externalValidateDbPlp - Validate a model on new databases

This function extracts data using a user specified connection and cdm_schema, applied the model and then calcualtes the performance

Usage

externalValidateDbPlp(
  plpModel,
  validationDatabaseDetails = createDatabaseDetails(),
  validationRestrictPlpDataSettings = createRestrictPlpDataSettings(),
  settings = createValidationSettings(recalibrate = "weakRecalibration"),
  logSettings = createLogSettings(verbosity = "INFO", logName = "validatePLP"),
  outputFolder = NULL
)

Arguments

plpModel

The model object returned by runPlp() containing the trained model

validationDatabaseDetails

A list of objects of class databaseDetails created using createDatabaseDetails

validationRestrictPlpDataSettings

A list of population restriction settings created by createRestrictPlpDataSettings()

settings

A settings object of class validationSettings created using createValidationSettings

logSettings

An object of logSettings created using createLogSettings specifying how the logging is done

outputFolder

The directory to save the validation results to (subfolders are created per database in validationDatabaseDetails)

Value

An externalValidatePlp object containing the following components

• model: The model object

• executionSummary: A list of execution details

• prediction: A dataframe containing the predictions

• performanceEvaluation: A dataframe containing the performance metrics

• covariateSummary: A dataframe containing the covariate summary

Details

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

Examples