summary.ipooledBin: Summarize ipooledBin or ipooledBinList objects
| summary.ipooledBin | R Documentation |
Summarize ipooledBin or ipooledBinList objects
Description
The functions provide more detail underlying the results from ipooledBin
Usage
## S3 method for class 'ipooledBin'
summary(object, ...)
## S3 method for class 'summary.ipooledBin'
print(x, ...)
## S3 method for class 'summary.ipooledBin'
x[i, j, drop = if (missing(i)) TRUE else length(cols) == 1]
Arguments
object |
an object of class |
x |
an object of class |
... |
for additional arguments |
i,j |
elements to extract or replace. For [ and [[, these are numeric or character or, for [ only, empty or logical. Numeric values are coerced to integer as if by as.integer. |
drop |
logical. If TRUE the result is coerced to the lowest possible dimension. The default is to drop if only one column is left, but not to drop if only one row is left. |
Details
Summaries include, in addition to the original object, as attributes: the number of individuals, number of pools, number of positive pools, sensitivity, and specificity, along the point estimation method used.
Value
The original pooledBin object with additional list elements
scale |
scale of estimates, with default 1 |
... |
future arguments |
and attributes class and call
Author(s)
Brad Biggerstaff
See Also
See also ipooledBin
Examples
# Consider an imaginary example, where pools of size
# 1, 5, 10 and 50 are tested, 5 pools of each size.
# Among the 5 pools with sizes 1 and 5, no pool is positive,
# while among the 5 pools of sizes 10 and 50, 1 and 2 positive
# pools are identified, respectively.
x1 <- c(0,0,1,2)
m1 <- c(1,5,10,50)
n1 <- c(5,5,5,5)
ipooledBin(x=x1, m=m1, n=n1, sens=0.95, spec=0.99)
ipooledBin(x=x1, m=m1, n=n1, sens=0.95, spec=0.99, scale = 1000)
summary(ipooledBin(x=x1, m=m1, n=n1, sens=0.95, spec=0.99, scale=1000))
