ConcordanceJMMLSM

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) <doi:10.48550/arXiv.2506.12741>.
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. This is the final release of the 'JMH' package. Active development has been moved to the 'FastJM' package, which provides improved functionality and ongoing support. Users are strongly encouraged to transition to 'FastJM'.

Shanpeng Li

Joint Model of Heterogeneous Repeated Measures and Survival Data

Gang Li

ConcordanceJMMLSM function

<dl><dt>seed</dt>
<dd>a numeric value of seed to be specified for cross validation.</dd>
<dt>object</dt>
<dd>object of class 'JMMLSM'.</dd>
<dt>opt</dt>
<dd>Optimization method to fit a linear mixed effects model, either nlminb (default) or optim.</dd>
<dt>n.cv</dt>
<dd>number of folds for cross validation. Default is 3.</dd>
<dt>maxiter</dt>
<dd>the maximum number of iterations of the EM algorithm that the 
function will perform. Default is 10000.</dd>
<dt>initial.optimizer</dt>
<dd>Method for numerical optimization to be used. Default is <code>BFGS</code>.</dd>
<dt>initial.para</dt>
<dd>Initial guess of parameters for cross validation. Default is FALSE.</dd>
<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd></dl>

Arguments

Shanpeng Li <a href="/link/lishanpeng0913%40ucla.edu?package=JMH&version=1.0.4" data-mini-rdoc="JMH::lishanpeng0913@ucla.edu">lishanpeng0913@ucla.edu</a>

Author

Concordance for joint models — ConcordanceJMMLSM

<dl>

<dt>seed</dt>
<dd>a numeric value of seed to be specified for cross validation.</dd>


<dt>object</dt>
<dd>object of class 'JMMLSM'.</dd>


<dt>opt</dt>
<dd>Optimization method to fit a linear mixed effects model, either nlminb (default) or optim.</dd>


<dt>n.cv</dt>
<dd>number of folds for cross validation. Default is 3.</dd>


<dt>maxiter</dt>
<dd>the maximum number of iterations of the EM algorithm that the 
function will perform. Default is 10000.</dd>


<dt>initial.optimizer</dt>
<dd>Method for numerical optimization to be used. Default is <code>BFGS</code>.</dd>


<dt>initial.para</dt>
<dd>Initial guess of parameters for cross validation. Default is FALSE.</dd>


<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd>

</dl>

Shanpeng Li <a href='mailto:lishanpeng0913@ucla.edu'>lishanpeng0913@ucla.edu</a>

ConcordanceJMMLSM: Concordance for joint models

Description

Usage

Value

Arguments

Author

See Also