LogisticLogNormalSub-class: Standard logistic model with bivariate (log) normal prior...

In crmPack: Object-Oriented Implementation of CRM Designs

Standard logistic model with bivariate (log) normal prior with substractive dose standardization

Description

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

Details

The covariate is the dose x minus the reference dose x^{*}:

logit[p(x)] = \alpha + \beta \cdot (x - x^{*})

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

The prior is

(\alpha, \log(\beta)) \sim Normal(\mu, \Sigma)

The slots of this class contain the mean vector and the covariance matrix of the bivariate normal distribution, as well as the reference dose.

Slots

mean

the prior mean vector \mu

cov

the prior covariance matrix \Sigma

refDose

the reference dose x^{*}

Examples

model <- LogisticLogNormalSub(mean = c(-0.85, 1),
                           cov = matrix(c(1, -0.5, -0.5, 1), nrow = 2),
                           refDose = 50)

crmPack documentation built on June 26, 2024, 5:07 p.m.