opt.pool.size {binGroup}

Find the optimal pool size for Optimal Dorfman or Thresholded Optimal Dorfman

Description

Find the optimal common pool size for Optimal Dorfman (OD) or Thresholded Optimal Dorfman (TOD) testing.

Usage

opt.pool.size(p, max.p, se = 1, sp = 1)

Arguments

p

a vector of each individual's probability of infection.

max.p

the maximum allowable pool size.

se

the sensitivity of the diagnostic test.

sp

the specificity of the diagnostic test.

Details

This function finds the optimal common pool size for OD or TOD testing. Using OD testing, all individuals are tested using an optimal common pool size. Using TOD testing, individuals are partitioned into low-risk and high-risk groups, and all low-risk individuals are tested using an optimal common pool size. See McMahan et al. (2012) for additional details on the implementation of OD or TOD testing.

Value

The optimal common pool size for OD or TOD testing.

Author(s)

This function was originally written by Christopher S. McMahan for McMahan et al. (2012). The function was obtained from http://chrisbilder.com/grouptesting.

References

McMahan, C., Tebbs, J., Bilder, C. (2012). “Informative Dorfman Screening.” Biometrics, 68(1), 287–296. ISSN 0006341X, doi: 10.1111/j.1541-0420.2011.01644.x.

See Also

http://chrisbilder.com/grouptesting

Other Informative Dorfman functions: accuracy.dorf, characteristics.pool, inf.dorf.measures, opt.info.dorf, pool.specific.dorf, thresh.val.dorf

Examples

# This example takes less than 1 second to run.
# Estimated running time was calculated using a 
#   computer with 16 GB of RAM and one core of an 
#   Intel i7-6500U processor.
set.seed(8135)
p.vec <- p.vec.func(p=0.02, alpha=1, grp.sz=10)
opt.pool.size(p=p.vec, max.p=3, se=0.95, sp=0.95)