BLOQ: Impute and Analyze Data with BLOQ Observations

It includes estimating the area under the concentrations versus time curve (AUC) and its standard error for data with Below the Limit of Quantification (BLOQ) observations. Two approaches are implemented: direct estimation using censored maximum likelihood, also by first imputing the BLOQ's using various methods, then compute AUC and its standard error using imputed data. Technical details can found in Barnett, Helen Yvette, Helena Geys, Tom Jacobs, and Thomas Jaki. "Methods for Non-Compartmental Pharmacokinetic Analysis With Observations Below the Limit of Quantification." Statistics in Biopharmaceutical Research (2020): 1-12. (available online: <https://www.tandfonline.com/doi/full/10.1080/19466315.2019.1701546>).

Version: 0.1-1
Imports: maxLik, mvtnorm
Suggests: testthat
Published: 2020-06-07
Author: Vahid Nassiri [cre], Helen Barnett [aut], Helena Geys [aut], Tom Jacobs [aut], Thomas Jaki [aut]
Maintainer: Vahid Nassiri <vahid.nassiri at openanalytics.eu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: NEWS
CRAN checks: BLOQ results

Documentation:

Reference manual: BLOQ.pdf

Downloads:

Package source: BLOQ_0.1-1.tar.gz
Windows binaries: r-devel: BLOQ_0.1-1.zip, r-release: BLOQ_0.1-1.zip, r-oldrel: BLOQ_0.1-1.zip
macOS binaries: r-release (arm64): BLOQ_0.1-1.tgz, r-release (x86_64): BLOQ_0.1-1.tgz, r-oldrel: BLOQ_0.1-1.tgz
Old sources: BLOQ archive

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