Package: lpmec
Title: Measurement Error Analysis and Correction Under Identification
        Restrictions
Version: 1.1.4
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) <doi:10.48550/arXiv.2507.22218>.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: false
Maintainer: Connor Jerzak <connor.jerzak@gmail.com>
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
RoxygenNote: 7.3.3
URL: https://github.com/cjerzak/lpmec-software
BugReports: https://github.com/cjerzak/lpmec-software/issues
NeedsCompilation: no
Packaged: 2026-02-05 17:34:00 UTC; cjerzak
Repository: CRAN
Date/Publication: 2026-02-09 13:30:14 UTC
