NextBestMTD-class

.NextBestMTD

The class with the input for finding the next best MTD estimate

classes

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

NextBestMTD-class function

<dl>
<dt><code>target</code></dt>
<dd>the target toxicity probability</dd></dl>
<dt><code>derive</code></dt>
<dd>the function which derives from the input, a vector of
posterior MTD samples called <code>mtdSamples</code>, the final next best MTD
estimate.</dd>

Slots

The class with the input for finding the next best MTD estimate — NextBestMTD-class

<dl>
<dt><code>target</code></dt>
<dd>the target toxicity probability</dd>


<dt><code>derive</code></dt>
<dd>the function which derives from the input, a vector of
posterior MTD samples called <code>mtdSamples</code>, the final next best MTD
estimate.</dd>


</dl>

NextBestMTD-class: The class with the input for finding the next best MTD estimate

Description

Arguments

Slots

Examples