PVBcorrect: Partial Verification Bias Correction for Diagnostic Accuracy

Performs partial verification bias (PVB) correction for binary diagnostic tests, where PVB arises from selective patient verification in diagnostic accuracy studies. Supports correction of important accuracy measures – sensitivity, specificity, positive predictive values and negative predictive value – under missing-at-random and missing-not-at-random missing data mechanisms. Available methods and references are "Begg and Greenes' methods" in Alonzo & Pepe (2005) <doi:10.1111/j.1467-9876.2005.00477.x> and deGroot et al. (2011) <doi:10.1016/j.annepidem.2010.10.004>; "Multiple imputation" in Harel & Zhou (2006) <doi:10.1002/sim.2494>, "EM-based logistic regression" in Kosinski & Barnhart (2003) <doi:10.1111/1541-0420.00019>; "Inverse probability weighting" in Alonzo & Pepe (2005) <doi:10.1111/j.1467-9876.2005.00477.x>; "Inverse probability bootstrap sampling" in Nahorniak et al. (2015) <doi:10.1371/journal.pone.0131765> and Arifin & Yusof (2022) <doi:10.3390/diagnostics12112839>; "Scaled inverse probability resampling methods" in Arifin & Yusof (2025) <doi:10.1371/journal.pone.0321440>.

Version:	0.3.1
Depends:	R (≥ 2.10)
Imports:	boot, mice
Suggests:	testthat (≥ 3.0.0)
Published:	2025-10-08
DOI:	10.32614/CRAN.package.PVBcorrect
Author:	Wan Nor Arifin [aut, cre, cph]
Maintainer:	Wan Nor Arifin <wnarifin at gmail.com>
License:	MIT + file LICENSE
URL:	https://github.com/wnarifin/PVBcorrect/
NeedsCompilation:	no
Materials:	README, NEWS
CRAN checks:	PVBcorrect results

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