hnscc

High dimensional head and neck cancer gene expression data

datasets

Perform mediation analysis for time to event high-dimensional data.
Mediation Analysis proposed by Miocevic et al.(2017) <doi:10.1080/10705511.2017.1342541>
as a statistical tool in the Bayesian framework.
Time to event data analysis methods like Cox proportional hazard model,
accelerated failure time model to work with high dimensional data
with Bayesian approaches are provided. Missing data imputation techniques tool
to work with high dimensional data coupled for mediation analysis by
presented by the active mediator variables.

Atanu Bhattacharjee

autohd

High Dimensional Bayesian Survival Mediation Analysis

Akash Pawar

hnscc function

A dataframe with 565 rows and 104 variables<dl class="dl-horizontal">
<dt>ID</dt><dd>ID of subjects</dd>
<dt>leftcensoring</dt><dd>Initial censoring time</dd>
<dt>death</dt><dd>Survival event</dd>
<dt>death2</dt><dd>Survival event with competing risk</dd>
<dt>os</dt><dd>Duration of overall survival</dd>
<dt>PFS</dt><dd>Duration of progression free survival</dd>
<dt>Prog</dt><dd>Progression event</dd>
<dt>GJB1,...,HMGCS2</dt><dd>High dimensional covariates</dd></dl>

Format

Head and neck cancer data — hnscc

A dataframe with 565 rows and 104 variables<dl class='dl-horizontal'>
<dt>ID</dt><dd>ID of subjects</dd>
<dt>leftcensoring</dt><dd>Initial censoring time</dd>
<dt>death</dt><dd>Survival event</dd>
<dt>death2</dt><dd>Survival event with competing risk</dd>
<dt>os</dt><dd>Duration of overall survival</dd>
<dt>PFS</dt><dd>Duration of progression free survival</dd>
<dt>Prog</dt><dd>Progression event</dd>
<dt>GJB1,...,HMGCS2</dt><dd>High dimensional covariates</dd></dl>

hnscc: Head and neck cancer data

Description

Usage

Arguments

Format

Examples