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binGroup

Evaluation and Experimental Design for Binomial Group Testing

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.

Functions (59)

Array.Measures

Operating characteristics for array testing without master pooling

Inf.Array

Find the optimal testing configuration for informative array testing without master pooling

Inf.D3

Find the optimal testing configuration for 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

MasterPool.Array.Measures

Operating characteristics for array testing with 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

NI.Dorf

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

OTC

Find the optimal testing configuration

accuracy.dorf

Accuracy measures for informative Dorfman testing

beta.dist

Expected value of order statistics from a beta distribution

bgtCI

Confidence Intervals for One Proportion in Binomial Group Testing

bgtPower

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

bgtTest

Hypothesis Test for One Proportion in Binomial Group Testing

bgtWidth

Expected Width of Confidence Intervals in Binomial Group Testing

bgtvs

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

binCI

Confidence Intervals for One Binomial Proportion

binDesign

Sample Size Iteration for One Parameter Binomial Problem

binGroup-package

Statistical Methods for Group Testing.

binPower

Power Calculation for One Parameter Binomial Problem

binTest

Hypothesis tests for One Binomial Proportion

binWidth

Expected Confidence Interval Width for One Binomial Proportion

characteristics.pool

Testing expenditure for informative Dorfman testing

estDesign

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

gt.control

Auxiliary for Controlling Group Testing Regression

gtreg

Fitting Group Testing Models

gtreg.halving

Fitting Group Testing Models Under the Halving Protocol

gtreg.mp

Fitting Group Testing Models in Matrix Pooling Setting

hierarchical.desc2

Operating characteristics for hierarchical group testing

hivsurv

Data from an HIV surveillance project

inf.dorf.measures

Operating characteristics 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

p.vec.func

Generate a vector of probabilities for informative group testing algorithms.

plot.bgtDesign

Plot Results of nDesign or sDesign

plot.binDesign

Plot Results of binDesign

plot.poolbin

Diagnostic line fit for pool.bin objects

pool.specific.dorf

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

pooledBin

Confidence intervals for a single proportion

pooledBinDiff

Confidence intervals for the difference of proportions

predict.gt

Predict Method for Group Testing Model Fits

print.bgt

Print Functions for Group Testing CIs and Tests for One Proportion

print.bgtDesign

Print Functions for nDesign and sDesign

print.binDesign

Print Function for binDesign

print.gt

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

print.poolbindiff

Print methods for classes "poolbin" and "poolbindiff"

print.summary.gt.mp

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

residuals.gt

Extract Model Residuals From a Fitted Group Testing Model

sDesign

Iterate Group Size for a One-Parameter Group Testing Problem

sim.gt

Simulation Function for Group Testing Data

sim.halving

Simulation Function for Group Testing Data for the Halving Protocol

sim.mp

Simulation Function for Group Testing Data with Matrix Pooling Design

summary.gt

Summary Method for Group Testing Model (Simple Pooling) Fits

summary.gt.mp

Summary Method for Group Testing Model (Matrix Pooling) Fits

summary.poolbindiff

Summary methods for "poolbin" and "poolbindiff"

thresh.val.dorf

Find the optimal threshold value for Thresholded Optimal Dorfman testing

binGroup

Evaluation and Experimental Design for Binomial Group Testing

v2.2-1

GPL (>= 3)

Authors

Boan Zhang [aut], Christopher Bilder [aut], Brad Biggerstaff [aut], Frank Schaarschmidt [aut, cre], Brianna Hitt [aut]

Initial release

2018-08-24

binGroup

Functions (59)

binGroup

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