setup_FE_model

Setup fixed effects part for longitudinal marker k (internal function)
input:

Estimation of joint models for multivariate longitudinal markers (with various distributions available) and survival outcomes (possibly accounting for competing risks) with Integrated Nested Laplace Approximations (INLA). The flexible and user friendly function joint() facilitates the use of the fast and reliable inference technique implemented in the 'INLA' package for joint modeling. More details are given in the help page of the joint() function (accessible via ?joint in the R console) and the vignette associated to the joint() function (accessible via vignette("INLAjoint") in the R console).

Denis Rustand

INLAjoint

Multivariate Joint Modeling for Longitudinal and Time-to-Event
Outcomes with 'INLA'

Elias Teixeira Krainski

Haavard Rue

Janet van Niekerk

setup_FE_model function

<dl><dt>formula</dt>
<dd>with lme4 format (fixed effects and random effects in the same object)</dd>
<dt>dataset</dt>
<dd>that contains the outcome</dd>
<dt>timeVar</dt>
<dd>name of time variable</dd>
<dt>k</dt>
<dd>identifies the longitudinal marker among 1:K markers</dd>
<dt>dataOnly</dt>
<dd>boolean for internal use, indicates if only preparing data (i.e., not fitting the model)
output:</dd></dl>

Arguments

Setup fixed effects part for longitudinal marker k — setup_FE_model

<dl>

<dt>formula</dt>
<dd>with lme4 format (fixed effects and random effects in the same object)</dd>


<dt>dataset</dt>
<dd>that contains the outcome</dd>


<dt>timeVar</dt>
<dd>name of time variable</dd>


<dt>k</dt>
<dd>identifies the longitudinal marker among 1:K markers</dd>


<dt>dataOnly</dt>
<dd>boolean for internal use, indicates if only preparing data (i.e., not fitting the model)
output:</dd>

</dl>

setup_FE_model: Setup fixed effects part for longitudinal marker k

Description

Usage

Value

Arguments