| predvalPlot {MetaIntegrator} | R Documentation |
Plot positive and negative predictive values across different prevalences
Description
Positive and negative predictive values (PPV and NPV) are two diagnostic statistics that change depending on the prevalence, so if you don't have a discrete prevalence to work with this function can create a plot that shows the positive and negative predictive values across all possible prevalences (as long as you have already calculated the sensitivity and specificity).
Usage
predvalPlot(sens, spec, nsteps=1000, title=NULL, rounding=2)
Arguments
sens |
the sensitivity of the prediction |
spec |
the specificity of the prediction |
nsteps |
the number of steps between prevalence 0% and 100% (i.e. the number of steps in the X-axis) (default: 1000) |
title |
title of the plot (if left blank, it will just indicate the input sensitivity and specificity) |
rounding |
number of significant digits for displaying the sensitivity, specificity, PPV, and NPV (default: 2) |
Value
Plotly plot of predictive values vs. prevalence
Author(s)
Lara Murphy, Aditya M. Rao
Examples
predvalPlot(sens = 0.9, spec = 0.8)