LogisticNormalMixture-class: 'LogisticNormalMixture'

In crmPack: Object-Oriented Implementation of Dose Escalation Designs

LogisticNormalMixture

Description

LogisticNormalMixture is the class for standard logistic regression model with a mixture of two bivariate normal priors on the intercept and slope parameters.

Usage

LogisticNormalMixture(comp1, comp2, weightpar, ref_dose)

.DefaultLogisticNormalMixture()

Arguments

comp1	(ModelParamsNormal) bivariate normal prior specification of the first component. See ModelParamsNormal for more details.
comp2	(ModelParamsNormal) bivariate normal prior specification of the second component. See ModelParamsNormal for more details.
weightpar	(numeric) the beta parameters for the weight of the first component. It must a be a named vector of length 2 with names a and b and with strictly positive values.
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, alpha1) ~ w * Normal(mean1, cov1) + (1 - w) * Normal(mean2, cov2).

The weight w for the first component is assigned a beta prior B(a, b).

Slots

comp1

(ModelParamsNormal)
bivariate normal prior specification of the first component.

comp2

(ModelParamsNormal)
bivariate normal prior specification of the second component.

weightpar

(numeric)
the beta parameters for the weight of the first component. It must a be a named vector of length 2 with names a and b and with strictly positive values.

ref_dose

(positive_number)
the reference dose.

Note

The weight of the two normal priors is a model parameter, hence it is a flexible mixture. This type of prior is often used with a mixture of a minimal informative and an informative component, in order to make the CRM more robust to data deviations from the informative component.

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

See Also

ModelParamsNormal, ModelLogNormal, LogisticNormalFixedMixture, LogisticLogNormalMixture.

Examples

my_model <- LogisticNormalMixture(
  comp1 = ModelParamsNormal(
    mean = c(-0.85, 1),
    cov = matrix(c(1, -0.5, -0.5, 1), nrow = 2)
  ),
  comp2 = ModelParamsNormal(
    mean = c(1, 1.5),
    cov = matrix(c(1.2, -0.45, -0.45, 0.6), nrow = 2)
  ),
  weightpar = c(a = 1, b = 1),
  ref_dose = 50
)

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