Bayesian logistic regression model with optional
EXchangeability-NonEXchangeability parameter modelling for flexible
borrowing from historical or concurrent data-sources. The safety model
can guide dose-escalation decisions for adaptive oncology Phase I
dose-escalation trials which involve an arbitrary number of
drugs. Please refer to Neuenschwander et al. (2008)
<doi:10.1002/sim.3230> and Neuenschwander et al. (2016)
<doi:10.1080/19466315.2016.1174149> for details on the methodology.

Bayesian Logistic Regression for Oncology Dose-Escalation Trials

package-ubuntu-20.04-r-4.0.5#cran#OncoBayes2-0.7-0

<table summary="R argblock">
<tr valign="top">
<td><code>x</code></td>
<td>
<p>object to summarise</p>
</td>
</tr>
<tr valign="top">
<td><code>margin</code></td>
<td>
<p>margin over which to marginalize</p>
</td>
</tr>
</table>

package-ubuntu-20.04-r-4.0.5#cran#OncoBayes2-0.7-0#docs#dot-marginSums

dot-marginSums

Description

Usage

Arguments

OncoBayes2

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`x`	object to summarise
`margin`	margin over which to marginalize