Man pages for OHDSI/PatientLevelPrediction
Develop Clinical Prediction Models Using the Common Data Model

averagePrecisionCalculate the average precision
brierScorebrierScore
calibrationInLargeCalculate the calibration in large
calibrationLinecalibrationLine
computeAucCompute the area under the ROC curve
computeGridPerformanceComputes grid performance with a specified performance...
configurePythonSets up a python environment to use for PLP (can be conda or...
covariateSummarycovariateSummary
createCohortCovariateSettingsExtracts covariates based on cohorts
createDatabaseDetailsCreate a setting that holds the details about the cdmDatabase...
createDatabaseSchemaSettingsCreate the PatientLevelPrediction database result schema...
createDefaultExecuteSettingsCreates default list of settings specifying what parts of...
createDefaultSplitSettingCreate the settings for defining how the plpData are split...
createExecuteSettingsCreates list of settings specifying what parts of runPlp to...
createExistingSplitSettingsCreate the settings for defining how the plpData are split...
createFeatureEngineeringSettingsCreate the settings for defining any feature engineering that...
createGlmModelcreateGlmModel
createIterativeImputerCreate Iterative Imputer settings
createLearningCurvecreateLearningCurve
createLogSettingsCreate the settings for logging the progression of the...
createModelDesignSpecify settings for developing a single model
createNormalizerCreate the settings for normalizing the data @param type The...
createPlpResultTablesCreate the results tables to store PatientLevelPrediction...
createPreprocessSettingsCreate the settings for preprocessing the trainData.
createRandomForestFeatureSelectionCreate the settings for random foreat based feature selection
createRareFeatureRemoverCreate the settings for removing rare features
createRestrictPlpDataSettingscreateRestrictPlpDataSettings define extra restriction...
createSampleSettingsCreate the settings for defining how the trainData from...
createSimpleImputerCreate Simple Imputer settings
createSklearnModelPlug an existing scikit learn python model into the PLP...
createSplineSettingsCreate the settings for adding a spline for continuous...
createStratifiedImputationSettingsCreate the settings for using stratified imputation.
createStudyPopulationCreate a study population
createStudyPopulationSettingscreate the study population settings
createTempModelLocCreate a temporary model location
createUnivariateFeatureSelectionCreate the settings for defining any feature selection that...
createValidationDesigncreateValidationDesign - Define the validation design for...
createValidationSettingscreateValidationSettings define optional settings for...
diagnoseMultiplePlpRun a list of predictions diagnoses
diagnosePlpdiagnostic - Investigates the prediction problem settings -...
evaluatePlpevaluatePlp
externalValidateDbPlpexternalValidateDbPlp - Validate a model on new databases
extractDatabaseToCsvExports all the results from a database into csv files
fitPlpfitPlp
getCalibrationSummaryGet a sparse summary of the calibration
getCohortCovariateDataExtracts covariates based on cohorts
getDemographicSummaryGet a demographic summary
getEunomiaPlpDataCreate a plpData object from the Eunomia database'
getPlpDataExtract the patient level prediction data from the server
getPredictionDistributionCalculates the prediction distribution
getPredictionDistribution_binaryCalculates the prediction distribution
getThresholdSummaryCalculate all measures for sparse ROC
iciCalculate the Integrated Calibration Index from Austin and...
insertCsvToDatabaseFunction to insert results into a database from csvs
insertResultsToSqliteCreate sqlite database with the results
iterativeImputeImputation
listAppendjoin two lists
listCartesianCartesian product
loadPlpAnalysesJsonLoad the multiple prediction json settings from a file
loadPlpDataLoad the plpData from a folder
loadPlpModelloads the plp model
loadPlpResultLoads the evalaution dataframe
loadPlpShareableLoads the plp result saved as json/csv files for transparent...
loadPredictionLoads the prediction dataframe to json
MapIdsMap covariate and row Ids so they start from 1
migrateDataModelMigrate Data model
minMaxNormalizeA function that normalizes continous features to have values...
modelBasedConcordanceCalculate the model-based concordance, which is a calculation...
outcomeSurvivalPlotPlot the outcome incidence over time
PatientLevelPredictionPatientLevelPrediction
pfiPermutation Feature Importance
plotDemographicSummaryPlot the Observed vs. expected incidence, by age and gender
plotF1MeasurePlot the F1 measure efficiency frontier using the sparse...
plotGeneralizabilityPlot the train/test generalizability diagnostic
plotLearningCurveplotLearningCurve
plotNetBenefitPlot the net benefit
plotPlpPlot all the PatientLevelPrediction plots
plotPrecisionRecallPlot the precision-recall curve using the sparse...
plotPredictedPDFPlot the Predicted probability density function, showing...
plotPredictionDistributionPlot the side-by-side boxplots of prediction distribution, by...
plotPreferencePDFPlot the preference score probability density function,...
plotSmoothCalibrationPlot the smooth calibration as detailed in Calster et al. "A...
plotSparseCalibrationPlot the calibration
plotSparseCalibration2Plot the conventional calibration
plotSparseRocPlot the ROC curve using the sparse thresholdSummary data...
plotVariableScatterplotPlot the variable importance scatterplot
pmmFitPredictive mean matching using lasso
predictCyclopsCreate predictive probabilities
predictGlmpredict using a logistic regression model
predictPlppredictPlp
preprocessDataA function that wraps around...
print.plpDataPrint a plpData object
print.summary.plpDataPrint a summary.plpData object
recalibratePlprecalibratePlp
recalibratePlpRefitrecalibratePlpRefit
removeRareFeaturesA function that removes rare features from the data
robustNormalizeA function that normalizes continous by the interquartile...
runMultiplePlpRun a list of predictions analyses
runPlprunPlp - Develop and internally evaluate a model using...
savePlpAnalysesJsonSave the modelDesignList to a json file
savePlpDataSave the plpData to folder
savePlpModelSaves the plp model
savePlpResultSaves the result from runPlp into the location directory
savePlpShareableSave the plp result as json files and csv files for...
savePredictionSaves the prediction dataframe to a json file
setAdaBoostCreate setting for AdaBoost with python...
setCoxModelCreate setting for lasso Cox model
setDecisionTreeCreate setting for the scikit-learn DecisionTree with python
setGradientBoostingMachineCreate setting for gradient boosting machine model using...
setIterativeHardThresholdingCreate setting for Iterative Hard Thresholding model
setLassoLogisticRegressionCreate modelSettings for lasso logistic regression
setLightGBMCreate setting for gradient boosting machine model using...
setMLPCreate setting for neural network model with python's...
setNaiveBayesCreate setting for naive bayes model with python
setPythonEnvironmentUse the python environment created using configurePython()
setRandomForestCreate setting for random forest model using sklearn
setSVMCreate setting for the python sklearn SVM (SVC function)
simpleImputeSimple Imputation
simulatePlpDataGenerate simulated data
simulationProfileA simulation profile for generating synthetic patient level...
sklearnFromJsonLoads sklearn python model from json
sklearnToJsonSaves sklearn python model object to json in path
splitDataSplit the plpData into test/train sets using a splitting...
summary.plpDataSummarize a plpData object
toSparseMConvert the plpData in COO format into a sparse R matrix
validateExternalvalidateExternal - Validate model performance on new data
validateMultiplePlpexternally validate the multiple plp models across new...
viewDatabaseResultPlpopen a local shiny app for viewing the result of a PLP...
viewMultiplePlpopen a local shiny app for viewing the result of a multiple...
viewPlpviewPlp - Interactively view the performance and model...
OHDSI/PatientLevelPrediction documentation built on Feb. 14, 2025, 9:44 a.m.