ydata

The <code>ydata</code> data frame has 1353 rows and 6 columns.

datasets

Maximum likelihood estimation for the semi-parametric joint modeling of competing risks and longitudinal data in the presence of heterogeneous within-subject variability, proposed by Li and colleagues (2023) <arXiv:2301.06584>.
The proposed method models the within-subject variability of the biomarker and associates it with the risk of the competing risks event. The time-to-event data is modeled using a (cause-specific) Cox proportional hazards regression model with time-fixed covariates.
The longitudinal outcome is modeled using a mixed-effects location and scale model. The association is captured by shared random effects. The model
is estimated using an Expectation Maximization algorithm.

Shanpeng Li

Joint Model of Heterogeneous Repeated Measures and Survival Data

Jin Zhou

Hua Zhou

Gang Li

ydata function

This data frame contains the following columns:
<dl> <dt><code>ID</code></dt>
<dd>patient identifier.</dd>
 <dt><code>Y</code></dt>
<dd>response variable.</dd>
 <dt><code>time</code></dt>
<dd>visit time.</dd>
 <dt><code>Z1</code></dt>
<dd>treatment indicator. <code>0</code> denotes the placebo group and <code>1</code> the treatment group.</dd> 
 <dt><code>Z2</code></dt>
<dd>continuous variable..</dd> 
 <dt><code>Z3</code></dt>
<dd>continuous variable..</dd> 
</dl>

Format

Simulated longitudinal data — ydata

This data frame contains the following columns:
<dl>

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


 <dt><code>Y</code></dt>
<dd>response variable.</dd>


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


 <dt><code>Z1</code></dt>
<dd>treatment indicator. <code>0</code> denotes the placebo group and <code>1</code> the treatment group.</dd>

 
 <dt><code>Z2</code></dt>
<dd>continuous variable..</dd>

 
 <dt><code>Z3</code></dt>
<dd>continuous variable..</dd>

 
</dl>

ydata: Simulated longitudinal data

Description

Usage

Arguments

Format