estDesign {binGroup}R Documentation

Planning of group size to achieve minimal mse in a binomial group testing experiment

Description

Find the group size s for a fixed number of assays n and an assumed true proportion p.tr for which the mse of the point estimator is minimal and bias is within a restriction. To optimze binomial group testing design as recommended by Swallow(1985), if main objective is estimation.

Usage

estDesign(n, smax, p.tr, biasrest = 0.05)

Arguments

n integer, fixed sample size (number of assays)
smax integer, maximal group size allowed in planning of the design
p.tr assumed true proportion of the 'positive' trait in the population to be tested, specify as a value between 0 and 1
biasrest value between 0 and 1 specifying the absolute bias maximally allowed

Details

Swallow (1985) recommends to use the upper bound of the expected range of true proportion p.tr for optimization of tzhe design. For further details see the reference. Up to now, specify n<1020.

Value

the group size s, for which the mse of the estimator is minimal for the given n, p.tr or the group size s for which bias restriction biasrest is just not violated, and for this particular group size s: a list containing:

varp the variance of the estimator
mse the mean square error of the estimator
bias the bias of the estimator
exp the expected value of the estimator

References

Swallow WH, 1985: Group testing for estimating infection rates and probabilities of disease transmission. Phytopathology Vol.75, N.8, 882-889.

See Also

nDesign, sDesign for choice of the binomial group testing design according to the power in a hypothesis test

Examples


### Compare table 1 in Swallow(1985),885:

estDesign(n=10, smax=100, p.tr=0.001)

estDesign(n=10, smax=100, p.tr=0.01)

estDesign(n=25, smax=100, p.tr=0.05)

estDesign(n=40, smax=100, p.tr=0.25)

estDesign(n=200, smax=100, p.tr=0.3)


[Package binGroup version 0.3-2 Index]