The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
PVBcorrect
The package contains a number of functions to perform partial
verification bias (PVB) correction for estimates of accuracy measures in
diagnostic accuracy studies. The available methods are:
- Begg and Greenes’ method (as extended by Alonzo & Pepe,
2005)
- Begg and Greenes’ method 1 and 2 (with PPV and NPV as extended by
deGroot et al, 2011)
- EM-based logistic regression method (Kosinski & Barnhart,
2003)
- Inverse Probability Weighting (IPW) method (Alonzo & Pepe,
2005)
- Inverse Probability Bootstrap (IPB) sampling method (Arifin &
Yusof, 2022; Nahorniak et al., 2015)
- Multiple imputation method by logistic regression (Harel & Zhou,
2006)
- Scaled Inverse Probability Resampling methods (Arifin & Yusof,
2023; Arifin & Yusof, 2025)
Prerequisites
The required packages are:
install.packages("boot", "mice")
Installation
Install PVBcorrect package from CRAN:
install.packages("PVBcorrect")
or from GitHub:
install.packages("devtools")
devtools::install_github("wnarifin/PVBcorrect")
Usage, news and updates
Please view Wiki page:
https://github.com/wnarifin/PVBcorrect/wiki
References
- Alonzo, T. A., & Pepe, M. S. (2005). Assessing accuracy of a
continuous screening test in the presence of verification bias. Journal
of the Royal Statistical Society: Series C (Applied Statistics), 54(1),
173–190.
- Arifin, W. N., & Yusof, U. K. (2025). Partial Verification Bias
Correction Using Scaled Inverse Probability Resampling for Binary
Diagnostic Tests. medRxiv.
https://doi.org/10.1101/2025.03.09.25323631
- Arifin, W. N. (2023). Partial verification bias correction in
diagnostic accuracy studies using propensity score-based methods (PhD
thesis, Universiti Sains Malaysia).
https://erepo.usm.my/handle/123456789/19184
- Arifin, W. N., & Yusof, U. K. (2022a). Correcting for partial
verification bias in diagnostic accuracy studies: a tutorial using R.
Statistics in Medicine, 41(9), 1709–1727.
- Arifin, W. N., & Yusof, U. K. (2022b). Partial Verification Bias
Correction Using Inverse Probability Bootstrap Sampling for Binary
Diagnostic Tests. Diagnostics, 12, 2839.
- Begg, C. B., & Greenes, R. A. (1983). Assessment of diagnostic
tests when disease verification is subject to selection bias.
Biometrics, 207–215.
- de Groot, J. A. H., Janssen, K. J. M., Zwinderman, A. H., Bossuyt,
P. M. M., Reitsma, J. B., & Moons, K. G. M. (2011). Correcting for
partial verification bias: a comparison of methods. Annals of
Epidemiology, 21(2), 139–148.
- Harel, O., & Zhou, X.-H. (2006). Multiple imputation for
correcting verification bias. Statistics in Medicine, 25(22),
3769–3786.
- He, H., & McDermott, M. P. (2012). A robust method using
propensity score stratification for correcting verification bias for
binary tests. Biostatistics, 13(1), 32–47.
- Kosinski, A. S., & Barnhart, H. X. (2003). Accounting for
nonignorable verification bias in assessment of diagnostic tests.
Biometrics, 59(1), 163–171.
- Nahorniak, M., Larsen, D. P., Volk, C., & Jordan, C. E. (2015).
Using Inverse Probability Bootstrap Sampling to Eliminate Sample Induced
Bias in Model Based Analysis of Unequal Probability Samples. Plos One,
10(6), e0131765. https://doi.org/10.1371/journal.pone.0131765
- Zhou, X.-H. (1993). Maximum likelihood estimators of sensitivity and
specificity corrected for verification bias. Communications in
Statistics-Theory and Methods, 22(11), 3177–3198.
- Zhou, X.-H. (1994). Effect of verification bias on positive and
negative predictive values. Statistics in Medicine, 13(17),
1737–1745.
- Zhou, X.-H., Obuchowski, N. A., & McClish, D. K. (2011).
Statistical Methods in Diagnostic Medicine (2nd ed.). John Wiley &
Sons.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.