predRE

Function to compute individual random effects using hlme output parameters

internal

Based on random forest principle, 'DynForest' is able to include
multiple longitudinal predictors to provide individual predictions.
Longitudinal predictors are modeled through the random forest. The
methodology is fully described for a survival outcome in:
Devaux, Helmer, Genuer & Proust-Lima (2023)
<doi: 10.1177/09622802231206477>.

Anthony Devaux

DynForest

Random Forest with Multivariate Longitudinal Predictors

Robin Genuer

Cécile Proust-Lima

Louis Capitaine

predRE function

<dl><dt>model</dt>
<dd>output object from hlme function</dd>
<dt>formula</dt>
<dd>list of formula for fixed and random part</dd>
<dt>data</dt>
<dd>data to compute random effect</dd></dl>

Arguments

Function to compute individual random effects using hlme output parameters — predRE

<dl>

<dt>model</dt>
<dd>output object from hlme function</dd>


<dt>formula</dt>
<dd>list of formula for fixed and random part</dd>


<dt>data</dt>
<dd>data to compute random effect</dd>

</dl>

predRE: Function to compute individual random effects using hlme output parameters

Description

Usage

Value

Arguments