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.

Version:	1.0.0
Depends:	R (≥ 2.10)
Imports:	dplyr, ggplot2, rlang, stats, methods, scales
Suggests:	INLA, knitr, testthat (≥ 3.0.0), tibble, rmarkdown, spelling
Published:	2024-06-24
DOI:	10.32614/CRAN.package.inlamemi
Author:	Emma Skarstein [cre, aut, cph], Stefanie Muff [aut]
Maintainer:	Emma Skarstein <emma at skarstein.no>
License:	MIT + file LICENSE
URL:	https://emmaskarstein.github.io/inlamemi/, https://github.com/emmaSkarstein/inlamemi
NeedsCompilation:	no
Additional_repositories:	https://inla.r-inla-download.org/R/stable/
Language:	en-US
Citation:	inlamemi citation info
Materials:	README NEWS
CRAN checks:	inlamemi results

Documentation:

Reference manual:	inlamemi.pdf
Vignettes:	Influence of systolic blood pressure on coronary heart disease How are the models structured? How to not use inlamemi Modifying the default plot Multiple variables with measurement error and missingness Survival data with repeated systolic blood pressure measurements Simulated examples

Downloads:

Package source:	inlamemi_1.0.0.tar.gz
Windows binaries:	r-devel: inlamemi_1.0.0.zip, r-release: inlamemi_1.0.0.zip, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): inlamemi_1.0.0.tgz, r-oldrel (x86_64): inlamemi_1.0.0.tgz

Linking:

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