get_cox_risk_and_failure_sets

This function calculates the risk and failure sets for subjects in a Cox proportional hazards model based on their time-to-event data, status, and an indicator vector.

To improve estimation accuracy and stability in statistical modeling, catalytic prior distributions are employed, integrating observed data with synthetic data generated from a simpler model's predictive distribution. This approach enhances model robustness, stability, and flexibility in complex data scenarios. The catalytic prior distributions are introduced by 'Huang et al.' (2020, <doi:10.1073/pnas.1920913117>), Li and Huang (2023, <doi:10.48550/arXiv.2312.01411>).

Dongming Huang

catalytic

Tools for Applying Catalytic Priors in Statistical Modeling

Yitong Wu

Weihao Li

Ministry of Education, Singapore 

get_cox_risk_and_failure_sets function

<dl><dt>time_vector</dt>
<dd>A numeric vector of time-to-event data for each subject.</dd>
<dt>status_vector</dt>
<dd>A numeric vector indicating event occurrence (1 = event, 0 = censored).</dd>
<dt>indicator_vector</dt>
<dd>A numeric vector representing the indicator times used to define risk and failure sets.</dd></dl>

Arguments

Calculate Risk and Failure Sets for Cox Proportional Hazards Model — get_cox_risk_and_failure_sets

<dl>

<dt>time_vector</dt>
<dd>A numeric vector of time-to-event data for each subject.</dd>


<dt>status_vector</dt>
<dd>A numeric vector indicating event occurrence (1 = event, 0 = censored).</dd>


<dt>indicator_vector</dt>
<dd>A numeric vector representing the indicator times used to define risk and failure sets.</dd>

</dl>

get_cox_risk_and_failure_sets: Calculate Risk and Failure Sets for Cox Proportional Hazards Model

Description

Usage

Value

Arguments