summary,HierarchicalSimulations-method

summary-HierarchicalSimulations

<a href="https://lifecycle.r-lib.org/articles/stages.html#experimental"><img src="figures/lifecycle-experimental.svg?package=crmPack&version=2.2.1" alt="[Experimental]"></a>
Summarize hierarchical simulations by delegating to the corresponding
arm-level simulation summary methods.

Implements a wide range of dose escalation
designs. The focus is on model-based 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. Bayesian inference is performed via MCMC sampling in JAGS, and it is easy
to setup a new design with custom 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.
Further details are presented in
Sabanés Bové et al. (2019) <doi:10.18637/jss.v089.i10>.

Daniel Sabanes Bove

crmPack

Object-Oriented Implementation of Dose Escalation Designs

Daniel Sabanés Bové

Wai Yin Yeung

Burak Kuersad Guenhan

Giuseppe Palermo

Thomas Jaki

Jiawen Zhu

Ziwei Liao

Dimitris Kontos

Marlene Schulte-Goebel

Doug Kelkhoff

Oliver Boix

Robert Adams

Clara Beck

John Kirkpatrick

Wojciech Wójciak

Guanya Peng

Prerana Chandratre

F. Hoffmann-La Roche AG 

Merck Healthcare KGaA 

Bayer AG 

RPACT GmbH 

summary,HierarchicalSimulations-method function

<dl><dt>object</dt>
<dd>(<code>HierarchicalSimulations</code>) the object we want to summarize.</dd>
<dt>truth</dt>
<dd>(<code>function</code> or named <code>list</code> of <code>function</code>) true DLT
probability function(s). If a list is supplied, names must match the
hierarchical arms.</dd>
<dt>target</dt>
<dd>(<code>numeric</code> or named <code>list</code> of <code>numeric</code>) target toxicity
interval(s). If a list is supplied, names must match the hierarchical arms.</dd>
<dt>...</dt>
<dd>additional arguments can be supplied here for <code>truth</code>.</dd></dl>

Arguments

<a href='https://lifecycle.r-lib.org/articles/stages.html#experimental'><img src='figures/lifecycle-experimental.svg' alt='[Experimental]' /></a>
Summarize hierarchical simulations by delegating to the corresponding
arm-level simulation summary methods.

Summarize Hierarchical Design Simulations — summary,HierarchicalSimulations-method

<dl>

<dt>object</dt>
<dd>(<code>HierarchicalSimulations</code>) the object we want to summarize.</dd>


<dt>truth</dt>
<dd>(<code>function</code> or named <code>list</code> of <code>function</code>) true DLT
probability function(s). If a list is supplied, names must match the
hierarchical arms.</dd>


<dt>target</dt>
<dd>(<code>numeric</code> or named <code>list</code> of <code>numeric</code>) target toxicity
interval(s). If a list is supplied, names must match the hierarchical arms.</dd>


<dt>...</dt>
<dd>additional arguments can be supplied here for <code>truth</code>.</dd>

</dl>

Summarize Hierarchical Design Simulations

summary,HierarchicalSimulations-method: Summarize Hierarchical Design Simulations

Description

Usage

Value

Arguments