lpmec: Measurement Error Analysis and Correction Under Identification Restrictions
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