ProbitLogNormal-class: 'ProbitLogNormal'

In crmPack: Object-Oriented Implementation of Dose Escalation Designs

ProbitLogNormal

Description

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

Usage

ProbitLogNormal(mean, cov, ref_dose = 1)

.DefaultProbitLogNormal()

Arguments

mean	(numeric) the prior mean vector.
cov	(matrix) the prior covariance matrix. The precision matrix prec is internally calculated as an inverse of cov.
ref_dose	(number) the reference dose x* (strictly positive number).

Details

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

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

The model used in the DualEndpoint classes is an extension of this model: DualEndpoint supports both ProbitNormal (which is not implemented yet) and ProbitLogNormal models through its use_log_dose slot. ProbitLogNormal has no such flag, so always uses ⁠log(x/x*)⁠as a covariate in its model. Therefore 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, when use_log_dose = TRUE is used.

Typically, end users will not use the .DefaultProbitLogNormal() function.

See Also

ModelLogNormal, LogisticNormal, LogisticLogNormal, LogisticLogNormalSub, ProbitLogNormalRel.

Examples

my_model <- ProbitLogNormal(
  mean = c(-0.85, 1),
  cov = matrix(c(1, -0.5, -0.5, 1), nrow = 2),
  ref_dose = 7.2
)

crmPack documentation built on Nov. 29, 2025, 5:07 p.m.