sampleParameters

Generates parameters from models estimated with <code>hlme</code>,
<code>lcmm</code>, <code>multlcmm</code>, <code>Jointlcmm</code> or <code>mpjlcmm</code> functions.
Parameters are randomly sampled from a Gaussian distribution using estimates
and corresponding variances of a model.

Estimation of various extensions of the mixed models including latent class mixed models, joint latent class mixed models, mixed models for curvilinear outcomes, mixed models for multivariate longitudinal outcomes using a maximum likelihood estimation method (Proust-Lima, Philipps, Liquet (2017) <doi:10.18637/jss.v078.i02>).

Cécile Proust-Lima

lcmm

Extended Mixed Models Using Latent Classes and Latent Processes

Cecile Proust-Lima

Viviane Philipps

Amadou Diakite

Benoit Liquet

Alan Genz

John Burkardt

sampleParameters function

<dl><dt>x</dt>
<dd>an object of class <code>hlme</code>, <code>lcmm</code>, <code>multlcmm</code>,
<code>Jointlcmm</code>, or <code>mpjlcmm</code>.</dd>
<dt>cholesky</dt>
<dd>optional logical indicating if cholesky parameters should be
returned. Default to FALSE, the variance-covariance parameters of the
random effects are returned.</dd></dl>

Arguments

Author

Sample models parameters — sampleParameters

<dl>

<dt>x</dt>
<dd>an object of class <code>hlme</code>, <code>lcmm</code>, <code>multlcmm</code>,
<code>Jointlcmm</code>, or <code>mpjlcmm</code>.</dd>


<dt>cholesky</dt>
<dd>optional logical indicating if cholesky parameters should be
returned. Default to FALSE, the variance-covariance parameters of the
random effects are returned.</dd>

</dl>

sampleParameters: Sample models parameters

Description

Usage

Value

Arguments

Author

Examples