binGroup (version 2.2-1)

Informative.array.prob: Arrange a matrix of probabilities for informative array testing

Description

Arrange a vector of individual risk probabilities in a matrix for informative array testing without master pooling.

Usage

Informative.array.prob(prob.vec, nr, nc, method = "sd")

Arguments

prob.vec

vector of individual risk probabilities, of length nr*nc.

nr

the number of rows in the array.

nc

the number of columns in the array.

method

character string defining the method to be used for matrix arrangement. Options include spiral ("sd") and gradient ("gd") arrangement. See McMahan et al. (2012) for additional details.

Value

A matrix of probabilities arranged according to the specified method.

References

McMahan2012bbinGroup

See Also

p.vec.func for generating a vector of individual risk probabilities from an overall probability of disease and Array.Measures for calculating operating characteristics for informative array testing without master pooling.

http://chrisbilder.com/grouptesting

Other Individual risk probability functions: beta.dist, p.vec.func

Examples

# NOT RUN {
# Use the gradient arrangement method to create a matrix
#   of individual risk probabilities for a 10x10 array.
# Depending on the specified probability, alpha level, 
#   and overall group size, simulation may be necessary in 
#   order to generate the vector of individual probabilities. 
#   This is done using the p.vec.func() function and requires 
#   the user to set a seed in order to reproduce results.
# This example takes less than 1 second to run.
# Estimated running time was calculated using a 
#   computer with 16 GB of RAM and one core of an 
#   Intel i7-6500U processor.
set.seed(1107)
p.vec1 <- p.vec.func(p=0.05, alpha=2, grp.sz=100)
Informative.array.prob(prob.vec=p.vec1, nr=10, nc=10, method="gd")

# Use the spiral arrangement method to create a matrix
#   of individual risk probabilities for a 5x5 array.
# Depending on the specified probability, alpha level, 
#   and overall group size, simulation may be necessary in 
#   order to generate the vector of individual probabilities. 
#   This is done using the p.vec.func() function and requires 
#   the user to set a seed in order to reproduce results.
# This example takes less than 1 second to run.
# Estimated running time was calculated using a 
#   computer with 16 GB of RAM and one core of an 
#   Intel i7-6500U processor.
set.seed(8791)
p.vec2 <- p.vec.func(p=0.02, alpha=0.5, grp.sz=25)
Informative.array.prob(prob.vec=p.vec2, nr=5, nc=5, method="sd")
# }