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.

Object-Oriented Implementation of CRM Designs

package-ubuntu-20.04-r-4.0.5#cran#crmPack-1.0.0

<p>The virtual class for stopping rules
</p>

<p><code><a href="StoppingList-class.html">StoppingList</a></code>,
<code><a href="StoppingCohortsNearDose-class.html">StoppingCohortsNearDose</a></code>,
<code><a href="StoppingPatientsNearDose-class.html">StoppingPatientsNearDose</a></code>,
<code><a href="StoppingMinCohorts-class.html">StoppingMinCohorts</a></code>,
<code><a href="StoppingMinPatients-class.html">StoppingMinPatients</a></code>,
<code><a href="StoppingTargetProb-class.html">StoppingTargetProb</a></code>
<code><a href="StoppingMTDdistribution-class.html">StoppingMTDdistribution</a></code>,
<code><a href="StoppingTargetBiomarker-class.html">StoppingTargetBiomarker</a></code>,
<code><a href="StoppingHighestDose-class.html">StoppingHighestDose</a></code>
</p>

package-ubuntu-20.04-r-4.0.5#cran#crmPack-1.0.0#docs#Stopping-class

Stopping-class

Description

See Also

crmPack

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