subset.lvm

measurement

Extract measurement models or user-specified subset of model

models

regression

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

Brice Ozenne

Thomas Gerds

subset.lvm function

<dl><dt>x</dt>
<dd><code>lvm</code>-object.</dd>
<dt>vars</dt>
<dd>Character vector or formula specifying variables to include in
subset.</dd>
<dt>...</dt>
<dd>Additional arguments to be passed to the low level functions</dd></dl>

Arguments

Author

Extract subset of latent variable model — subset.lvm

<dl>

<dt>x</dt>
<dd><code>lvm</code>-object.</dd>


<dt>vars</dt>
<dd>Character vector or formula specifying variables to include in
subset.</dd>


<dt>...</dt>
<dd>Additional arguments to be passed to the low level functions</dd>

</dl>

subset.lvm: Extract subset of latent variable model

Description

Usage

Value

Arguments

Author

Examples