blrm_formula_linear

<code>blrm_formula_linear</code> is a convenience function
for generating a formula for <code>blrm_trial</code> and
<code>blrm_exnex</code> with an interaction of the form:
$$\eta \, \prod_{i=1}^N (d_i \big / d_i^*))$$

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.

Sebastian Weber

OncoBayes2

Bayesian Logistic Regression for Oncology Dose-Escalation Trials

Novartis Pharma AG

Lukas A. Widmer

Andrew Bean

Trustees of Columbia University

blrm_formula_linear function

<dl><dt>ref_doses</dt>
<dd>Numeric vector of reference doses with names
corresponding to drug names</dd>
<dt>max_interaction_level</dt>
<dd>Highest interaction order to consider
$[1 - Inf]$. Default: 2</dd>
<dt>specific_interaction_terms</dt>
<dd>List of custom interaction terms
to generate (e.g. list(c("drug1", "drug2"), c("drug1",
"drug3"))). Default: NULL</dd></dl>

Arguments

Build a BLRM formula with linear interaction term in logit-space — blrm_formula_linear

<dl>

<dt>ref_doses</dt>
<dd>Numeric vector of reference doses with names
corresponding to drug names</dd>


<dt>max_interaction_level</dt>
<dd>Highest interaction order to consider
$[1 - Inf]$. Default: 2</dd>


<dt>specific_interaction_terms</dt>
<dd>List of custom interaction terms
to generate (e.g. list(c("drug1", "drug2"), c("drug1",
"drug3"))). Default: NULL</dd>

</dl>

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blrm_formula_linear: Build a BLRM formula with linear interaction term in logit-space

Description

Usage

Value

Arguments

Examples