Concordance

Implements scalable joint models for large-scale competing risks time-to-event data with one or multiple longitudinal biomarkers using the efficient algorithms developed by Li et al. (2022) <doi:10.1155/2022/1362913> and <doi:10.48550/arXiv.2506.12741>.
The time-to-event process is modeled using a cause-specific Cox proportional hazards model
with time-fixed covariates, while longitudinal biomarkers are modeled
using linear mixed-effects models. The association between the longitudinal
and survival processes is captured through shared random effects. The
package enables analysis of large-scale biomedical data to model biomarker
trajectories, estimate their effects on event risks, and perform dynamic
prediction of future events based on patients' longitudinal histories.
Functions for simulating survival and longitudinal data for multiple
biomarkers are included, along with built-in example datasets. The package
also supports modeling a single biomarker with heterogeneous within-subject
variability via functionality adapted from the 'JMH' package.

Shanpeng Li

FastJM

Semi-Parametric Joint Modeling of Longitudinal and Survival Data

Ace Mejia-Sanchez

Emily Ouyang

Gang Li

Concordance function

<dl><dt>seed</dt>
<dd>A numeric value used to set the random seed for cross-validation.
Default is <code>100</code>.</dd>
<dt>object</dt>
<dd>A fitted object of class <code>jmcs</code>, <code>JMMLSM</code>, or <code>mvjmcs</code>.</dd>
<dt>n.cv</dt>
<dd>Number of cross-validation folds. Default is <code>3</code>.</dd>
<dt>maxiter</dt>
<dd>Maximum number of EM iterations allowed when refitting the
model within each cross-validation fold. Default is <code>10000</code>.</dd>
<dt>initial.para</dt>
<dd>Logical value indicating whether initial parameter values
are used when refitting the model. Default is <code>TRUE</code>.</dd>
<dt>...</dt>
<dd>Further arguments passed to model-specific methods.</dd></dl>

Arguments

Concordance for joint models — Concordance

<dl>

<dt>seed</dt>
<dd>A numeric value used to set the random seed for cross-validation.
Default is <code>100</code>.</dd>


<dt>object</dt>
<dd>A fitted object of class <code>jmcs</code>, <code>JMMLSM</code>, or <code>mvjmcs</code>.</dd>


<dt>n.cv</dt>
<dd>Number of cross-validation folds. Default is <code>3</code>.</dd>


<dt>maxiter</dt>
<dd>Maximum number of EM iterations allowed when refitting the
model within each cross-validation fold. Default is <code>10000</code>.</dd>


<dt>initial.para</dt>
<dd>Logical value indicating whether initial parameter values
are used when refitting the model. Default is <code>TRUE</code>.</dd>


<dt>...</dt>
<dd>Further arguments passed to model-specific methods.</dd>

</dl>

Concordance: Concordance for joint models

Description

Usage

Value

Arguments

See Also