binGroup (version 2.2-3)

thresh.val.dorf: Find the optimal threshold value for Thresholded Optimal Dorfman testing

Description

Find the optimal threshold value for Thresholded Optimal Dorfman (TOD) testing.

Usage

thresh.val.dorf(p, psz, se = 1, sp = 1)

Value

The optimal threshold value for TOD testing.

Arguments

p

a vector of each individual's probability of infection.

psz

the initial pool size.

se

the sensitivity of the diagnostic test.

sp

the specificity of the diagnostic test.

Author

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

Details

This function finds the optimal threshold value for TOD testing for situations where the threshold value is not specified. See McMahan et al. (2012) for additional details on the implementation of TOD testing.

References

McMahan2012abinGroup

See Also

http://chrisbilder.com/grouptesting/

Other Informative Dorfman functions: accuracy.dorf(), characteristics.pool(), inf.dorf.measures(), opt.info.dorf(), opt.pool.size(), pool.specific.dorf()

Examples

# This example takes approximately 4 seconds to run. 
# Estimated running time was calculated using a 
#   computer with 16 GB of RAM and one core of an 
#   Intel i7-6500U processor.
if (FALSE) {
set.seed(3154)
p.vec <- p.vec.func(p=0.10, alpha=0.5, grp.sz=1000)
thresh.val.dorf(p=p.vec, psz=10, se=0.95, sp=0.95)}

# 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.
p.vec <- p.vec.func(p=0.15, alpha=2, grp.sz=100)
thresh.val.dorf(p=p.vec, psz=10, se=0.95, sp=0.95)