Evaluation of diagnostic accuracy in detecting ordered symptom statuses without a gold standard

Zheyu Wang, Xiao Hua Zhou, Miqu Wang

Research output: Contribution to journalArticlepeer-review

Abstract

Our research is motivated by 2 methodological problems in assessing diagnostic accuracy of traditional Chinese medicine (TCM) doctors in detecting a particular symptom whose true status has an ordinal scale and is unknown-imperfect gold standard bias and ordinal scale symptom status. In this paper, we proposed a nonparametric maximum likelihood method for estimating and comparing the accuracy of different doctors in detecting a particular symptom without a gold standard when the true symptom status had an ordered multiple class. In addition, we extended the concept of the area under the receiver operating characteristic curve to a hyper-dimensional overall accuracy for diagnostic accuracy and alternative graphs for displaying a visual result. The simulation studies showed that the proposed method had good performance in terms of bias and mean squared error. Finally, we applied our method to our motivating example on assessing the diagnostic abilities of 5 TCM doctors in detecting symptoms related to Chills disease.

Original languageEnglish (US)
Pages (from-to)567-581
Number of pages15
JournalBiostatistics
Volume12
Issue number3
DOIs
StatePublished - Jul 2011

Keywords

  • Bootstrap
  • Diagnostic accuracy
  • EM algorithm
  • MSE
  • Ordinal tests
  • Traditional Chinese medicine (TCM)
  • Volume under the ROC surface (VUS)

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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