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The Cost-Effectiveness of Reclassification Sampling for Prevalence Estimation

Author

Listed:
  • Airat Bekmetjev
  • Dirk VanBruggen
  • Brian McLellan
  • Benjamin DeWinkle
  • Eric Lunderberg
  • Nathan Tintle

Abstract

Background: Typically, a two-phase (double) sampling strategy is employed when classifications are subject to error and there is a gold standard (perfect) classifier available. Two-phase sampling involves classifying the entire sample with an imperfect classifier, and a subset of the sample with the gold-standard. Methodology/Principal Findings: In this paper we consider an alternative strategy termed reclassification sampling, which involves classifying individuals using the imperfect classifier more than one time. Estimates of sensitivity, specificity and prevalence are provided for reclassification sampling, when either one or two binary classifications of each individual using the imperfect classifier are available. Robustness of estimates and design decisions to model assumptions are considered. Software is provided to compute estimates and provide advice on the optimal sampling strategy. Conclusions/Significance: Reclassification sampling is shown to be cost-effective (lower standard error of estimates for the same cost) for estimating prevalence as compared to two-phase sampling in many practical situations.

Suggested Citation

  • Airat Bekmetjev & Dirk VanBruggen & Brian McLellan & Benjamin DeWinkle & Eric Lunderberg & Nathan Tintle, 2012. "The Cost-Effectiveness of Reclassification Sampling for Prevalence Estimation," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-6, February.
    • Handle: RePEc:plo:pone00:0032058
    DOI: 10.1371/journal.pone.0032058
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    References listed on IDEAS

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    1. J. Sutcliffe, 1965. "A probability model for errors of classification. I. General considerations," Psychometrika, Springer;The Psychometric Society, vol. 30(1), pages 73-96, March.
    2. Tintle Nathan L & Gordon Derek & McMahon Francis J & Finch Stephen J, 2007. "Using Duplicate Genotyped Data in Genetic Analyses: Testing Association and Estimating Error Rates," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 6(1), pages 1-29, February.
    3. Hironori Fujisawa & Shizue Izumi, 2000. "Inference about Misclassification Probabilities from Repeated Binary Responses," Biometrics, The International Biometric Society, vol. 56(3), pages 706-711, September.
    4. Borchers Bryce & Brown Marshall & McLellan Brian & Bekmetjev Airat & Tintle Nathan L, 2009. "Incorporating Duplicate Genotype Data into Linear Trend Tests of Genetic Association: Methods and Cost-Effectiveness," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-20, May.
    5. J. Sutcliffe, 1965. "A probability model for errors of classification. II. Particular cases," Psychometrika, Springer;The Psychometric Society, vol. 30(2), pages 129-155, June.
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