inlamemi: Missing Data and Measurement Error Modelling in INLA

Facilitates fitting measurement error and missing data imputation models using integrated nested Laplace approximations, according to the method described in Skarstein, Martino and Muff (2023) <doi:10.1002/bimj.202300078>. See Skarstein and Muff (2024) <doi:10.48550/arXiv.2406.08172> for details on using the package.

README.md How are the models structured? How to avoid using inlamemi Influence of systolic blood pressure on coronary heart disease Modifying the default plot Multiple variables with measurement error and missingness Simulated examples Survival model with repeated systolic blood pressure measurements

Vignettes Man pages API and functions Files

Package details
Author	Emma Skarstein [cre, aut, cph] (<https://orcid.org/0000-0002-6347-855X>), Stefanie Muff [aut] (<https://orcid.org/0000-0002-8425-0757>)
Maintainer	Emma Skarstein <emma@skarstein.no>
License	MIT + file LICENSE
Version	1.1.0
URL	https://emmaskarstein.github.io/inlamemi/ https://github.com/emmaSkarstein/inlamemi
Package repository	View on CRAN
Installation	Install the latest version of this package by entering the following in R: `install.packages("inlamemi")`