h_eval_combo_truth

<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>
Evaluates the true toxicity probability at a given dose combination using the
provided <code>truth</code> function. The <code>truth</code> function can be flexible in how it
accepts the dose combination as input, and this helper tries different ways to
call it in order to extract the toxicity probability.

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 

h_eval_combo_truth function

<dl><dt>truth</dt>
<dd>(<code>function</code>) optional function mapping a dose combination to
a toxicity probability. It can accept one argument (length-2 numeric vector
or one-row matrix) or two numeric arguments (<code>drug1</code>, <code>drug2</code>).</dd>
<dt>dose_pair</dt>
<dd>(<code>numeric</code>) a length-2 numeric vector representing the dose
combination for drug1 and drug2.</dd>
<dt>...</dt>
<dd>additional arguments passed to <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>
Evaluates the true toxicity probability at a given dose combination using the
provided <code>truth</code> function. The <code>truth</code> function can be flexible in how it
accepts the dose combination as input, and this helper tries different ways to
call it in order to extract the toxicity probability.

Helper for Evaluating the True Toxicity Probability at a Dose Combination — h_eval_combo_truth

<dl>

<dt>truth</dt>
<dd>(<code>function</code>) optional function mapping a dose combination to
a toxicity probability. It can accept one argument (length-2 numeric vector
or one-row matrix) or two numeric arguments (<code>drug1</code>, <code>drug2</code>).</dd>


<dt>dose_pair</dt>
<dd>(<code>numeric</code>) a length-2 numeric vector representing the dose
combination for drug1 and drug2.</dd>


<dt>...</dt>
<dd>additional arguments passed to <code>truth</code>.</dd>

</dl>

Helper for Evaluating the True Toxicity Probability at a Dose Combination

h_eval_combo_truth: Helper for Evaluating the True Toxicity Probability at a Dose Combination

Description

Usage

Value

Arguments