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Calibrates population-level cause-specific mortality fractions (CSMFs) that are derived using computer-coded verbal autopsy (CCVA) algorithms. Leveraging the data collected in the Child Health and Mortality Prevention Surveillance (CHAMPS;<https://champshealth.org/>) project, the package stores misclassification matrix estimates of three CCVA algorithms (EAVA, InSilicoVA, and InterVA) and two age groups (neonates aged 0-27 days, and children aged 1-59 months) across countries (specific estimates for Bangladesh, Ethiopia, Kenya, Mali, Mozambique, Sierra Leone, and South Africa, and a combined estimate for all other countries), enabling global calibration. These estimates are obtained using the framework proposed in Pramanik et al. (2025;<doi:10.1214/24-AOAS2006>) and are analyzed in Pramanik et al. (2026;<doi:10.1136/bmjgh-2025-021747>). Given VA-only data for an age group, CCVA algorithm, and country, the package utilizes the corresponding misclassification matrix estimate in the modular VA-Calibration framework (Pramanik et al.,2025;<doi:10.1214/24-AOAS2006>) and produces calibrated estimates of CSMFs. The package also supports ensemble calibration to accommodate multiple algorithms. More generally, this allows calibration of population-level prevalence derived from single-class predictions of discrete classifiers. For this, users need to provide fixed or uncertainty-quantified misclassification matrices. This work is supported by the Eunice Kennedy Shriver National Institute of Child Health K99 NIH Pathway to Independence Award (1K99HD114884-01A1), the Bill and Melinda Gates Foundation (INV-034842), and the Johns Hopkins Data Science and AI Institute.
| Version: | 2.2 |
| Depends: | R (≥ 3.5) |
| Imports: | rstan, openVA, parallel, ggplot2, patchwork, reshape2, LaplacesDemon, MASS |
| Suggests: | knitr, rmarkdown |
| Published: | 2026-03-20 |
| DOI: | 10.32614/CRAN.package.vacalibration |
| Author: | Sandipan Pramanik |
| Maintainer: | Sandipan Pramanik <sandy.pramanik at gmail.com> |
| BugReports: | https://github.com/sandy-pramanik/vacalibration/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/sandy-pramanik/vacalibration |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | vacalibration results |
| Reference manual: | vacalibration.html , vacalibration.pdf |
| Vignettes: |
Intro to vacalibration (source, R code) |
| Package source: | vacalibration_2.2.tar.gz |
| Windows binaries: | r-devel: vacalibration_2.2.zip, r-release: vacalibration_2.2.zip, r-oldrel: vacalibration_2.2.zip |
| macOS binaries: | r-release (arm64): vacalibration_2.2.tgz, r-oldrel (arm64): vacalibration_2.2.tgz, r-release (x86_64): vacalibration_2.2.tgz, r-oldrel (x86_64): vacalibration_2.2.tgz |
| Old sources: | vacalibration archive |
| Reverse suggests: | openVA |
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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.
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