plot.lpmec_onerun

Creates a scatter plot comparing the two split-half latent variable estimates.

Implements methods for analyzing latent variable models with measurement
error correction, including Item Response Theory (IRT) models. Provides tools for
various correction methods such as Bayesian Markov Chain Monte Carlo (MCMC),
over-imputation, bootstrapping for robust standard errors, Ordinary Least Squares
(OLS), and Instrumental Variables (IV) based approaches. Supports flexible
specification of observable indicators and groupings for latent variable analyses
in social sciences and other fields. Methods are described in a working paper
(2025) <doi:10.48550/arXiv.2507.22218>.

Connor Jerzak

lpmec

Measurement Error Analysis and Correction Under Identification
Restrictions

Stephen Jessee

plot.lpmec_onerun function

<dl><dt>x</dt>
<dd>An object of class <code>lpmec_onerun</code> returned by <code>lpmec_onerun</code>.</dd>
<dt>...</dt>
<dd>Additional arguments passed to <code><a href="/link/plot?package=lpmec&version=1.1.4" data-mini-rdoc="lpmec::plot">plot</a></code>.</dd></dl>

Arguments

Plot method for lpmec_onerun objects — plot.lpmec_onerun

<dl>

<dt>x</dt>
<dd>An object of class <code>lpmec_onerun</code> returned by <code>lpmec_onerun</code>.</dd>


<dt>...</dt>
<dd>Additional arguments passed to <code><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></code>.</dd>

</dl>

plot.lpmec_onerun: Plot method for lpmec_onerun objects

Description

Usage

Value

Arguments

See Also