DAG.to.MAG.in.pwSEM

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

DAG.to.MAG.in.pwSEM function

<dl><dt>full.DAG</dt>
<dd>The DAG with latent variables, usually produced with the
DAG() function of the ggm package</dd>
<dt>latents</dt>
<dd>A character vector giving the names of the latent variables
in the DAG</dd>
<dt>conditioning.latents</dt>
<dd>A character vector giving the names
of those latents, listed in the "latents" argument, that serve as
conditioning variables for sampling (i.e. selection bias).</dd></dl>

Arguments

Title DAG.to.MAG.in.pwSEM — DAG.to.MAG.in.pwSEM

<dl>

<dt>full.DAG</dt>
<dd>The DAG with latent variables, usually produced with the
DAG() function of the ggm package</dd>


<dt>latents</dt>
<dd>A character vector giving the names of the latent variables
in the DAG</dd>


<dt>conditioning.latents</dt>
<dd>A character vector giving the names
of those latents, listed in the "latents" argument, that serve as
conditioning variables for sampling (i.e. selection bias).</dd>

</dl>

DAG.to.MAG.in.pwSEM: Title DAG.to.MAG.in.pwSEM

Description

Usage

Value

Arguments

Examples