execute: Execute the Study
In mi-erasmusmc/CovCoagEmaPrediction: Coagulopathy prediction in SARS-Cov-2

Description Usage Arguments Details Examples

Execute the Study

execute(
  connectionDetails,
  cdmDatabaseSchema,
  cdmDatabaseName = "friendly database name",
  cohortDatabaseSchema = cdmDatabaseSchema,
  cohortTable = "cohort",
  oracleTempSchema = cohortDatabaseSchema,
  outputFolder,
  createProtocol = F,
  createCohorts = F,
  runDiagnostic = F,
  viewDiagnostic = F,
  runAnalyses = F,
  createResultsDoc = F,
  createValidationPackage = F,
  saveModelsToJson = T,
  skeletonVersion = "v0.0.1",
  analysesToValidate = NULL,
  packageResults = F,
  minCellCount = 5,
  createShiny = F,
  createJournalDocument = F,
  analysisIdDocument = 1,
  onlyFetchData = F,
  sampleSize = NULL,
  verbosity = "INFO",
  cdmVersion = 5
)

`connectionDetails`	An object of type `connectionDetails` as created using the `createConnectionDetails` function in the DatabaseConnector package.
`cdmDatabaseSchema`	Schema name where your patient-level data in OMOP CDM format resides. Note that for SQL Server, this should include both the database and schema name, for example 'cdm_data.dbo'.
`cdmDatabaseName`	Shareable name of the database
`cohortDatabaseSchema`	Schema name where intermediate data can be stored. You will need to have write priviliges in this schema. Note that for SQL Server, this should include both the database and schema name, for example 'cdm_data.dbo'.
`cohortTable`	The name of the table that will be created in the work database schema. This table will hold the target population cohorts used in this study.
`oracleTempSchema`	Should be used in Oracle to specify a schema where the user has write priviliges for storing temporary tables.
`outputFolder`	Name of local folder to place results; make sure to use forward slashes (/). Do not use a folder on a network drive since this greatly impacts performance.
`createProtocol`	Creates a protocol based on the analyses specification
`createCohorts`	Create the cohortTable table with the target population and outcome cohorts?
`runDiagnostic`	Runs a diagnostic of the T, O and tar settings for the cdmDatabaseSchema - can be used to check whether to change settings or whether the prediction may not do well.
`viewDiagnostic`	Opens a shiny app with the diagnostic results (run after runDiagnostic completes)
`runAnalyses`	Run the model development
`createResultsDoc`	Create a document containing the results of each prediction
`createValidationPackage`	Create a package for sharing the models
`saveModelsToJson`	Whether to save the models as json for validation (not all models are supported)
`skeletonVersion`	The version of the validation skeleton to use
`analysesToValidate`	A vector of analysis ids (e.g., c(1,3,10)) specifying which analysese to export into validation package. Default is NULL and all are exported.
`packageResults`	Should results be packaged for later sharing?
`minCellCount`	The minimum number of subjects contributing to a count before it can be included in packaged results.
`createShiny`	Create a shiny app with the results
`createJournalDocument`	Do you want to create a template journal document populated with results?
`analysisIdDocument`	Which Analysis_id do you want to create the document for?
`onlyFetchData`	Only fetch data for the analyses without fitting models. Setting this flag will overwrite your input provided to the runAnalyses and createCohorts parameters.
`sampleSize`	The number of patients in the target cohort to sample (if NULL uses all patients)
`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: DEBUGHighest verbosity showing all debug statements TRACEShowing information about start and end of steps INFOShow informative information (Default) WARNShow warning messages ERRORShow error messages FATALBe silent except for fatal errors
`cdmVersion`	The version of the common data model

This function executes the CovCoagEmaPrediction Study.

## Not run: 
connectionDetails <- createConnectionDetails(dbms = "postgresql",
                                             user = "joe",
                                             password = "secret",
                                             server = "myserver")

execute(connectionDetails,
        cdmDatabaseSchema = "cdm_data",
        cdmDatabaseName = 'shareable name of the database'
        cohortDatabaseSchema = "study_results",
        cohortTable = "cohort",
        oracleTempSchema = NULL,
        outputFolder = "c:/temp/study_results", 
        createProtocol = T,
        createCohorts = T,
        runDiagnostic = F,
        viewDiagnostic = F,
        runAnalyses = T,
        createResultsDoc = T,
        createValidationPackage = T,
        saveModelsToJson = T,
        skeletonVersion = 'v1.0.1',
        packageResults = F,
        minCellCount = 5,
        createShiny = F,
        sampleSize = 10000,
        verbosity = "INFO",
        cdmVersion = 5)

## End(Not run)