predvalPlot: Plot positive and negative predictive values across different...

In MetaIntegrator: Meta-Analysis of Gene Expression Data

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)

MetaIntegrator documentation built on March 26, 2020, 6:29 p.m.