Robust group testing for multiple traits with misclassification

References

• A.C. Atkinson and B. Bogacka, Compound D- and Ds-optimum designs for determining the order of a chemical reaction, Technometrics 39 (1997), pp. 347–356.
   Web of Science ®Google Scholar
• A.C. Atkinson, A.N. Donev, and R.D. Tobias, Optimum Experimental Designs, with SAS, Oxford University Press, Oxford, 2007.
   Google Scholar
• F. Behets, S. Bortozzi, M. Kasali, M. Kashamuka, L. Atikala, C. Brown, R.W. Ryder, and T.C. Quinn, Successful use of pooled sera to determine HIV-1 seroprevalence in Zaire with development of cost-efficiency models, AIDS 4 (1990), pp. 737–742. doi: 10.1097/00002030-199008000-00004
   PubMed Web of Science ®Google Scholar
• C.L. Chiang and W.C. Reeves, Statistical estimation of virus infection rates in mosquito vector populations, Am. J. Hyg. 75 (1962), pp. 377–391.
   PubMed Web of Science ®Google Scholar
• R.D. Cook and W.K. Wong, On the equivalence of constrained and compound optimal designs, J. Am. Stat. Assoc. 89 (1994), pp. 687–692. doi: 10.1080/01621459.1994.10476794
   Web of Science ®Google Scholar
• R. Dorfman, The detection of defective members of large populations, Ann. Math. Stat. 14 (1943), pp. 436–440. doi: 10.1214/aoms/1177731363
   Google Scholar
• J.L. Gastwirth and W.O. Johnson, Screening with cost-effective quality control: Potential applications to HIV and drug testing, J. Am. Stat. Assoc. 89 (1994), pp. 972–981. doi: 10.1080/01621459.1994.10476831
   Web of Science ®Google Scholar
• J.M. Hughes-Oliver and W.F. Rosenberger, Efficient estimation of the prevalence of multiple rare traits, Biometrika 87 (2000), pp. 315–327. doi: 10.1093/biomet/87.2.315
   Web of Science ®Google Scholar
• H.Y. Kim, M.G. Hudgens, J. Dreyfuss, D. Westreich, and C.D. Pilcher, Comparison of group testing algorithms for case identification in the presence of test error, Biometrics 63 (2007), pp. 1152–1163. doi: 10.1111/j.1541-0420.2007.00817.x
   PubMed Web of Science ®Google Scholar
• A.Y. Liu, C.L. Liu, Z.W. Zhang, and P.S. Albert, Optimality of group testing in the presence of misclassification, Biometrika 99 (2012), pp. 245–251. doi: 10.1093/biomet/asr064
   PubMed Web of Science ®Google Scholar
• R.M. Pfeiffer, J.L. Rutter, M.H. Gail, J. Struewing, and J.L. Gastwirth, Efficiency of DNA pooling to estimate joint allele frequencies and measure linkage disequilibrium, Genet. Epidemiol. 22 (2002), pp. 94–102. doi: 10.1002/gepi.1046
   PubMed Web of Science ®Google Scholar
• W.H. Press, B.P. Flannery, S.A. Teukolsky, and W.T. Vetterling (eds), Numerical Recipes in Fortran77 the Art of Scientific Computing, Cambridge University Press, Cambridge, 1992.
   Google Scholar
• W.H. Swallow, Group testing for estimating infection rates and probabilities of disease transmission, Phytopathology 75 (1985), pp. 882–889. doi: 10.1094/Phyto-75-882
   Web of Science ®Google Scholar
• W.H. Swallow, Relative mean squared error and cost considerations in choosing group size for group testing to estimate infection rates and probabilities of disease transmission, Phytopathology 77 (1987), pp. 1376–1381. doi: 10.1094/Phyto-77-1376
   Web of Science ®Google Scholar
• J.M. Tebbs, C.S. McMahan, and C.R. Bilder, Two-stage hierarchical group testing for multiple infections with application to the infertility prevention project, Biometrics 69 (2013), pp. 1064–1073. doi: 10.1111/biom.12080
   PubMed Web of Science ®Google Scholar
• J.M. Tebbs and W.H. Swallow, Estimating ordered binomial proportions with the use of group testing, Biometrika 90 (2003), pp. 471–477. doi: 10.1093/biomet/90.2.471
   Web of Science ®Google Scholar
• K.H. Thompson, Estimation of the proportion of vectors in a natural population of insects, Biometrics 18 (1962), pp. 568–578. doi: 10.2307/2527902
   Web of Science ®Google Scholar
• X.M. Tu, E. Litvak, and M. Pagano, On the informativeness and accuracy of pooled testing in estimating prevalence of a rare disease: Application to HIV screening, Biometrika 82 (1995), pp. 287–297. doi: 10.1093/biomet/82.2.287
   Web of Science ®Google Scholar
• G.R. Uhl, Q.-R. Liu, D. Walther, J. Hess, and D. Naiman, Polysubstance abuse-vulnerability genes: Genome scans for association, using 1,004 subjects and 1,494 single-nucleotide polymorphisms, Am. J. Hum. Genet. 69 (2001), pp. 1290–1300. doi: 10.1086/324467
   PubMed Web of Science ®Google Scholar
• B. Zhang, C.R. Bilder, and J.M. Tebbs, Regression analysis for multiple-disease group testing data, Stat. Med. 32 (2013), pp. 4954–4966. doi: 10.1002/sim.5858
   PubMed Web of Science ®Google Scholar