Description Usage Arguments Details Value References See Also Examples
‘gtcorr.hierarchical’ calculates the efficiencies of hierarchical group testing procedures for nested and random arrangements, allowing for correlation between units and test error.
1 2 3  gtcorr.hierarchical(n, m = 1, p, sigma = 0, se = 1, sp = 1, arrangement
= c("nested", "random"), model = c("betabinomial", "Madsen",
"MorelNeerchal"), ...)

n 
a numeric vector of pool sizes where 
m 
cluster size. 
p 
probability of a unit testing positive. 
sigma 
pairwise correlation of two units in a cluster. 
se 
sensitivity. The probability that a pool of units tests positive given than at least one unit in that pool is positive 
sp 
specificity. The probability that a pool of units tests negative given that at least one unit in that pool is negative 
arrangement 
how clusters are arranged. Should be ‘nested’ or ‘random’. 
model 
probability model for clusters. Should be ‘betabinomial’, ‘Madsen’, or ‘MorelNeerchal’. 
... 

One of m
, p
, sigma
, se
, or sp
can have
more than one value.
m
should not be greater than n[1]
. For a
‘nested’ arrangement, m
should be divisible by n[s]
or
n[s]
should be divisible by m
for all s
.
See Lendle et. al. 2011 for more information.
n 
number of units per pool at each stage. 
param.grid 
a data frame containing the values of 
arrangement 
arrangement. 
model 
model. 
efficiency 
a vector of efficiencies, one for each row of

Samuel D. Lendle, Michael Hudgens, and Bahjat F. Qaqish, "Group Testing for Case Identification with Correlated Responses" Submitted 2011. Biometrics.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17  ##Plot efficiencies of a Dorfman (2 stage hierarchical) algorithm
##by cluster size and sigma
m < 2^(0:8)
sig.0 < gtcorr.hierarchical(n=256, p=.001, m=m, sigma=0)$efficiency
sig.05 < gtcorr.hierarchical(n=256, p=.001, m=m, sigma=0.05)$efficiency
sig.5 < gtcorr.hierarchical(n=256, p=.001, m=m, sigma=0.5)$efficiency
sig.99 < gtcorr.hierarchical(n=256, p=.001, m=m, sigma=.99)$efficiency
plot(m, sig.99, log="x", type='b', ylab="Efficiency", axes=FALSE)
box()
axis(1, at=m)
axis(2)
lines(m, sig.5, type='b', pch=22)
lines(m, sig.05, type='b', pch=23)
lines(m, sig.0, type='b', pch=24)
legend('bottomleft', c("sigma=0", "sigma=0.05", "sigma=0.5",
"sigma=0.99"), pch=21:24)

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