opt.pool.size: Find the optimal pool size for Optimal Dorfman or Thresholded...
In binGroup: Evaluation and Experimental Design for Binomial Group Testing

Description Usage Arguments Details Value Author(s) References See Also Examples

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

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

`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.

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.

The optimal common pool size for OD or TOD testing.

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

\insertRef

McMahan2012abinGroup

http://chrisbilder.com/grouptesting

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

# 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)