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lpmec  

Measurement Error Analysis and Correction Under Identification Restrictions
View on CRAN: Click here


Download and install lpmec package within the R console
Install from CRAN:
install.packages("lpmec")

Install from Github:
library("remotes")
install_github("cran/lpmec")

Install by package version:
library("remotes")
install_version("lpmec", "1.1.4")



Attach the package and use:
library("lpmec")
Maintained by
Connor Jerzak
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-02-09
Latest Update: 2026-02-09
Description:
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>.
How to cite:
Connor Jerzak (2026). lpmec: Measurement Error Analysis and Correction Under Identification Restrictions. R package version 1.1.4, https://cran.r-project.org/web/packages/lpmec. Accessed 24 Oct. 2026.
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Complete documentation for lpmec
Functions, R codes and Examples using the lpmec R package
Full lpmec package functions and examples
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