Confidence intervals for post-test probability.
Confidence intervals are a natural way to describe the uncertainty of post-test probability in diagnostic tests. We consider confidence intervals for two different scenarios. At a site, for example, hospital emergency room or student health centre, with measured values of disease prevalence, sensitivity and specificity available, the confidence interval is similar to results in the literature, but at a site where measured values of these indices are unavailable, we develop a method, using the values of disease prevalence, sensitivity and specificity from other sites, to obtain a confidence interval for post-test probability. We use the diagnosis of strep throat to illustrate the results. We also obtain confidence intervals from simulations to compare with the results of both scenarios.
Monsour
M J
MJ
Department of Biostatistics, School of Public Health, University of North Carolina, Chapel Hill 27514.
Evans
A T
AT
Kupper
L L
LL
D000328:Adult; D001499:Bayes Theorem; D019411:Clinical Laboratory Techniques / Q000706:statistics & numerical data*; D016001:Confidence Intervals; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D010612:Pharyngitis / Q000175:diagnosis / Q000453:epidemiology; D011237:Predictive Value of Tests; D015995:Prevalence; D011336:Probability; D012680:Sensitivity and Specificity; D013290:Streptococcal Infections / Q000175:diagnosis / Q000453:epidemiology