complete_visits

Expand long-format data to all subject and visit combinations

A general implementation of Structural Equation Models
with latent variables (MLE, 2SLS, and composite likelihood
estimators) with both continuous, censored, and ordinal
outcomes (Holst and Budtz-Joergensen (2013) <doi:10.1007/s00180-012-0344-y>).
Mixture latent variable models and non-linear latent variable models
(Holst and Budtz-Joergensen (2020) <doi:10.1093/biostatistics/kxy082>).
The package also provides methods for graph exploration (d-separation,
back-door criterion), simulation of general non-linear latent variable
models, and estimation of influence functions for a broad range of
statistical models.

Klaus Holst

lava

Latent Variable Models

Klaus K. Holst

Benedikt Sommer

Brice Ozenne

Thomas Gerds

complete_visits function

<dl><dt>data</dt>
<dd>(data.frame) data in long format</dd>
<dt>id</dt>
<dd>(character) name of the subject variable</dd>
<dt>time</dt>
<dd>(character) name of the visit variable. In the returned data
this variable is a factor with levels <code>levels</code>.</dd>
<dt>response</dt>
<dd>(character) optional name of the response variable which is
set to <code>NA</code> in added rows</dd>
<dt>levels</dt>
<dd>(vector) visit levels. Defaults to the levels of the visit
variable if it is a factor, and otherwise its sorted unique values.</dd></dl>

Arguments

Expand long-format data — complete_visits

<dl>

<dt>data</dt>
<dd>(data.frame) data in long format</dd>


<dt>id</dt>
<dd>(character) name of the subject variable</dd>


<dt>time</dt>
<dd>(character) name of the visit variable. In the returned data
this variable is a factor with levels <code>levels</code>.</dd>


<dt>response</dt>
<dd>(character) optional name of the response variable which is
set to <code>NA</code> in added rows</dd>


<dt>levels</dt>
<dd>(vector) visit levels. Defaults to the levels of the visit
variable if it is a factor, and otherwise its sorted unique values.</dd>

</dl>

complete_visits: Expand long-format data

Description

Usage

Value

Arguments

Details

Examples