Accuracy measures for informative Dorfman testing
Calculate the accuracy measures for each individual in a pool used with informative Dorfman testing.
accuracy.dorf(p, se, sp)
p |
a vector of each individual's probability of infection. |
se |
the sensitivity of the diagnostic test. |
sp |
the specificity of the diagnostic test. |
This function calculates the pooling sensitivity, pooling specificity, pooling positive predictive value, and pooling negative predictive value for each individual belonging to a pool of size greater than or equal to one used with informative Dorfman testing. Calculations of these measures are done using the equations presented in McMahan et al. (2012).
a list containing:
PSe |
a vector containing each individual's pooling sensitivity. |
PSp |
a vector containing each individual's pooling specificity. |
PPV |
a vector containing each individual's pooling positive predictive value. |
NPV |
a vector containing each individual's pooling negative predictive value. |
This function was originally written by Christopher S. McMahan for McMahan et al. (2012). The function was obtained from http://chrisbilder.com/grouptesting.
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.
Other Informative Dorfman functions: characteristics.pool,
inf.dorf.measures,
opt.info.dorf, opt.pool.size,
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) accuracy.dorf(p=p.vec[1:3], se=0.90, sp=0.90)
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