ProbitLogNormalRel-class: 'ProbitLogNormalRel'

In 0liver0815/onc-crmpack-test: Object-Oriented Implementation of CRM Designs

Description

ProbitLogNormalRel is the class for probit regression model with a bivariate normal prior on the intercept and log slope.

Usage

ProbitLogNormalRel(mean, cov, ref_dose = 0)

Arguments

mean	(numeric) the prior mean vector.
cov	(matrix) the prior covariance matrix.
ref_dose	(number) the reference dose.

Details

The covariate is the dose x divided by a reference dose x*, i.e.:

probit[p(x)] = alpha0 + alpha1 * x/x*,

where p(x) is the probability of observing a DLT for a given dose x. The prior

(alpha0, log(alpha1)) ~ Normal(mean, cov).

Note

This model is also used in the DualEndpoint classes, so this class can be used to check the prior assumptions on the dose-toxicity model, even when sampling from the prior distribution of the dual endpoint model is not possible.

See Also

ModelLogNormal, LogisticNormal, LogisticLogNormal, LogisticLogNormalSub, ProbitLogNormal.

Examples

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

0liver0815/onc-crmpack-test documentation built on Feb. 19, 2022, 12:25 a.m.