print.SLCARE

Print point estimates (Est), bootstrap standard error estimates (SE), initial estimates for the estimation algorithm (Init), convergence criterion (ConvergeLoss), latent class membership probability (ClassProb), predicted number of recurrent events (PostPredict), relative entropy of the fitted model (Entropy), p-value (pvalue) for SLCARE.

Efficient R package for latent class analysis of recurrent events, based on the semiparametric multiplicative intensity model by Zhao et al. (2022) <doi:10.1111/rssb.12499>. SLCARE returns estimates for non-functional model parameters along with the associated variance estimates and p-values. Visualization tools are provided to depict the estimated functional model parameters and related functional quantities of interest. SLCARE also delivers a model checking plot to help assess the adequacy of the fitted model.

Qi Yu

SLCARE

Semiparametric Latent Class Analysis of Recurrent Events

Limin Peng

print.SLCARE function

<dl><dt>x</dt>
<dd>an object of class <code>SLCARE</code>.</dd>
<dt>type</dt>
<dd>the type of the output.</dd>
<dt>...</dt>
<dd>other arguments.</dd></dl>

Arguments

Print Results for SLCARE — print.SLCARE

<dl>

<dt>x</dt>
<dd>an object of class <code>SLCARE</code>.</dd>


<dt>type</dt>
<dd>the type of the output.</dd>


<dt>...</dt>
<dd>other arguments.</dd>

</dl>

print.SLCARE: Print Results for SLCARE

Description

Usage

Arguments

See Also