conduct.phase2

This function is used to estimate the effect size of each subgroup and to
select the most promising subgroup.

Design a Bayesian seamless multi-arm biomarker-enriched phase II/III
design with the survival endpoint with allowing sample size re-estimation.
James M S Wason, Jean E Abraham, Richard D Baird, Ioannis Gournaris, Anne-Laure Vallier, James D Brenton, Helena M Earl, Adrian P Mander (2015) <doi:10.1038/bjc.2015.278>.
Guosheng Yin, Nan Chen, J. Jack Lee (2018) <doi:10.1007/s12561-017-9199-7>.
Ying Yuan, Beibei Guo, Mark Munsell, Karen Lu, Amir Jazaeri (2016) <doi:10.1002/sim.6971>.

Chengxue Zhong

SAME

Seamless Adaptive Multi-Arm Multi-Stage Enrichment

Haitao Pan

Hongyu Miao

conduct.phase2 function

<dl><dt>formula</dt>
<dd>a formula object, with the combinations of treatment and
biomarker term, e.g., formula = "T1:B1+T1:B2+T2:B1+T2:B2"</dd>
<dt>surv</dt>
<dd>survival time</dd>
<dt>event</dt>
<dd>the status indicator, 0=alive, 1=dead</dd>
<dt>data</dt>
<dd>a data.frame in which to interpret the variables named in the formula</dd></dl>

Arguments

Function to identify the most promising treatment-biomarker-linked subgroup — conduct.phase2

<dl>

<dt>formula</dt>
<dd>a formula object, with the combinations of treatment and
biomarker term, e.g., formula = "T1:B1+T1:B2+T2:B1+T2:B2"</dd>


<dt>surv</dt>
<dd>survival time</dd>


<dt>event</dt>
<dd>the status indicator, 0=alive, 1=dead</dd>


<dt>data</dt>
<dd>a data.frame in which to interpret the variables named in the formula</dd>

</dl>

conduct.phase2: Function to identify the most promising treatment-biomarker-linked subgroup

Description

Usage

Value

Arguments

Examples