bgtvs: Confidence Interval for One Proportion in Group Testing with...

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

Calculates confidence intervals for a single proportion in binomial group testing if groups of different size are evaluated

Usage

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bgtvs(n, s, y, conf.level = 0.95, alternative = "two.sided",
 maxiter = 100)

Arguments

n

vector of integer values, specifying the number of groups of the different sizes

s

vector of integer values, specifying the group sizes, must be of same length as n

y

vector of integer values, specifying the number of positive groups among the n groups tested

conf.level

a single numeric value, the confidence level of the interval

alternative

a character string, with options "two.sided", "less", "greater"

maxiter

maximal number steps in iteration of confidence limits

Details

Hepworth (1996) describes methods for constructing confidence intervals in binomial group testing, if groups of different size are used. Currently, only the exact method (Hepworth, 1996, equation5, Table.5) is implemented. Note, that the algorithm becomes computationally very expensive if the number of different groups becomes larger than 3.

Value

A list containing

conf.int

a numeric vector, the lower and upper limits of the confidence interval

estimate

the point estimate

conf.level

as input

alternative

as imput

input

a matrix containing the input values of n (number of groups), s (group size), and y (number of positive pools)

moreover, some of the input arguments.

Author(s)

Frank Schaarschmidt

References

Hepworth, G (1996): Exact confidence intervals for proportions estimated by group testing. Biometrics 52, 1134-1146.

See Also

pooledBin for asymptotic methods to calculate confidence intervals for one proportion in designs with a number of different pool sizes. Note that pooledBin can handle larger number of different pool sizes than bgtvs

Examples

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# Consider a very simple example,
# given in Hepworth (1996), table 5:
# 2 groups each containing 5 units,
# and 3 groups, each containing 2 units

# In the first setting (n=2, s=5) y=1 positive group 
# has been observed, in the second setting (n=3, s=2),
# y=2 positive have been observed.

bgtvs(n=c(2,3), s=c(5,2), y=c(1,2)) 

###############################################

# Recalculate the example given in
# Hepworth (1996), table 5:

 bgtvs(n=c(2,3), s=c(5,2), y=c(0,0))
 bgtvs(n=c(2,3), s=c(5,2), y=c(0,1))
 bgtvs(n=c(2,3), s=c(5,2), y=c(0,2))
 bgtvs(n=c(2,3), s=c(5,2), y=c(0,3))
 bgtvs(n=c(2,3), s=c(5,2), y=c(1,0))
 bgtvs(n=c(2,3), s=c(5,2), y=c(1,1))
 bgtvs(n=c(2,3), s=c(5,2), y=c(1,2))
 bgtvs(n=c(2,3), s=c(5,2), y=c(1,3))
 bgtvs(n=c(2,3), s=c(5,2), y=c(2,0))
 bgtvs(n=c(2,3), s=c(5,2), y=c(2,1))
 bgtvs(n=c(2,3), s=c(5,2), y=c(2,2))
 bgtvs(n=c(2,3), s=c(5,2), y=c(2,3))

binGroup documentation built on March 18, 2018, 2:04 p.m.