crmPack (version 2.0.0)

LogisticLogNormalGrouped-class: LogisticLogNormalGrouped

Description

LogisticLogNormalGrouped is the class for a logistic regression model for both the mono and the combo arms of the simultaneous dose escalation design.

Usage

LogisticLogNormalGrouped(mean, cov, ref_dose = 1)
.DefaultLogisticLogNormalGrouped()

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 continuous covariate is the natural logarithm of the dose \(x\) divided by the reference dose \(x*\) as in LogisticLogNormal. In addition, \(I_c\) is a binary indicator covariate which is 1 for the combo arm and 0 for the mono arm. The model is then defined as: $$logit[p(x)] = (alpha0 + I_c * delta0) + (alpha1 + I_c * delta1) * log(x / x*),$$ where \(p(x)\) is the probability of observing a DLT for a given dose \(x\), and delta0 and delta1 are the differences in the combo arm compared to the mono intercept and slope parameters alpha0 and alpha1. The prior is defined as $$(alpha0, log(delta0), log(alpha1), log(delta1)) ~ Normal(mean, cov).$$

See Also

ModelLogNormal, LogisticLogNormal.

Examples

my_model <- LogisticLogNormalGrouped(
  mean = c(-0.85, 0, 1, 0),
  cov = diag(1, 4),
  ref_dose = 50
)
my_model