In a previous post, I gave a cursory overview of how prior information about covariate measurement error can reduce bias in linear regression. In the comments, Rasmus Bååth asked about estimation in the absence of strong priors. Here, I’ll describe a Bayesian approach for estimation and correction for covariate measurement error using a latent-variable based errors-in-variables...