extenet

Based on re-constructed Kaplan-Meier plot from ExteNET trial (Martin et al., 2017)

datasets

Implements tipping point sensitivity analysis for time-to-event endpoints under different missing data scenarios, as described in Oodally et al. (2025) <doi:10.48550/arXiv.2506.19988>. Supports both model-based and model-free imputation, multiple imputation workflows, plausibility assessment and visualizations. Enables robust assessment for regulatory and exploratory analyses.

Ajmal Oodally

tipse

Tipping Point Analysis for Survival Endpoints

Craig Wang

Zheng Li

extenet function

A data frame with 2840 rows and 5 columns:<dl>
<dt>SUBJID</dt>
<dd>Dummy patient ID</dd><dt>TRT01P</dt>
<dd>Treatment arm (Neratinib or placebo)</dd><dt>AVAL</dt>
<dd>iDFS time in days</dd><dt>EVENT</dt>
<dd>Indicator for iDFS event</dd><dt>CNSRRS</dt>
<dd>Censoring reason (Lost to follow-up or Other)</dd><dt>MAXAVAL</dt>
<dd>Maximum potential survival time, duration between randomization to data cut-off</dd>
</dl>

Format

Patient level data from dummy trial — extenet

A data frame with 2840 rows and 5 columns:<dl>
<dt>SUBJID</dt>
<dd>Dummy patient ID</dd>

<dt>TRT01P</dt>
<dd>Treatment arm (Neratinib or placebo)</dd>

<dt>AVAL</dt>
<dd>iDFS time in days</dd>

<dt>EVENT</dt>
<dd>Indicator for iDFS event</dd>

<dt>CNSRRS</dt>
<dd>Censoring reason (Lost to follow-up or Other)</dd>

<dt>MAXAVAL</dt>
<dd>Maximum potential survival time, duration between randomization to data cut-off</dd>


</dl>

extenet: Patient level data from dummy trial

Description

Usage

Arguments

Format