{ "_id": "6acf26e3d9de2f3f33fc85a6", "Package": "BLOQ", "Type": "Package", "Version": "0.1-2", "Date": "2025-05-05", "Title": "Methods to Impute and Analyze Data with BLOQ Observations", "Authors@R": "c(\nperson(\"Vahid\",\"Nassiri\", email = \"vahid.nassiri@openanalytics.eu\", role = \"cre\"),\nperson(\"Helen\", \"Barnett\", email= \"h.barnett@lancaster.ac.uk\", role = \"aut\"),\nperson(\"Helena\", \"Geys\", email= \"HGEYS@its.jnj.com\", role = \"aut\"),\nperson(\"Tom\", \"Jacobs\", email= \"TJACOBS1@its.jnj.com\", role = \"aut\"),\nperson(\"Thomas\", \"Jaki\", email= \"t.jaki@lancaster.ac.uk\", role = \"aut\"))", "Maintainer": "Vahid Nassiri ", "Description": "Provides methods for estimating the area under the\nconcentration versus time curve (AUC) and its standard error in\nthe presence of Below the Limit of Quantification (BLOQ)\nobservations. Two approaches are implemented: direct estimation\nusing censored maximum likelihood, and a two-step approach that\nfirst imputes BLOQ values using various methods and then\ncomputes the AUC using the imputed data. Technical details are\ndescribed in Barnett et al. (2020), \"Methods for\nNon-Compartmental Pharmacokinetic Analysis With Observations\nBelow the Limit of Quantification,\" Statistics in\nBiopharmaceutical Research.\n.", "License": "GPL (>= 2)", "Encoding": "UTF-8", "RoxygenNote": "7.3.2", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-14 06:48:08 UTC", "User": "root" }, "Author": "Vahid Nassiri [cre], Helen Barnett [aut], Helena Geys [aut],\nTom Jacobs [aut], Thomas Jaki [aut]", "Repository": "https://vahidnassiri.r-universe.dev", "Date/Publication": "2025-05-05 16:43:09 UTC", "RemoteUrl": "https://github.com/cran/BLOQ", "RemoteRef": "HEAD", "RemoteSha": "95863d89b302ccaa881d4c9297b232fd94c438b7", "_user": "vahidnassiri", "_type": "src", "_file": "BLOQ_0.1-2.tar.gz", "_fileid": "https://r2.ropensci.org/9693c9839bf7b60b4a215907da57d473fdb7186fb3c149c44f5d01fe5b600171", "_filesize": 204137, "_sha256": "9693c9839bf7b60b4a215907da57d473fdb7186fb3c149c44f5d01fe5b600171", "_expires": "2027-01-22T06:53:21.000Z", "_created": 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