lpmec: Measurement Error Analysis and Correction Under Identification Restrictions

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Authors: Connor Jerzak, Stephen A. Jessee
Cited by: 0
References: 1

Abstract

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) .

Fields of Study & Subjects

Psychometric Methodologies and Testing Statistical Methods and Bayesian Inference Survey Sampling and Estimation Techniques

Publication details

Publication date
9 February 2026
Language
EN
Document type
Dataset