MKmisc (version 1.9)

predValues: Compute PPV and NPV.

Description

The function computes the positive (PPV) and negative predictive value (NPV) given sensitivity, specificity and prevalence (pre-test probability).

Usage

predValues(sens, spec, prev)

Value

Vector or matrix with PPV and NPV.

Arguments

sens

numeric vector: sensitivities.

spec

numeric vector: specificities.

prev

numeric vector: prevalence.

Author

Matthias Kohl

Details

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.

Examples

## 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)