BLOQ: Impute and Analyze Data with Observations Below the Limit of Quantification

Methods for non-compartmental pharmacokinetic analysis with observations below the limit of quantification (BLOQ) are implemented as described in Barnett, Helen Yvette. "Optimizing pharmacokinetic studies utilizing microsampling." PhD diss., Lancaster University, 2017. (available online: <http://eprints.lancs.ac.uk/89163/1/2017barnettphd.pdf>). It includes estimating the area under the concentrations versus time curve (AUC) and its standard error using two approaches: 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.

Version: 0.1-0
Imports: maxLik, mvnmle, mvtnorm
Suggests: testthat
Published: 2018-08-13
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
CRAN checks: BLOQ results

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Reference manual: BLOQ.pdf
Package source: BLOQ_0.1-0.tar.gz
Windows binaries: r-devel: BLOQ_0.1-0.zip, r-release: BLOQ_0.1-0.zip, r-oldrel: BLOQ_0.1-0.zip
OS X binaries: r-release: BLOQ_0.1-0.tgz, r-oldrel: BLOQ_0.1-0.tgz

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