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binGroup (version 2.2-1)

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

1,578

Version

2.2-1

License

GPL (>= 3)

Last Published

August 24th, 2018

Functions in binGroup (2.2-1)

binTest

Hypothesis tests for One Binomial Proportion
characteristics.pool

Testing expenditure for informative Dorfman testing
NI.Dorf

Find the optimal testing configuration for non-informative two-stage hierarchical testing
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
binDesign

Sample Size Iteration for One Parameter Binomial Problem
estDesign

Sample Size Iteration Depending on Minimal MSE in One-Parameter Group Testing
pooledBinDiff

Confidence intervals for the difference of proportions
binCI

Confidence Intervals for One Binomial Proportion
beta.dist

Expected value of order statistics from a beta distribution
predict.gt

Predict Method for Group Testing Model Fits
bgtCI

Confidence Intervals for One Proportion in Binomial Group Testing
gtreg.halving

Fitting Group Testing Models Under the Halving Protocol
bgtWidth

Expected Width of Confidence Intervals in Binomial Group Testing
gtreg.mp

Fitting Group Testing Models in Matrix Pooling Setting
binWidth

Expected Confidence Interval Width for One Binomial Proportion
hierarchical.desc2

Operating characteristics for hierarchical group testing
hivsurv

Data from an HIV surveillance project
summary.gt.mp

Summary Method for Group Testing Model (Matrix Pooling) Fits
binPower

Power Calculation for One Parameter Binomial Problem
print.poolbindiff

Print methods for classes "poolbin" and "poolbindiff"
summary.poolbindiff

Summary methods for "poolbin" and "poolbindiff"
Inf.D3

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

Confidence Interval for One Proportion in Group Testing with Variable Group Sizes
inf.dorf.measures

Operating characteristics for informative two-stage hierarchical (Dorfman) testing
Inf.Dorf

Find the optimal testing configuration for informative two-stage hierarchical (Dorfman) testing
nDesign

Iterate Sample Size in One Parameter Group Testing
opt.info.dorf

Find the characteristics of an informative two-stage hierarchical (Dorfman) algorithm
opt.pool.size

Find the optimal pool size for Optimal Dorfman or Thresholded Optimal Dorfman
plot.binDesign

Plot Results of binDesign
bgtPower

Power to Reject a Hypothesis in Binomial Group Testing for One Proportion
plot.poolbin

Diagnostic line fit for pool.bin objects
print.summary.gt

Print Functions for summary.gt.mp and summary.gt
sim.gt

Simulation Function for Group Testing Data
bgtTest

Hypothesis Test for One Proportion in Binomial Group Testing
sim.halving

Simulation Function for Group Testing Data for the Halving Protocol
thresh.val.dorf

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

Auxiliary for Controlling Group Testing Regression
gtreg

Fitting Group Testing Models
pool.specific.dorf

Find the optimal pool sizes for Pool-Specific Optimal Dorfman (PSOD) testing
pooledBin

Confidence intervals for a single proportion
print.bgt

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

Print Function for binDesign
sim.mp

Simulation Function for Group Testing Data with Matrix Pooling Design
print.gt

Print methods for objects of classes "gt" and "gt.mp"
print.bgtDesign

Print Functions for nDesign and sDesign
summary.gt

Summary Method for Group Testing Model (Simple Pooling) Fits
residuals.gt

Extract Model Residuals From a Fitted Group Testing Model
sDesign

Iterate Group Size for a One-Parameter Group Testing Problem
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
Informative.array.prob

Arrange a matrix of probabilities for informative array testing
OTC

Find the optimal testing configuration
Array.Measures

Operating characteristics for array testing without master pooling
Inf.Array

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

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

Operating characteristics for array testing with master pooling
accuracy.dorf

Accuracy measures for informative Dorfman testing