Prevalence and Regression for Pool-Tested (Group-Tested) Data

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Documentation for package ‘PoolTestR’ version 0.2.0

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ExampleData A synthetic dataset for pooled testing
getPrevalence Predicting Prevalence from a Mixed or Fixed Effect Logistic Regression with Presence/Absence Tests on Pooled Samples
getPrevalence.brmsfit Predicting Prevalence from a Mixed or Fixed Effect Logistic Regression with Presence/Absence Tests on Pooled Samples
getPrevalence.glm Predicting Prevalence from a Mixed or Fixed Effect Logistic Regression with Presence/Absence Tests on Pooled Samples
getPrevalence.glmerMod Predicting Prevalence from a Mixed or Fixed Effect Logistic Regression with Presence/Absence Tests on Pooled Samples
HierPoolPrev Estimation of prevalence based on presence/absence tests on pooled samples in a hierarchical sampling frame. Uses an intercept-only random effects model to model prevalence at population level. See PoolReg and PoolRegBayes for full mixed-effect modelling
PoolLink Link Function for Logistic Regression with Presence/Absence Tests on Pooled Samples
PoolPrev Estimation of prevalence based on presence/absence tests on pooled samples
PoolReg Frequentist Mixed or Fixed Effect Logistic Regression with Presence/Absence Tests on Pooled Samples
PoolRegBayes Bayesian Mixed or Fixed Effect Logistic Regression with Presence/Absence Tests on Pooled Samples
SimpleExampleData A synthetic dataset for pooled testing
TruePrev A synthetic dataset for pooled testing