crmPack (version 2.0.0)

LogisticLogNormal-class: LogisticLogNormal

Description

LogisticLogNormal is the class for the usual logistic regression model with a bivariate normal prior on the intercept and log slope.

Usage

LogisticLogNormal(mean, cov, ref_dose = 1)
.DefaultLogisticLogNormal()

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 the dose \(x\) divided by the reference dose \(x*\), i.e.: $$logit[p(x)] = alpha0 + alpha1 * log(x/x*),$$ where \(p(x)\) is the probability of observing a DLT for a given dose \(x\). The prior $$(alpha0, log(alpha1)) ~ Normal(mean, cov).$$

See Also

ModelLogNormal, LogisticNormal, LogisticLogNormalSub, ProbitLogNormal, ProbitLogNormalRel, LogisticLogNormalMixture, DALogisticLogNormal.

Examples

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