ArticleJournal of agricultural, biological, and environmental statistics2017
Bias Correction in Estimating Proportions by Pooled Testing.
Article in Journal of agricultural, biological, and environmental statistics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Confidence Intervals for a Proportion Estimated From Pooled Samples Based on Firth's Corrected Score.Biometrical journal. Biometrische Zeitschrift · 2026Article
- Meteorological and environmental drivers of West Nile virus prevalence in Culex pipiens mosquitoes in Emilia-Romagna, Italy in 2013 to 2022.PLoS pathogens · 2025Article
- Assessing Simultaneous Infection with Multiple Pathogens via Group Testing with Imperfect Multiplex Assays.Journal of agricultural, biological, and environmental statistics · 2025Article
- A numbers game: mosquito-based arbovirus surveillance in two distinct geographic regions of Latin America.Journal of medical entomology · 2025Article
- A numbers game: Mosquito-based arbovirus surveillance in two distinct geographic regions of Latin America.bioRxiv : the preprint server for biology · 2024Article
- binGroup2: Statistical Tools for Infection Identification via Group Testing.The R journal · 2023Article
- Surveillance for Zika, Chikungunya, and Dengue Virus Incidence and RNAemia in Blood Donors at 4 Brazilian Blood Centers During 2016-2019.The Journal of infectious diseases · 2023Article
- Using group testing in a two-phase epidemiologic design to identify the effects of a large number of antibody reactions on disease risk.BMC medical research methodology · 2022Article
- A proposed framework for the development and qualitative evaluation of West Nile virus models and their application to local public health decision-making.PLoS neglected tropical diseases · 2021Review
- Understanding Mosquito Surveillance Data for Analytic Efforts: A Case Study.Journal of medical entomology · 2021Review
- Bias Correction in Estimating Proportions by Imperfect Pooled Testing.Journal of agricultural, biological, and environmental statistics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.