3 papers
stat.ME2024
Bayesian models for missing and misclassified variables using integrated nested Laplace approximations
Emma Skarstein, Leonardo Soares Bastos, Håvard Rue +1
Misclassified variables used in regression models, either as a covariate or as the response, may lead to biased estimators and incorrect inference. Even though Bayesian models to a…
stat.ME2024
inlamemi: An R package for missing data imputation and measurement error modelling using INLA
Emma Skarstein, Stefanie Muff
Measurement error and missing data in variables used in statistical models are common, and can at worst lead to serious biases in analyses if they are ignored. Yet, these problems…
stat.ME2023
A joint Bayesian framework for missing data and measurement error using integrated nested Laplace approximations
Emma Sofie Skarstein, Sara Martino, Stefanie Muff
Measurement error (ME) and missing values in covariates are often unavoidable in disciplines that deal with data, and both problems have separately received considerable attention…