Package: lpmec Title: Measurement Error Analysis and Correction Under Identification Restrictions Version: 1.3.0 Author: Connor Jerzak [aut, cre], Stephen Jessee [aut] Authors@R: c( person("Connor", "Jerzak", email = "connor.jerzak@gmail.com", role = c("aut", "cre")), person("Stephen", "Jessee", email = "sjessee@austin.utexas.edu", role = c("aut")) ) 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) . Also includes corrections for panel fixed-effects and differencing designs, latent treatment-effect moderators in randomized experiments, and multi-measure reliability bounds. Depends: R (>= 3.5.0) License: GPL-3 Encoding: UTF-8 LazyData: false Maintainer: Connor Jerzak Imports: reticulate, stats, sensemakr, pscl, AER, sandwich, mvtnorm, Amelia, emIRT, gtools Suggests: testthat (>= 3.0.0), knitr, rmarkdown SystemRequirements: Python (>= 3.10) with jax, numpy, numpyro (optional; for NumPyro backend via reticulate) VignetteBuilder: knitr Config/testthat/edition: 3 URL: https://github.com/cjerzak/lpmec-software BugReports: https://github.com/cjerzak/lpmec-software/issues Config/roxygen2/version: 8.0.0 Config/pak/sysreqs: cmake make libicu-dev libpng-dev python3 Repository: https://cjerzak.r-universe.dev Date/Publication: 2026-10-16 23:09:02 UTC RemoteUrl: https://github.com/cjerzak/lpmec-software RemoteRef: HEAD RemoteSha: 21d2b1ec502c8c587f704a7aee0eb442c18a818f RemoteSubdir: lpmec NeedsCompilation: no Packaged: 2026-10-16 23:49:47 UTC; root