JMMLSM_control

Control options for <code>JMMLSM()</code>

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

JMMLSM_control function

<dl><dt>maxiter</dt>
<dd>Maximum number of EM iterations. The default is <code>1000</code>.</dd>
<dt>tol</dt>
<dd>Convergence tolerance. The default is <code>1e-4</code>.</dd>
<dt>quadpoint</dt>
<dd>Number of Gauss--Hermite quadrature points. The default is
<code>15</code>.</dd>
<dt>verbose</dt>
<dd>Logical value indicating whether to print iteration details.
The default is <code>FALSE</code>.</dd>
<dt>initial.para</dt>
<dd>Optional list of user-supplied initial parameter values.
The default is <code>NULL</code>.</dd>
<dt>method</dt>
<dd>Numerical integration method used in the E-step. Available
options are <code>"adaptive"</code> and <code>"standard"</code>. The default is
<code>"adaptive"</code>.</dd>
<dt>opt</dt>
<dd>Optimization method used to fit the initial linear mixed-effects
model. Available options are <code>"nlminb"</code> and <code>"optim"</code>. The default
is <code>"nlminb"</code>.</dd></dl>

Arguments

Control Options for JMMLSM — JMMLSM_control

<dl>

<dt>maxiter</dt>
<dd>Maximum number of EM iterations. The default is <code>1000</code>.</dd>


<dt>tol</dt>
<dd>Convergence tolerance. The default is <code>1e-4</code>.</dd>


<dt>quadpoint</dt>
<dd>Number of Gauss--Hermite quadrature points. The default is
<code>15</code>.</dd>


<dt>verbose</dt>
<dd>Logical value indicating whether to print iteration details.
The default is <code>FALSE</code>.</dd>


<dt>initial.para</dt>
<dd>Optional list of user-supplied initial parameter values.
The default is <code>NULL</code>.</dd>


<dt>method</dt>
<dd>Numerical integration method used in the E-step. Available
options are <code>"adaptive"</code> and <code>"standard"</code>. The default is
<code>"adaptive"</code>.</dd>


<dt>opt</dt>
<dd>Optimization method used to fit the initial linear mixed-effects
model. Available options are <code>"nlminb"</code> and <code>"optim"</code>. The default
is <code>"nlminb"</code>.</dd>

</dl>

JMMLSM_control: Control Options for JMMLSM

Description

Usage

Value

Arguments

Details