predValues | R Documentation |
The function computes the positive (PPV) and negative predictive value (NPV) given sensitivity, specificity and prevalence (pre-test probability).
predValues(sens, spec, prev)
sens |
numeric vector: sensitivities. |
spec |
numeric vector: specificities. |
prev |
numeric vector: prevalence. |
The function computes the positive (PPV) and negative predictive value (NPV) given sensitivity, specificity and prevalence (pre-test probability).
It's a simple application of the Bayes formula.
One can also specify vectors of length larger than 1 for sensitivity and specificity.
Vector or matrix with PPV and NPV.
Matthias Kohl Matthias.Kohl@stamats.de
## Example: HIV test ## 1. ELISA screening test (4th generation) predValues(sens = 0.999, spec = 0.998, prev = 0.001) ## 2. Western-Plot confirmation test predValues(sens = 0.998, spec = 0.999996, prev = 1/3) ## Example: connection between sensitivity, specificity and PPV sens <- seq(0.6, 0.99, by = 0.01) spec <- seq(0.6, 0.99, by = 0.01) ppv <- function(sens, spec, pre) predValues(sens, spec, pre)[,1] res <- outer(sens, spec, ppv, pre = 0.1) image(sens, spec, res, col = terrain.colors(256), main = "PPV for prevalence = 10%", xlim = c(0.59, 1), ylim = c(0.59, 1)) contour(sens, spec, res, add = TRUE)
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