PoolTestR: Prevalence and Regression for Pool-Tested (Group-Tested) Data

An easy-to-use tool for working with presence/absence tests on 'pooled' or 'grouped' samples. The primary application is for estimating prevalence of a marker in a population based on the results of tests on pooled specimens. This sampling method is often employed in surveillance of rare conditions in humans or animals (e.g. molecular xenomonitoring). The package was initially conceived as an R-based alternative to the molecular xenomonitoring software, 'PoolScreen' <https://sites.uab.edu/statgenetics/software/>. However, it goes further, allowing for estimates of prevalence to be adjusted for hierarchical sampling frames, and perform flexible mixed-effect regression analyses (McLure et al. pre-print <arXiv:2012.05405>). The package is currently in early stages, however more features are planned or in the works: e.g. adjustments for imperfect test specificity/sensitivity, functions for helping with optimal experimental design, and functions for spatial modelling.

Version: 0.1.1
Depends: R (≥ 3.4.0)
Imports: dplyr, methods, Rcpp (≥ 0.12.0), rstan (≥ 2.18.1), rstantools (≥ 2.0.0), brms, stats, lme4, stringr, progress
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.3.0), rstan (≥ 2.18.1), StanHeaders (≥ 2.18.0)
Published: 2021-02-15
Author: Angus McLure ORCID iD [aut, cre]
Maintainer: Angus McLure <angus.mclure at anu.edu.au>
BugReports: https://github.com/AngusMcLure/PoolTestR
License: GPL (≥ 3)
URL: https://github.com/AngusMcLure/PoolTestR
NeedsCompilation: yes
SystemRequirements: GNU make
Language: en-AU
Materials: README NEWS
CRAN checks: PoolTestR results

Documentation:

Reference manual: PoolTestR.pdf

Downloads:

Package source: PoolTestR_0.1.1.tar.gz
Windows binaries: r-devel: PoolTestR_0.1.1.zip, r-release: PoolTestR_0.1.1.zip, r-oldrel: PoolTestR_0.1.1.zip
macOS binaries: r-release (arm64): PoolTestR_0.1.1.tgz, r-release (x86_64): PoolTestR_0.1.1.tgz, r-oldrel: PoolTestR_0.1.1.tgz
Old sources: PoolTestR archive

Linking:

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