MedDiagn: Computes the posterior probability of having a certain disease from
prevalence, sensitivity, and specificity data.
Description
If experimental data on the sensitivity and the specificity
of a diagnostic test are available, and the prevalence of the the
condition is known with its raw data, then this function estimates
the posterior probability of having the condition, with its 95%
credible interval.
Usage
MedDiagn(x0, n0, x1, n1, x2, n2, N = 10000,
alpha = 0.05, pdf = FALSE)
Arguments
x0
prevalence raw data: number of people with a certain condition
n0
number of people examined for that condition
x1
sensitivity data: number of people with the disease for whom this test was positive
n1
total number of people in the sensitivity sample
x2
specificity raw data: number of people who did not have the disease who
tested negative
n2
total number of people in the specificity sample
N
number of cases to be simulated (best left at 10000 or greater
alpha
credibility required (default 95%)
pdf
set this to TRUE only if you want to keep a pdf-file of the posterior
probability plot
Value
none returned: a plot and printed information are produced
References
van Hulst, R. 2018. Evaluating Scientific Evidence. ms.