ProbitLogNormal

Initialization function for the "ProbitLogNormal" class

methods

Implements a wide range of model-based dose
escalation designs, ranging from classical and modern continual
reassessment methods (CRMs) based on dose-limiting toxicity endpoints to
dual-endpoint designs taking into account a biomarker/efficacy outcome. The
focus is on Bayesian inference, making it very easy to setup a new design
with its own JAGS code. However, it is also possible to implement 3+3
designs for comparison or models with non-Bayesian estimation. The whole
package is written in a modular form in the S4 class system, making it very
flexible for adaptation to new models, escalation or stopping rules.

Daniel Sabanes Bove

crmPack

Object-Oriented Implementation of CRM Designs

Wai Yin Yeung

Giuseppe Palermo

Thomas Jaki

ProbitLogNormal function

<dl><dt>mu</dt>
<dd>the prior mean vector</dd>
<dt>Sigma</dt>
<dd>the prior covariance matrix</dd>
<dt>refDose</dt>
<dd>the reference dose \(x^{*}\), default 1 (no standardization)</dd>
<dt>useLogDose</dt>
<dd>should the log of (standardized) dose be used? (not default)</dd></dl>

Arguments

Initialization function for the "ProbitLogNormal" class — ProbitLogNormal

<dl>

<dt>mu</dt>
<dd>the prior mean vector</dd>


<dt>Sigma</dt>
<dd>the prior covariance matrix</dd>


<dt>refDose</dt>
<dd>the reference dose \(x^{*}\), default 1 (no standardization)</dd>


<dt>useLogDose</dt>
<dd>should the log of (standardized) dose be used? (not default)</dd>

</dl>

ProbitLogNormal: Initialization function for the "ProbitLogNormal" class

Description

Usage

Value

Arguments