Evidence map›Paper›PMID 29249898›Full record

ArticleJournal of the Royal Statistical Society. Series B, Statistical methodology2017

Optimal group testing designs for estimating prevalence with uncertain testing errors.

Shih-Hao Huang, Mong-Na Lo Huang, Kerby Shedden, Weng Kee Wong

Abstract read
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In one paragraph

Article in Journal of the Royal Statistical Society. Series B, Statistical methodology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Assessing Simultaneous Infection with Multiple Pathogens via Group Testing with Imperfect Multiplex Assays.Journal of agricultural, biological, and environmental statistics · 2025
    Article
  2. Article
  3. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shih-Hao HuangNational Sun Yat-sen University, Kaohsiung, Taiwan.
Mong-Na Lo HuangNational Sun Yat-sen University, Kaohsiung, Taiwan.
Kerby SheddenThe University of Michigan, Ann Arbor, U.S.A.
Weng Kee WongUniversity of California at Los Angeles, Los Angeles, U.S.A.

Funding

Designing Efficient Designs under Model Uncertainty for Biological StudiesR01GM107639 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI WONG, WENG K · 2014 to 2017
$1.0M
NIGMS NIH HHS R01 GM107639
6 · The paper itself

Abstract

We construct optimal designs for group testing experiments where the goal is to estimate the prevalence of a trait using a test with uncertain sensitivity and specificity. Using optimal design theory for approximate designs, we show that the most efficient design for simultaneously estimating the prevalence, sensitivity, and specificity requires three different group sizes with equal frequencies. However, if estimating prevalence as accurately as possible is the only focus, the optimal strategy is to have three group sizes with unequal frequencies. Based on a Chlamydia study in the United States, we compare performances of competing designs and provide insights into how the unknown sensitivity and specificity of the test affect the performance of the prevalence estimator. We demonstrate that the proposed locally

Indexed as

D-optimalityDs-optimalityGroup testingSensitivitySpecificity

Identifiers

PMID29249898
PMCPMC5726813

What OpenQuestion holds

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Registered trials

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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.