| summary.opChar {binGroup2} | R Documentation |
Summary method for operating characteristics results
Description
Produce a summary list for objects of class
"opChar" returned by operatingCharacteristics1
(opChar1) or operatingCharacteristics2
(opChar2).
Usage
## S3 method for class 'opChar'
summary(object, ...)
Arguments
object |
an object of class "opChar", providing the calculated operating characteristics for a group testing algorithm. |
... |
currently not used. |
Details
This function produces a summary list for objects of
class "opChar" returned by operatingCharacteristics1
(opChar1) or operatingCharacteristics2
(opChar2). It formats the testing configuration, expected number
of tests, expected number of tests per individual, and accuracy measures.
The Configuration component of the result gives the testing configuration, which may include the group sizes for each stage of a hierarchical testing algorithm or the row/column size and array size for an array testing algorithm. The Tests component of the result gives the expected number of tests and the expected number of tests per individual for the algorithm.
The Accuracy component gives the individual accuracy measures for
each individual in object and the overall accuracy measures for the
algorithm. Accuracy measures included are the pooling sensitivity, pooling
specificity, pooling positive predictive value, and pooling negative
predictive value. The overall accuracy measures displayed are weighted
averages of the corresponding individual accuracy measures for all
individuals in the algorithm. Expressions for these averages are provided
in the Supplementary Material for Hitt et al. (2019). For more information,
see the Details' section for the operatingCharacteristics1
(opChar1) or operatingCharacteristics2 (opChar2)
function.
Value
summary.opChar returns an object of class "summary.opChar", a list containing:
Algorithm |
character string specifying the name of the group testing algorithm. |
Configuration |
matrix detailing the configuration from object. For hierarchical testing, this includes the group sizes for each stage of testing. For array testing, this includes the array dimension (row/column size) and the array size (the total number of individuals in the array). |
Tests |
matrix detailing the expected number of tests and expected number of tests per individual from object |
.
Accuracy |
a list containing:
|
Author(s)
Brianna D. Hitt
See Also
operatingCharacteristics1 (opChar1) and
operatingCharacteristics2 (opChar2) for creating
an object of class "opChar".
Examples
# Calculate the operating characteristics for
# non-informative four-stage hierarchical testing.
config.mat <- matrix(data = c(rep(1, 24), rep(1, 16),
rep(2, 8), rep(1, 8),
rep(2, 8), rep(3, 4),
rep(4, 2), rep(5, 2), 1:24),
nrow = 4, ncol = 24, byrow = TRUE)
calc1 <- opChar1(algorithm = "D4", p = 0.01,
Se = 0.99, Sp = 0.99,
hier.config = config.mat,
a = c(1, 9, 17, 21, 23))
summary(calc1)
# Calculate the operating characteristics for
# informative array testing without master pooling.
calc2 <- opChar1(algorithm = "IA2", p = 0.025, alpha = 0.5,
Se = 0.95, Sp = 0.99, rowcol.sz = 10)
summary(calc2)
# Calculate the operating characteristics for
# informative two-stage hierarchical testing
# with a multiplex assay for two diseases.
config.mat <- matrix(data = c(rep(1, 5), rep(2, 4),
1, 1:10),
nrow = 2, ncol = 10, byrow = TRUE)
Se <- matrix(data = c(rep(0.95, 2), rep(0.99, 2)),
nrow = 2, ncol = 2, byrow = FALSE)
Sp <- matrix(data = c(rep(0.96, 2), rep(0.98, 2)),
nrow = 2, ncol = 2, byrow = FALSE)
calc3 <- opChar2(algorithm = "ID2",
alpha = c(18.25, 0.75, 0.75, 0.25),
Se = Se, Sp = Sp,
hier.config = config.mat)
summary(calc3)
# Calculate the operating characteristics for
# non-informative array testing with master pooling
# with a multiplex assay for two diseases.
calc4 <- opChar2(algorithm = "A2M",
p.vec = c(0.92, 0.05, 0.02, 0.01),
Se = rep(0.95, 2), Sp = rep(0.99, 2),
rowcol.sz = 8)
summary(calc4)