evaluatePlp: evaluatePlp

In OHDSI/PatientLevelPrediction: Develop Clinical Prediction Models Using the Common Data Model

evaluatePlp

Description

Evaluates the performance of the patient level prediction model

Usage

evaluatePlp(prediction, typeColumn = "evaluationType")

Arguments

prediction	The patient level prediction model's prediction
typeColumn	The column name in the prediction object that is used to stratify the evaluation

Details

The function calculates various metrics to measure the performance of the model

Value

An object of class plpEvaluation containing the following components

• evaluationStatistics: A data frame containing the evaluation statistics'

• thresholdSummary: A data frame containing the threshold summary'

• demographicSummary: A data frame containing the demographic summary'

• calibrationSummary: A data frame containing the calibration summary'

• predictionDistribution: A data frame containing the prediction distribution'

Examples

 
data("simulationProfile")
plpData <- simulatePlpData(simulationProfile, n= 1500)
population <- createStudyPopulation(plpData, outcomeId = 3, 
                                    populationSettings = createStudyPopulationSettings())
data <- splitData(plpData, population, splitSettings=createDefaultSplitSetting(splitSeed=42))
data$Train$covariateData <- preprocessData(data$Train$covariateData, 
                                           createPreprocessSettings())
path <- file.path(tempdir(), "plp")
model <- fitPlp(data$Train, modelSettings=setLassoLogisticRegression(seed=42),
                analysisId=1, analysisPath = path)
evaluatePlp(model$prediction) # Train and CV metrics

OHDSI/PatientLevelPrediction documentation built on Feb. 14, 2025, 9:44 a.m.