Bias Correction in Estimating Proportions by Pooled Testing

Graham Hepworth () and Brad J. Biggerstaff
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Graham Hepworth: The University of Melbourne
Brad J. Biggerstaff: Centers for Disease Control and Prevention

Journal of Agricultural, Biological and Environmental Statistics, 2017, vol. 22, issue 4, No 10, 602-614

Abstract: 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 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s13253-017-0297-2

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