Conditional dependence between tests affects the diagnosis and surveillance of animal diseases

Ian Gardner, Henrik Stryhn, Peter Lind, Michael T. Collins

Research output: Contribution to journalArticle

226 Scopus citations

Abstract

Dependence between the sensitivities or specificities of pairs of tests affects the sensitivity and specificity of tests when used in combination. Compared with values expected if tests are conditionally independent, a positive dependence in test sensitivity reduces the sensitivity of parallel test interpretation and a positive dependence in test specificity reduces the specificity of serial interpretation. We calculate conditional covariances as a measure of dependence between binary tests and show their relationship to kappa (a chance-corrected measure of test agreement). We use published data for toxoplasmosis and brucellosis in swine, and Johne's disease in cattle to illustrate calculation methods and to indicate the likely magnitude of the dependence between serologic tests used for diagnosis and surveillance of animal diseases. (C) 2000 Elsevier Science B.V.

Original languageEnglish (US)
Pages (from-to)107-122
Number of pages16
JournalPreventive Veterinary Medicine
Volume45
Issue number1-2
DOIs
StatePublished - May 30 2000

Keywords

  • Combined tests
  • Conditional dependence
  • Kappa
  • Parallel testing
  • Sensitivity
  • Serial testing
  • Specificity
  • Test covariance

ASJC Scopus subject areas

  • Food Animals
  • Animal Science and Zoology

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