title: Choosing a design to fit the situation: how to improve specificity and positive predictive values using Bayesian lot quality assurance sampling.
abstract: BACKGROUND
  Lot Quality Assurance Sampling (LQAS) is a provably useful tool for monitoring health programmes. Although LQAS ensures acceptable Producer and Consumer risks, the literature alleges that the method suffers from poor specificity and positive predictive values (PPVs). We suggest that poor LQAS performance is due, in part, to variation in the true underlying distribution. However, until now the role of the underlying distribution in expected performance has not been adequately examined.
  
  
  METHODS
  We present Bayesian-LQAS (B-LQAS), an approach to incorporating prior information into the choice of the LQAS sample size and decision rule, and explore its properties through a numerical study. Additionally, we analyse vaccination coverage data from UNICEF's State of the World's Children in 1968-1989 and 2008 to exemplify the performance of LQAS and B-LQAS.
  
  
  RESULTS
  Results of our numerical study show that the choice of LQAS sample size and decision rule is sensitive to the distribution of prior information, as well as to individual beliefs about the importance of correct classification. Application of the B-LQAS approach to the UNICEF data improves specificity and PPV in both time periods (1968-1989 and 2008) with minimal reductions in sensitivity and negative predictive value.
  
  
  CONCLUSIONS
  LQAS is shown to be a robust tool that is not necessarily prone to poor specificity and PPV as previously alleged. In situations where prior or historical data are available, B-LQAS can lead to improvements in expected performance.
authors: Department of Biostatistics, University of Washington, Seattle, WA, USA. colives@uw.edu
authors: Casey
authors: C
authors: Olives
authors: Marcello
authors: M
authors: Pagano
mesh_terms: D001499:Bayes Theorem; D002648:Child; D006801:Humans; D007114:Immunization / Q000706:statistics & numerical data*; D055810:Lot Quality Assurance Sampling; D008458:Measles Vaccine / Q000008:administration & dosage; D011159:Population Surveillance; D011237:Predictive Value of Tests; D015397:Program Evaluation / Q000379:methods; D011785:Quality Assurance, Health Care / Q000379:methods; D012107:Research Design; D012680:Sensitivity and Specificity; D014480:United Nations
chemical_list: D008458:Measles Vaccine
references: Health Policy Plan. 2001 Sep;16(3):248-55
references: 11527865
references: Am J Trop Med Hyg. 2004 Apr;70(4):390-4
references: 15100452
references: Soc Sci Med. 2006 Sep;63(6):1648-60
references: 16764978
references: Emerg Themes Epidemiol. 2010 Jun 09;7(1):3
references: 20534159
references: Sex Transm Infect. 2010 Feb;86 Suppl 1:i56-61
references: 20167732
references: Trop Med Int Health. 2005 Jul;10(7):647-58
references: 15960703
references: Health Policy Plan. 1993 Sep;8(3):217-23
references: 10128376
references: Parasitology. 2009 Nov;136(13):1707-18
references: 19450373
references: PLoS Negl Trop Dis. 2012;6(9):e1806
references: 22970333
references: Int J Epidemiol. 2010 Feb;39(1):69-71
references: 20139434