data.time

Management of data for longitudinal submodel

Estimation of mixed models including a subject-specific variance which can be time and covariate dependent. In the joint model framework, the package handles left truncation and allows a flexible dependence structure between the competing events and the longitudinal marker. The estimation is performed under the frequentist framework, using the Marquardt-Levenberg algorithm. (Courcoul, Tzourio, Woodward, Barbieri, Jacqmin-Gadda (2023) <arXiv:2306.16785>).

Léonie Courcoul

FlexVarJM

Estimate Joint Models with Subject-Specific Variance

Antoine Barbieri

Hélène Jacqmin-Gadda

data.time function

<dl><dt>data.id</dt>
<dd>A dataframe</dd>
<dt>Time</dt>
<dd>A vector of Time of events</dd>
<dt>formFixed</dt>
<dd>A formula for the fixed effects of the longitudinal submodel</dd>
<dt>formRandom</dt>
<dd>A formula for the random effects of the longitudinal submodel</dd>
<dt>timeVar</dt>
<dd>The name of the column of time in data.id. This variable must appears in data.id</dd></dl>

Arguments

Management of data for longitudinal submodel — data.time

<dl>

<dt>data.id</dt>
<dd>A dataframe</dd>


<dt>Time</dt>
<dd>A vector of Time of events</dd>


<dt>formFixed</dt>
<dd>A formula for the fixed effects of the longitudinal submodel</dd>


<dt>formRandom</dt>
<dd>A formula for the random effects of the longitudinal submodel</dd>


<dt>timeVar</dt>
<dd>The name of the column of time in data.id. This variable must appears in data.id</dd>

</dl>

data.time: Management of data for longitudinal submodel

Description

Usage

Value

Arguments