R/ExternalValidatePlp.R
externalValidatePlp.Rd
This function extracts data using a user specified connection and cdm_schema, applied the model and then calcualtes the performance
externalValidatePlp( plpResult, connectionDetails, validationSchemaTarget, validationSchemaOutcome, validationSchemaCdm, databaseNames, validationTableTarget = "cohort", validationTableOutcome = "cohort", validationIdTarget = NULL, validationIdOutcome = NULL, oracleTempSchema = NULL, verbosity = "INFO", keepPrediction = F, recalibrate = NULL, sampleSize = NULL, outputFolder )
plpResult | The object returned by runPlp() containing the trained model |
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connectionDetails | The connection details for extracting the new data |
validationSchemaTarget | A string or vector of strings specifying the database containing the target cohorts |
validationSchemaOutcome | A string or vector of strings specifying the database containing the outcome cohorts |
validationSchemaCdm | A string or vector of strings specifying the database containing the cdm |
databaseNames | A string of vector of strings specifying sharing friendly database names corresponding to validationSchemaCdm |
validationTableTarget | A string or vector of strings specifying the table containing the target cohorts |
validationTableOutcome | A string or vector of strings specifying the table containing the outcome cohorts |
validationIdTarget | An iteger specifying the cohort id for the target cohort |
validationIdOutcome | An iteger specifying the cohort id for the outcome cohort |
oracleTempSchema | The temp oracle schema requires read/write |
verbosity | Sets the level of the verbosity. If the log level is at or higher in priority than the logger threshold, a message will print. The levels are:
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keepPrediction | Whether to keep the predicitons for the new data |
recalibrate | A vector of characters specifying the recalibration method to apply |
sampleSize | If not NULL, the number of people to sample from the target cohort |
outputFolder | If you want to save the results enter the directory to save here |
A list containing the performance for each validation_schema
Users need to input a trained model (the output of runPlp()) and new database connections. The function will return a list of length equal to the number of cdm_schemas input with the performance on the new data