classificationplots: Generate plots for classification

In mathijsdeen/mdmaTools: Mathijs Deen's Miscellaneous Additional Tools

Description

Generate plots for classification of two groups given one continuous variable

Usage

classificationplots(
  response,
  outcome,
  levels,
  cutoffs.1 = NULL,
  cutoffs.2 = NULL,
  cutoffs.3 = NULL,
  xlab.3 = "Predicted probability",
  labels.3 = NULL,
  xlim.3 = NULL,
  ylim.3 = c(0, 10),
  pos.legend.2 = "right",
  pos.legend.3 = "topright"
)

Arguments

response	continuous variable that is used as a classifier
outcome	grouping variable
levels	levels of the grouping variable that are to be classified (should be of length 2)
cutoffs.1	cutoff values to be shown in the ROC curve
cutoffs.2	cutoff values to be shown in the sensitivity/specificity plot
cutoffs.3	cutoff values to be shown in the conditional distribution plot
xlab.3	label for x axis in conditional distribution plot
labels.3	legend labels for both groups in levels in conditional distribution plot
xlim.3	xlim for conditional distribution plot
ylim.3	ylim for conditional distribution plot
pos.legend.2	location for legend in sensitivity/specificity plot
pos.legend.3	location for legend in conditional distribution plot

Value

classificationplots returns three plots, and invisibly a dataframe containing sensitivities and specificities at all available threshold values.

Author(s)

Mathijs Deen

Examples

library(pROC)
classificationplots(aSAH$s100b,aSAH$outcome,levels=c("Good","Poor"))

mathijsdeen/mdmaTools documentation built on Dec. 21, 2021, 2:52 p.m.