## EXAMPLE 1:
## Calculate the surveillance system specificity (i.e., the probability that
## an uninfected population will be correctly identified as negative) if 30
## surveillance units have been tested from a population of 150 using a
## diagnostic test with surveillance unit specificity of 0.90, using a
## cut-point of one or more positives to consider the population positive.
## A specificity of 0.90 means that 9 out of 10 samples from disease-negative
## surveillance units will return a negative result (i.e., one of them will be
## a false positive).
rsu.spp.rs(N = 150, n = 30, c = 1, sp.u = 0.90)
## The surveillance system specificity is 0.03. There is a probability of
## 0.03 that all 30 samples will be negative.
## EXAMPLE 2:
## Now assume we set a cut-point of 6. That is, 6 or more samples have to
## return a positive result for us to declare the population positive:
rsu.spp.rs(N = 150, n = 30, c = 6, sp.u = 0.90)
## The surveillance system specificity is 0.95.
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