MetaIntegrator (version 2.1.3)

predvalPlot: 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

Examples

# NOT RUN {
predvalPlot(sens = 0.9, spec = 0.8)
# }