mvydata

The <code>mvydata</code> data frame has 4060 rows and 6 columns.

datasets

A joint model for large-scale, competing risks time-to-event data with singular or multiple longitudinal biomarkers, implemented with the efficient algorithms developed by Li and colleagues (2022) <doi:10.1155/2022/1362913> and <doi:10.48550/arXiv.2506.12741>.
The time-to-event data is modelled using a (cause-specific) Cox
proportional hazards regression model with time-fixed covariates.
The longitudinal biomarkers are modelled using a linear mixed
effects model. The association between the longitudinal submodel
and the survival submodel is captured through shared random
effects. It allows researchers to analyze large-scale data to
model biomarker trajectories, estimate their effects on event
outcomes, and dynamically predict future events from patients’
past histories. A function for simulating survival and longitudinal
data for multiple biomarkers is also included alongside built-in
datasets.

Shanpeng Li

FastJM

Semi-Parametric Joint Modeling of Longitudinal and Survival Data

Ning Li

Emily Ouyang

Hong Wang

Jin Zhou

Hua Zhou

Gang Li

mvydata function

This data frame contains the following columns:
<dl> <dt><code>ID</code></dt>
<dd>patient identifier.</dd> 
 <dt><code>time</code></dt>
<dd>visit time.</dd> 
 <dt><code>Y1</code></dt>
<dd>response variable of biomarker 1.</dd> 
 <dt><code>Y2</code></dt>
<dd>response variable of biomarker 2.</dd>
 <dt><code>X11</code></dt>
<dd>X11.</dd> 
 <dt><code>X12</code></dt>
<dd>X12.</dd> 
 
</dl>

Format

Simulated bivariate longitudinal data — mvydata

This data frame contains the following columns:
<dl>

 <dt><code>ID</code></dt>
<dd>patient identifier.</dd>

 
 <dt><code>time</code></dt>
<dd>visit time.</dd>

 
 <dt><code>Y1</code></dt>
<dd>response variable of biomarker 1.</dd>

 
 <dt><code>Y2</code></dt>
<dd>response variable of biomarker 2.</dd>


 <dt><code>X11</code></dt>
<dd>X11.</dd>

 
 <dt><code>X12</code></dt>
<dd>X12.</dd>

 
 
</dl>

mvydata: Simulated bivariate longitudinal data

Description

Usage

Arguments

Format