estimate.formula

Fit a GLM model specified by a formula and apply estimate.default
for robust inference.

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

estimate.formula function

<dl><dt>x</dt>
<dd>formula specifying the model</dd>
<dt>data</dt>
<dd>data.frame</dd>
<dt>weights</dt>
<dd>optional weights</dd>
<dt>family</dt>
<dd>GLM family (default <code>gaussian</code>)</dd>
<dt>...</dt>
<dd>Additional arguments to estimate.default</dd>
<dt>model</dt>
<dd>character string specifying the model type (default <code>"glm"</code>)</dd>
<dt>lvm</dt>
<dd>logical, if TRUE use <code>estimate.lvm</code> instead</dd></dl>

Arguments

Estimate method for formulas — estimate.formula

<dl>

<dt>x</dt>
<dd>formula specifying the model</dd>


<dt>data</dt>
<dd>data.frame</dd>


<dt>weights</dt>
<dd>optional weights</dd>


<dt>family</dt>
<dd>GLM family (default <code>gaussian</code>)</dd>


<dt>...</dt>
<dd>Additional arguments to estimate.default</dd>


<dt>model</dt>
<dd>character string specifying the model type (default <code>"glm"</code>)</dd>


<dt>lvm</dt>
<dd>logical, if TRUE use <code>estimate.lvm</code> instead</dd>

</dl>

estimate.formula: Estimate method for formulas

Description

Usage

Value

Arguments