thresh.val.dorf {binGroup} | R Documentation |
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)
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. |
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.
Value
The optimal threshold value for 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
, 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.
## Not run:
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)
## End(Not run)
# 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)