcmcOptions()
suppressWarnings({
  samples <- mcmc(data_ordinal, model, options)
})

doseFunction(model, alpha1 = samples@data$alpha2, beta = samples@data$beta, grade = 1L)(x = 0.75)
doseFunction(model, alpha2 = samples@data$alpha2, beta = samples@data$beta, grade = 2L)(x = 0.25)

Roche/crmPack documentation built on April 20, 2024, 1:10 p.m.