Man pages for OHDSI/PatientLevelPrediction
Package for patient level prediction using data in the OMOP Common Data Model

accuracyCalculate the accuracy
applyModelApply train model on new data Apply a Patient Level...
averagePrecisionCalculate the average precision
bySumFfCompute sum of values binned by a second variable
checkPlpInstallationCheck PatientLevelPrediction and its dependencies are...
computeAucCompute the area under the ROC curve
computeAucFromDataFramesCompute the area under the ROC curve
createCohortcreateCohort - Loads all the cohort sql in a network study...
createExistingModelSqlApply an existing logistic regression prediction model
createLrSqlConvert logistic regression model to sql code...
createStudyPopulationCreate a study population
diagnosticOddsRatioCalculate the diagnostic odds ratio
drawAttritionDiagramPlpDraw the attrition diagram
exportPlpDataToCsvExport all data in a plpData object to CSV files
exportPlpResultexportPlpResult exports an object returned by runPlp into a...
externalValidatePlpexternalValidatePlp - Validate a model on new databases
f1ScoreCalculate the f1Score
falseDiscoveryRateCalculate the falseDiscoveryRate
falseNegativeRateCalculate the falseNegativeRate
falseOmissionRateCalculate the falseOmissionRate
falsePositiveRateCalculate the falsePositiveRate
fitGLMModelFit a predictive model
getAttritionTableGet the attrition table for a population
getCalibrationGet a sparse summary of the calibration
getCovariateDataGet the covaridate data for a cohort table
getModelDetailsGet the predictive model details
getPlpDataGet the patient level prediction data from the server
getPlpTableCreate a dataframe with the summary details of the population...
getPredictionDistributionCalculates the prediction distribution
getThresholdSummaryCalculate all measures for sparse ROC
grepCovariateNamesExtract covariate names
insertDbPopulationInsert a population into a database
interpretInstallCodeTells you the package issue
loadPlpDataLoad the cohort data from a folder
loadPlpModelloads the plp model
loadPlpResultLoads the evalaution dataframe
loadPredictionLoads the prediciton dataframe to csv
negativeLikelihoodRatioCalculate the negativeLikelihoodRatio
negativePredictiveValueCalculate the negativePredictiveValue
packageResultsPackage the results for sharing with OHDSI researchers
personSplitterSplit data into random subsets stratified by class
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
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,...
plotRocPlot the ROC curve
plotSparseCalibrationPlot the calibration
plotSparseCalibration2Plot the conventional calibration
plotSparseRocPlot the ROC curve using the sparse thresholdSummary data...
plotVariableScatterplotPlot the variable importance scatterplot
plpDataSimulationProfileA simulation profile
positiveLikelihoodRatioCalculate the positiveLikelihoodRatio
positivePredictiveValueCalculate the positivePredictiveValue
predictFfdfGenerated predictions from a regression model
predictProbabilitiesCreate predictive probabilities
runPlprunPlp - Train and evaluate the model
savePlpDataSave the cohort data to folder
savePlpModelSaves the plp model
savePlpResultSaves the result from runPlp into the location directory
savePredictionSaves the prediction dataframe to csv
sensitivityCalculate the sensitivity
setAdaBoostCreate setting for AdaBoost with python
setCIReNNCreate setting for CIReNN model
setCovNNCreate setting for multi-resolution CovNN model (stucture...
setCovNN2Create setting for CovNN2 model - convolution across input...
setDecisionTreeCreate setting for DecisionTree with python
setDeepNNCreate setting for DeepNN model
setGradientBoostingMachineCreate setting for gradient boosting machine model using...
setKNNCreate setting for knn model
setLassoLogisticRegressionCreate setting for lasso logistic regression
setMLPCreate setting for neural network model with python
setNaiveBayesCreate setting for naive bayes model with python
setRandomForestCreate setting for random forest model with python (very...
similarPlpDataExtract new plpData using plpModel settings use metadata in...
simulatePlpDataGenerate simulated data
specificityCalculate the specificity
standardOutputstandardOutput - takes the output of runPlp or evaluatePlp...
submitResultssubmitResults - sends a zipped folder to the OHDSI network...
timeSplitterSplit test/train data by time and then partitions training...
toPlpDataConvert matrix into plpData
toSparseMConvert the plpData in COO format into a sparse R matrix
toSparsePythonConvert the plpData in COO format into a sparse python matrix
transportModelTransports a plpModel to a new location and removes sensitive...
transportPlpTransports a plpResult to a new location and removed...
viewPlpviewPlp - Interactively view the performance and model...
OHDSI/PatientLevelPrediction documentation built on July 16, 2018, 7:04 a.m.