Optimal design of multiple-objective Lot Quality Assurance Sampling (LQAS) plans

Belmiro P.M. Duarte, Weng Kee Wong

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Lot Quality Assurance Sampling (LQAS) plans are widely used for health monitoring purposes. We propose a systematic approach to design multiple-objective LQAS plans that meet user-specified type 1 and 2 error rates and targets for selected diagnostic accuracy metrics. These metrics may include sensitivity, specificity, positive predictive value, and negative predictive value in high or low anticipated prevalence rate populations. We use Mixed Integer Nonlinear Programming (MINLP) tools to implement our design methodology. Our approach is flexible in that it can directly generate classic LQAS plans that control error rates only and find optimal LQAS plans that meet multiple objectives in terms of diagnostic metrics. We give examples, compare results with the classic LQAS and provide an application using a malaria outcome indicator survey in Mozambique.

Original languageEnglish
Pages (from-to)572-581
Number of pages10
JournalBiometrics
Volume75
Issue number2
DOIs
Publication statusPublished - 2019

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • General Biochemistry,Genetics and Molecular Biology
  • General Immunology and Microbiology
  • General Agricultural and Biological Sciences
  • Applied Mathematics

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