Apply train model on new data Apply a Patient Level Prediction model on Patient Level Prediction Data and get the predicted risk in [0,1] for each person in the population. If the user inputs a population with an outcomeCount column then the function also returns the evaluation of the prediction (AUC, brier score, calibration)

Apply train model on new data Apply a Patient Level Prediction model on Patient Level Prediction Data and get the predicted risk in [0,1] for each person in the population. If the user inputs a population with an outcomeCount column then the function also returns the evaluation of the prediction (AUC, brier score, calibration)

applyModel(
  population,
  plpData,
  plpModel,
  calculatePerformance = T,
  databaseOutput = NULL,
  silent = F
)

Arguments

population	The population of people who you want to predict the risk for
plpData	The plpData for the population
plpModel	The trained PatientLevelPrediction model
calculatePerformance	Whether to also calculate the performance metrics [default TRUE]
databaseOutput	Whether to save the details into the prediction database
silent	Whether to turn off progress reporting

Examples

if (FALSE) {
# load the model and data
plpData <- loadPlpData("C:/plpdata")
plpModel <- loadPlpModel("C:/plpmodel")

# use the same population settings as the model:
populationSettings <- plpModel$populationSettings
populationSettings$plpData <- plpData
population <- do.call(createStudyPopulation, populationSettings)

# get the prediction:
prediction <- applyModel(population, plpData, plpModel)$prediction
}