Bias Correction in Estimating Proportions by Pooled Testing
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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.
KeywordsBias correction Estimation of proportions Group testing Pooled testing Virus prevalence
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