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. Environmental Modelling and Software.
<DOI:10.1016/j.envsoft.2021.105158>). 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.

Predict 10-Year Risk for Atherosclerotic Cardiovascular Disease
c(person(given = "Byron",
family = "Jaeger",
role = c("aut", "cre"),
email = "bcjaeger@uab.edu",
comment = c(ORCID = "0000-0001-7399-2299")))
The 2017 American College of Cardiology and American Heart
Association blood pressure guideline recommends using 10-year predicted
atherosclerotic cardiovascular disease risk to guide the decision to
initiate or intensify antihypertensive medication. The guideline recommends
using the Pooled Cohort risk prediction equations to predict 10-year
atherosclerotic cardiovascular disease risk. This package implements the
original Pooled Cohort risk prediction equations and also incorporates
updated versions based on more contemporary data and statistical methods.
References:
Goff DC, Lloyd-Jones DM, Bennett G, Coady S, D’Agostino RB, Gibbons R,
Greenland P, Lackland DT, Levy D, O’Donnell CJ, and Robinson JG (2014)
<doi:10.1016/j.jacc.2014.03.006>
Yadlowsky S, Hayward RA, Sussman JB, McClelland RL, Min YI, and Basu S (2018)
<doi:10.7326/m17-3011>.