lodi: Limit of Detection Imputation for Single-Pollutant Models

Impute observed values below the limit of detection (LOD) via censored likelihood multiple imputation (CLMI) in single-pollutant models, developed by Boss et al (2019) <doi:10.1097/EDE.0000000000001052>. CLMI handles exposure detection limits that may change throughout the course of exposure assessment. 'lodi' provides functions for imputing and pooling for this method.

Version: 0.9.2
Depends: R (≥ 3.1.0)
Imports: stats, rlang (≥ 0.3.0)
Suggests: testthat, knitr, rmarkdown
Published: 2020-02-07
Author: Jonathan Boss [aut], Alexander Rix [aut, cre]
Maintainer: Alexander Rix <alexrix at umich.edu>
BugReports: https://github.com/umich-cphds/lodi/issues
License: GPL-3
URL: https://github.com/umich-cphds/lodi
NeedsCompilation: no
Materials: README NEWS
In views: MissingData
CRAN checks: lodi results


Reference manual: lodi.pdf
Vignettes: Censored Likelihood Multiple Imputation in R
Package source: lodi_0.9.2.tar.gz
Windows binaries: r-devel: lodi_0.9.2.zip, r-release: lodi_0.9.2.zip, r-oldrel: lodi_0.9.2.zip
macOS binaries: r-release (arm64): lodi_0.9.2.tgz, r-release (x86_64): lodi_0.9.2.tgz, r-oldrel: lodi_0.9.2.tgz
Old sources: lodi archive


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