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binGroup (version 2.2-3)

Evaluation and Experimental Design for Binomial Group Testing

Description

Methods for estimation and hypothesis testing of proportions in group testing designs: methods for estimating a proportion in a single population (assuming sensitivity and specificity equal to 1 in designs with equal group sizes), as well as hypothesis tests and functions for experimental design for this situation. For estimating one proportion or the difference of proportions, a number of confidence interval methods are included, which can deal with various different pool sizes. Further, regression methods are implemented for simple pooling and matrix pooling designs. Methods for identification of positive items in group testing designs: Optimal testing configurations can be found for hierarchical and array-based algorithms. Operating characteristics can be calculated for testing configurations across a wide variety of situations.

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Version

Install

install.packages('binGroup')

Monthly Downloads

2,472

Version

2.2-3

License

GPL (>= 3)

Maintainer

Frank Schaarschmidt

Last Published

May 14th, 2025

Functions in binGroup (2.2-3)

bgtWidth

Expected Width of Confidence Intervals in Binomial Group Testing
beta.dist

Expected value of order statistics from a beta distribution
OTC

Find the optimal testing configuration
accuracy.dorf

Accuracy measures for informative Dorfman testing
bgtTest

Hypothesis Test for One Proportion in Binomial Group Testing
bgtvs

Confidence Interval for One Proportion in Group Testing with Variable Group Sizes
bgtPower

Power to Reject a Hypothesis in Binomial Group Testing for One Proportion
bgtCI

Confidence Intervals for One Proportion in Binomial Group Testing
binCI

Confidence Intervals for One Binomial Proportion
binDesign

Sample Size Iteration for One Parameter Binomial Problem
binTest

Hypothesis tests for One Binomial Proportion
gt.control

Auxiliary for Controlling Group Testing Regression
binPower

Power Calculation for One Parameter Binomial Problem
characteristics.pool

Testing expenditure for informative Dorfman testing
gtreg.mp

Fitting Group Testing Models in Matrix Pooling Setting
gtreg.halving

Fitting Group Testing Models Under the Halving Protocol
gtreg

Fitting Group Testing Models
binWidth

Expected Confidence Interval Width for One Binomial Proportion
estDesign

Sample Size Iteration Depending on Minimal MSE in One-Parameter Group Testing
hierarchical.desc2

Operating characteristics for hierarchical group testing
inf.dorf.measures

Operating characteristics for informative two-stage hierarchical (Dorfman) testing
opt.info.dorf

Find the characteristics of an informative two-stage hierarchical (Dorfman) algorithm
p.vec.func

Generate a vector of probabilities for informative group testing algorithms.
binGroup-package

Statistical Methods for Group Testing.
plot.bgtDesign

Plot Results of nDesign or sDesign
plot.poolbin

Diagnostic line fit for pool.bin objects
plot.binDesign

Plot Results of binDesign
hivsurv

Data from an HIV surveillance project
nDesign

Iterate Sample Size in One Parameter Group Testing
opt.pool.size

Find the optimal pool size for Optimal Dorfman or Thresholded Optimal Dorfman
pool.specific.dorf

Find the optimal pool sizes for Pool-Specific Optimal Dorfman (PSOD) testing
print.binDesign

Print Function for binDesign
pooledBin

Confidence intervals for a single proportion
print.bgt

Print Functions for Group Testing CIs and Tests for One Proportion
print.bgtDesign

Print Functions for nDesign and sDesign
pooledBinDiff

Confidence intervals for the difference of proportions
sDesign

Iterate Group Size for a One-Parameter Group Testing Problem
predict.gt

Predict Method for Group Testing Model Fits
thresh.val.dorf

Find the optimal threshold value for Thresholded Optimal Dorfman testing
residuals.gt

Extract Model Residuals From a Fitted Group Testing Model
print.summary.gt

Print Functions for summary.gt.mp and summary.gt
print.poolbindiff

Print methods for classes "poolbin" and "poolbindiff"
print.gt

Print methods for objects of classes "gt" and "gt.mp"
summary.gt.mp

Summary Method for Group Testing Model (Matrix Pooling) Fits
summary.gt

Summary Method for Group Testing Model (Simple Pooling) Fits
summary.poolbindiff

Summary methods for "poolbin" and "poolbindiff"
sim.mp

Simulation Function for Group Testing Data with Matrix Pooling Design
sim.halving

Simulation Function for Group Testing Data for the Halving Protocol
sim.gt

Simulation Function for Group Testing Data
Array.Measures

Operating characteristics for array testing without master pooling
NI.A2M

Find the optimal testing configuration for non-informative array testing with master pooling
NI.Array

Find the optimal testing configuration for non-informative array testing without master pooling
NI.D3

Find the optimal testing configuration for non-informative three-stage hierarchical testing
Inf.Dorf

Find the optimal testing configuration for informative two-stage hierarchical (Dorfman) testing
Informative.array.prob

Arrange a matrix of probabilities for informative array testing
Inf.Array

Find the optimal testing configuration for informative array testing without master pooling
NI.Dorf

Find the optimal testing configuration for non-informative two-stage hierarchical testing
MasterPool.Array.Measures

Operating characteristics for array testing with master pooling
Inf.D3

Find the optimal testing configuration for informative three-stage hierarchical testing