ROCplots: ROCplots

In professorbeautiful/NNTbiomarkerHome: Calculate Design Parameters for Biomarker Validation Studies

Description

A variety of ROC-related plots for a binary target and a single continuous predictor.

Usage

ROCplots(data, whichPlots = c("density", "raw", "ROC", "pv", "nnt",
  "nntRange"), NNTlower = 3, NNTupper = 10, N = 1000, prev = 0.2,
  diffInSD = 2, ...)

Arguments

data	Data frame with columns "class" (binary target variable) and "X" (predictor).
whichPlots	Which plots to do. Options are c("density", "raw", "ROC", "pv", "nnt")
NNTlower	Subjective input. If NNT < NNTlower, the decision is clearly to Treat.
NNTupper	Subjective input. If NNT > NNTupper, the decision is clearly to Wait.
N	For simulated data: sample size
prev	For simulated data: Prevalence
diffInSD	For simulated data: Difference: E(X | group=1) - E(X | group=0),measured in units of S.D (common to the 2 groups).
...	Extra arguments for a plot. Do not supply unless length(whichPlots)==1.

Details

The plots display the values achievable by changing the cutoff, in comparison with the desired values as determined by NNTlower and NNTupper. The "whichPlots" options are as follows:

• "density"Marginal density of X, with rug.

• "raw"X versus class.

• "ROC"Standard ROC curve.

• "pv"Plot of ppv versus npv, with indication of the acceptable range for cutoff.

• "nnt"Plot of NNTpos versus NNTneg, with indication of the acceptable region

• "nntRange"Plot of NNTpos and NNTneg versus cutoff, with indication of the acceptable range.

  By default, all the plots are made.

professorbeautiful/NNTbiomarkerHome documentation built on June 7, 2019, 8:28 a.m.