PatientLevelPrediction (version 6.4.1)

plotGeneralizability: Plot the train/test generalizability diagnostic

Description

Plot the train/test generalizability diagnostic

Usage

plotGeneralizability(
  covariateSummary,
  saveLocation = NULL,
  fileName = "Generalizability.png"
)

Value

A ggplot object. Use the ggsave function to save to file in a different format.

Arguments

covariateSummary

A prediction object as generated using the runPlp function.

saveLocation

Directory to save plot (if NULL plot is not saved)

fileName

Name of the file to save to plot, for example 'plot.png'. See the function ggsave in the ggplot2 package for supported file formats.

Details

Create a plot showing the train/test generalizability diagnostic #'

Examples

  # takes too long 
data("simulationProfile")
plpData <- simulatePlpData(simulationProfile, n=1000)
population <- createStudyPopulation(plpData, outcomeId = 3)
data <- splitData(plpData, population = population)
strata <- data.frame(
 rowId = c(data$Train$labels$rowId, data$Test$labels$rowId),
 strataName = c(rep("Train", nrow(data$Train$labels)),
                rep("Test", nrow(data$Test$labels))))
covariateSummary <- covariateSummary(plpData$covariateData, 
                                     cohort = dplyr::select(population, "rowId"),
 strata = strata, labels = population)
plotGeneralizability(covariateSummary)