v_samples_objects

v_samples

These functions are only used internally to validate the format
of an input <code>Samples</code> or inherited classes and therefore not exported.

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
Sabanes Bove et al. (2019) <doi:10.18637/jss.v089.i10>.

Daniel Sabanes Bove

crmPack

Object-Oriented Implementation of Dose Escalation Designs

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 

v_samples_objects function

<dl><dt>object</dt>
<dd>(<code>Samples</code>) object to validate.</dd></dl>

Arguments

<ul>
<li><code>v_samples()</code>: validates that the <code>Samples</code> object contains
valid <code>data</code> slot.</li>
</ul>

Functions

Internal Helper Functions for Validation of Samples Objects — v_samples_objects

<dl>

<dt>object</dt>
<dd>(<code>Samples</code>) object to validate.</dd>

</dl>

Internal Helper Functions for Validation of <code>Samples</code> Objects

v_samples_objects: Internal Helper Functions for Validation of `Samples` Objects

Description

Usage

Value

Arguments

Functions