nested_data

Empirical example with nesting structure, a binomial variable, and
3-level nesting structure.

datasets

Conduct dsep tests (piecewise SEM) of a directed, or mixed, acyclic graph
without latent variables (but possibly with implicitly marginalized or
conditioned latent variables that create dependent errors) based on
linear, generalized linear, or additive modelswith or without a
nesting structure for the data. Also included are functions to do desp tests
step-by-step,exploratory path analysis, and Monte Carlo X2 probabilities.
This package accompanies Shipley, B, (2026).Cause and Correlation in Biology:
A User's Guide to Path Analysis, StructuralEquations and
Causal Inference (3rd edition).  Cambridge University Press.

Bill Shipley

pwSEM

Piecewise Structural Equation Modelling

nested_data function

<div class="section" id="-nested-data-">
<h3>'nested_data'</h3>
A data frame with 1309 rows and 8 columns:<dl>
<dt>year</dt>
<dd>Year observation is collected</dd><dt>nest</dt>
<dd>Nest in which the observation is collected</dd><dt>ind</dt>
<dd>the individual within a given nest</dd><dt>XR</dt>
<dd>A binary variable</dd><dt>XM</dt>
<dd>A Gaussian variable</dd><dt>XH</dt>
<dd>A Gaussian variable</dd><dt>HP</dt>
<dd>A Guassian variable</dd><dt>XF</dt>
<dd>A Gaussian variable</dd>
</dl></div>

Format

nested_data: — nested_data

<div class='section' id='-nested-data-'>
<h3>'nested_data'</h3>


A data frame with 1309 rows and 8 columns:<dl>
<dt>year</dt>
<dd>Year observation is collected</dd>

<dt>nest</dt>
<dd>Nest in which the observation is collected</dd>

<dt>ind</dt>
<dd>the individual within a given nest</dd>

<dt>XR</dt>
<dd>A binary variable</dd>

<dt>XM</dt>
<dd>A Gaussian variable</dd>

<dt>XH</dt>
<dd>A Gaussian variable</dd>

<dt>HP</dt>
<dd>A Guassian variable</dd>

<dt>XF</dt>
<dd>A Gaussian variable</dd>


</dl>

</div>

nested_data: nested_data:

Description

Usage

Arguments

Format

'nested_data'