ArticleBiometrics2012
Group testing for case identification with correlated responses.
Article in Biometrics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Trial
- binGroup2: Statistical Tools for Infection Identification via Group Testing.The R journal · 2023Article
- The efficient design of Nested Group Testing algorithms for disease identification in clustered data.Journal of applied statistics · 2023Article
- Leveraging network structure to improve pooled testing efficiency.Journal of the Royal Statistical Society. Series C, Applied statistics · 2022Article
- Pooled testing of traced contacts under superspreading dynamics.PLoS computational biology · 2022Article
- Network-Informed Constrained Divisive Pooled Testing Assignments.Frontiers in big data · 2022Article
- Positively Correlated Samples Save Pooled Testing Costs.IEEE transactions on network science and engineering · 2021Article
- Array testing for multiplex assays.Biostatistics (Oxford, England) · 2020Article
- Group testing case identification with biomarker information.Computational statistics & data analysis · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
This article examines group testing procedures where units within a group (or pool) may be correlated. The expected number of tests per unit (i.e., efficiency) of hierarchical- and matrix-based procedures is derived based on a class of models of exchangeable binary random variables. The effect on efficiency of the arrangement of correlated units within pools is then examined. In general, when correlated units are arranged in the same pool, the expected number of tests per unit decreases, sometimes substantially, relative to arrangements that ignore information about correlation.
Indexed as
Identifiers
What OpenQuestion holds
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.