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Bias Correction in Estimating Proportions by Pooled Testing

  • Graham Hepworth
  • Brad J. Biggerstaff
Article
  • 136 Downloads

Abstract

In the estimation of proportions by pooled testing, the MLE is biased, and several methods of correcting the bias have been presented in previous studies. We propose a new estimator based on the bias correction method introduced by Firth (Biometrika 80:27–38, 1993), which uses a modification of the score function, and we provide an easily computable, Newton–Raphson iterative formula for its computation. Our proposed estimator is almost unbiased across a range of problems, and superior to existing methods. We show that for equal pool sizes the new estimator is equivalent to the estimator proposed by Burrows (Phytopathology 77:363–365, 1987). The performance of our estimator is examined using pooled testing problems encountered in plant disease assessment and prevalence estimation of mosquito-borne viruses.

Supplementary materials accompanying this paper appear online.

Keywords

Bias correction Estimation of proportions Group testing Pooled testing Virus prevalence 

Supplementary material

13253_2017_297_MOESM1_ESM.pdf (155 kb)
Supplementary material 1 (pdf 155 KB)

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Copyright information

© International Biometric Society 2017

Authors and Affiliations

  1. 1.School of Mathematics and StatisticsThe University of MelbourneVictoriaAustralia
  2. 2.Centers for Disease Control and PreventionFort CollinsUSA

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