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>).

Getting started

Package details

AuthorVahid Nassiri [cre], Helen Barnett [aut], Helena Geys [aut], Tom Jacobs [aut], Thomas Jaki [aut]
MaintainerVahid Nassiri <vahid.nassiri@openanalytics.eu>
LicenseGPL (>= 2)
Version0.1-1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("BLOQ")

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BLOQ documentation built on July 1, 2020, 11:37 p.m.