LogisticIndepBeta

Intialization function for "LogisticIndepBeta" class

methods

Implements a wide range of model-based dose
escalation 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. The
focus is on Bayesian inference, making it very easy to setup a new design
with its own 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.

Daniel Sabanes Bove

crmPack

Object-Oriented Implementation of CRM Designs

Wai Yin Yeung

Giuseppe Palermo

Thomas Jaki

LogisticIndepBeta function

<dl><dt>binDLE</dt>
<dd>the number of subjects observed with a DLE, the pseudo DLE responses</dd>
<dt>DLEdose</dt>
<dd>the corresponding dose levels for the pseudo DLE responses, pseudo dose levels</dd>
<dt>DLEweights</dt>
<dd>the total number of subjects treated at each of the dose levels, pseudo weights</dd>
<dt>data</dt>
<dd>the input data to update estimates of model parameters and 
follow the <code>Data</code> object class specification</dd></dl>

Arguments

Intialization function for "LogisticIndepBeta" class — LogisticIndepBeta

<dl>

<dt>binDLE</dt>
<dd>the number of subjects observed with a DLE, the pseudo DLE responses</dd>


<dt>DLEdose</dt>
<dd>the corresponding dose levels for the pseudo DLE responses, pseudo dose levels</dd>


<dt>DLEweights</dt>
<dd>the total number of subjects treated at each of the dose levels, pseudo weights</dd>


<dt>data</dt>
<dd>the input data to update estimates of model parameters and 
follow the <code>Data</code> object class specification</dd>

</dl>

LogisticIndepBeta: Intialization function for "LogisticIndepBeta" class

Description

Usage

Value

Arguments