Estimate the true prevalence, as well as positive
and negative predictive values and
likelihood ratios from
survey testing results using a test of known
Confidence limits for both apparent and true prevalence estimates are calculated.
Values are also plotted for a range of possible survey results.
Confidence limits for apparent prevalence use methods
Brown, LD, Cat, TT and DasGupta, A (2001). Interval Estimation for a proportion.
Statistical Science 16:101-133.
True prevalence estimates are calculated as described by:
Rogan and Gladen (1978). Estimating prevalence from the results of a screening test.
American Journal of Epidemiology 107:71-76.
True prevalence estimates
that are less than zero or greater than one are not consistent with assumed sensitivity
and specificity values, and are indicated by '<0' and '>1', respectively.
Confidence limit calculations assume
sensitivity and specificity are known exactly. The normal approximation method uses
the formula described by Greiner, M
and Gardner, IA (2000). Application of diagnostic tests in epidemiologic studies.
Preventive Veterinary Medicine 45:43-59.
Blaker's, Sterne, Clopper-Pearson and Wilson confidence limits are
calculated as described by Reiczigel, Földi and Ózsvári (2010). Exact confidence limits for
prevalence of a disease with an imperfect diagnostic test,
Epidemiology and Infection 138:1674-1678. The authors recommend Blaker's interval for general use.