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.AP2023
The Point Process Framework for Integrated Modelling of Biodiversity Data
Kwaku Peprah Adjei, Philip Mostert, Jorge Sicacha Parada +2
The quantity and types of biodiversity data being collected have increased in recent years. If we are to model and monitor biodiversity effectively, we need to respect how differen…