Correlation of Positive and Negative Predictive Values of Diagnostic Tests

This Demonstration examines the correlation of the negative predictive value (NPV) and the positive predictive value (PPV) of a diagnostic test for normally distributed nondiseased and diseased populations. Differing levels of prevalence of the disease are considered. The mean and standard deviation of the populations, measured in arbitrary units, are used.


  • [Snapshot]
  • [Snapshot]
  • [Snapshot]


The PPV and NPV that are used in the evaluation of the clinical accuracy of a diagnostic test applied to a diseased or nondiseased population can be calculated given the sensitivity and specificity of the test. Sensitivity is the fraction of the diseased population with a positive test, while specificity is the fraction of the nondiseased population with a negative test. If we denote by the sensitivity, the specificity and the prevalence, then:
Given a diseased and a nondiseased population, the specificity can be defined as a function of sensitivity; therefore, we can plot PPV versus NPV (a parametric plot).
The population data in the snapshots describes a bimodal distribution of serum glucose measurements in nondiabetic and diabetic populations [1].
This Demonstration is based on [2].
[1] T.-O. Lim, R. Bakri, Z. Morad and M. A. Hamid, "Bimodality in Blood Glucose Distribution: Is It Universal?," Diabetes Care, 25(12), 2002 pp. 2212–2217. doi:10.2337/diacare.25.12.2212.
[2] A. T. Hatjimihail. "Uncertainty of Measurement and Diagnostic Accuracy Measures," from the Wolfram Demonstrations Project—A Wolfram Web Resource.
    • Share:

Embed Interactive Demonstration New!

Just copy and paste this snippet of JavaScript code into your website or blog to put the live Demonstration on your site. More details »

Files require Wolfram CDF Player or Mathematica.