Literature DB >> 23049137

Optimality of group testing in the presence of misclassification.

Aiyi Liu1, Chunling Liu, Zhiwei Zhang, Paul S Albert.   

Abstract

Several optimality properties of Dorfman's (1943) group testing procedure are derived for estimation of the prevalence of a rare disease whose status is classified with error. Exact ranges of disease prevalence are obtained for which group testing provides more efficient estimation when group size increases.

Year:  2011        PMID： 23049137      PMCID： PMC3412609          DOI： 10.1093/biomet/asr064

Source DB:  PubMed          Journal:  Biometrika        ISSN： 0006-3444            Impact factor:   2.445


  9 in total

1.  Robustness of group testing in the estimation of proportions.

Authors:  M Hung; W H Swallow
Journal:  Biometrics       Date:  1999-03       Impact factor: 2.571

2.  Estimating prevalence by group testing using generalized linear models.

Authors:  C P Farrington
Journal:  Stat Med       Date:  1992-09-15       Impact factor: 2.373

3.  Using group testing to estimate a proportion, and to test the binomial model.

Authors:  C L Chen; W H Swallow
Journal:  Biometrics       Date:  1990-12       Impact factor: 2.571

4.  Accounting for error due to misclassification of exposures in case-control studies of gene-environment interaction.

Authors:  Li Zhang; Bhramar Mukherjee; Malay Ghosh; Stephen Gruber; Victor Moreno
Journal:  Stat Med       Date:  2008-07-10       Impact factor: 2.373

5.  Association mapping of disease loci, by use of a pooled DNA genomic screen.

Authors:  L F Barcellos; W Klitz; L L Field; R Tobias; A M Bowcock; R Wilson; M P Nelson; J Nagatomi; G Thomson
Journal:  Am J Hum Genet       Date:  1997-09       Impact factor: 11.025

6.  Sensitivity and specificity of pooled versus individual sera in a human immunodeficiency virus antibody prevalence study.

Authors:  B Cahoon-Young; A Chandler; T Livermore; J Gaudino; R Benjamin
Journal:  J Clin Microbiol       Date:  1989-08       Impact factor: 5.948

7.  Analysis of multistage pooling studies of biological specimens for estimating disease incidence and prevalence.

Authors:  R Brookmeyer
Journal:  Biometrics       Date:  1999-06       Impact factor: 2.571

8.  A new estimator for infection rates using pools of variable size.

Authors:  C T Le
Journal:  Am J Epidemiol       Date:  1981-07       Impact factor: 4.897

9.  Screening test for HTLV-III (AIDS agent) antibodies. Specificity, sensitivity, and applications.

Authors:  S H Weiss; J J Goedert; M G Sarngadharan; A J Bodner; R C Gallo; W A Blattner
Journal:  JAMA       Date:  1985-01-11       Impact factor: 56.272
  9 in total
  19 in total

1.  Bayesian regression for group testing data.

Authors:  Christopher S McMahan; Joshua M Tebbs; Timothy E Hanson; Christopher R Bilder
Journal:  Biometrics       Date:  2017-04-12       Impact factor: 2.571

2.  Two-stage hierarchical group testing for multiple infections with application to the infertility prevention project.

Authors:  Joshua M Tebbs; Christopher S McMahan; Christopher R Bilder
Journal:  Biometrics       Date:  2013-10-04       Impact factor: 2.571

3.  Regression analysis and variable selection for two-stage multiple-infection group testing data.

Authors:  Juexin Lin; Dewei Wang; Qi Zheng
Journal:  Stat Med       Date:  2019-07-11       Impact factor: 2.373

4.  Misclassified group-tested current status data.

Authors:  L C Petito; N P Jewell
Journal:  Biometrika       Date:  2016-12-08       Impact factor: 2.445

5.  Prevalence estimation subject to misclassification: the mis-substitution bias and some remedies.

Authors:  Zhiwei Zhang; Chunling Liu; Sungduk Kim; Aiyi Liu
Journal:  Stat Med       Date:  2014-07-18       Impact factor: 2.373

6.  Revisiting Nested Group Testing Procedures: New Results, Comparisons, and Robustness.

Authors:  Yaakov Malinovsky; Paul S Albert
Journal:  Am Stat       Date:  2018-06-04       Impact factor: 8.710

7.  Group testing regression models with dilution submodels.

Authors:  Md S Warasi; Christopher S McMahan; Joshua M Tebbs; Christopher R Bilder
Journal:  Stat Med       Date:  2017-08-30       Impact factor: 2.373

8.  Estimating the prevalence of multiple diseases from two-stage hierarchical pooling.

Authors:  Md S Warasi; Joshua M Tebbs; Christopher S McMahan; Christopher R Bilder
Journal:  Stat Med       Date:  2016-04-18       Impact factor: 2.373

9.  Group testing regression model estimation when case identification is a goal.

Authors:  Boan Zhang; Christopher R Bilder; Joshua M Tebbs
Journal:  Biom J       Date:  2013-02-08       Impact factor: 2.207

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

Authors:  Shih-Hao Huang; Mong-Na Lo Huang; Kerby Shedden; Weng Kee Wong
Journal:  J R Stat Soc Series B Stat Methodol       Date:  2016-12-19       Impact factor: 4.488
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