Package: BLOQ 0.1-1

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>).

Authors:Vahid Nassiri [cre], Helen Barnett [aut], Helena Geys [aut], Tom Jacobs [aut], Thomas Jaki [aut]

BLOQ_0.1-1.tar.gz
BLOQ_0.1-1.zip(r-4.5)BLOQ_0.1-1.zip(r-4.4)BLOQ_0.1-1.zip(r-4.3)
BLOQ_0.1-1.tgz(r-4.4-any)BLOQ_0.1-1.tgz(r-4.3-any)
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BLOQ.pdf |BLOQ.html
BLOQ/json (API)

# Install 'BLOQ' in R:
install.packages('BLOQ', repos = c('https://vahidnassiri.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.11 score 13 scripts 229 downloads 12 exports 8 dependencies

Last updated 4 years agofrom:bacaf5984d. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 18 2024
R-4.5-winOKNov 18 2024
R-4.5-linuxOKNov 18 2024
R-4.4-winOKNov 18 2024
R-4.4-macOKNov 18 2024
R-4.3-winOKNov 18 2024
R-4.3-macOKNov 18 2024

Exports:estimateAUCandStdErrestimateAUCwithCMLperTimePointestimateAUCwithFullCMLestimateAUCwithMVNCMLestimateAUCwithPairwiseCMLimputeBLOQimputeCMLimputeConstantimputeKernelDensityEstimationimputeROSsimulateBealModelFixedEffectssimulateBealModelMixedEffects

Dependencies:digestgenericslatticemaxLikmiscToolsmvtnormsandwichzoo