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:	1.1.0
Depends:	R (≥ 2.10)
Imports:	dplyr, ggplot2, rlang, stats, methods, scales
Suggests:	INLA, knitr, testthat (≥ 3.0.0), tibble, rmarkdown, spelling
Published:	2024-10-31
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:	How to avoid using inlamemi (source) Influence of systolic blood pressure on coronary heart disease (source) Modifying the default plot (source) Multiple variables with measurement error and missingness (source) Survival model with repeated systolic blood pressure measurements (source) Simulated examples (source) How are the models structured? (source)

Downloads:

Package source:	inlamemi_1.1.0.tar.gz
Windows binaries:	r-devel: inlamemi_1.1.0.zip, r-release: inlamemi_1.1.0.zip, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): inlamemi_1.1.0.tgz, r-oldrel (x86_64): inlamemi_1.1.0.tgz
Old sources:	inlamemi archive

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