A function to extract non-case and case continuous characterization results

A function to extract non-case and case continuous characterization results

Usage

getContinuousRiskFactors(
  connectionHandler,
  schema,
  cTablePrefix = "c_",
  cgTablePrefix = "cg_",
  databaseTable = "database_meta_data",
  targetId = NULL,
  outcomeId = NULL,
  analysisIds = NULL
)

Arguments

connectionHandler

A connection handler that connects to the database and extracts sql queries. Create a connection handler via `ResultModelManager::ConnectionHandler$new()`.

schema

The result database schema (e.g., 'main' for sqlite)

cTablePrefix

The prefix used for the characterization results tables

cgTablePrefix

The prefix used for the cohort generator results tables

databaseTable

The name of the table with the database details (default 'database_meta_data')

targetId

An integer corresponding to the target cohort ID

outcomeId

Am integer corresponding to the outcome cohort ID

analysisIds

The feature extraction analysis ID of interest (e.g., 201 is condition)

Value

A data.frame with the characterization results for the cases and non-cases

Details

Specify the connectionHandler, the schema and the target/outcome cohort IDs

See also

Other Characterization: getBinaryCaseSeries(), getBinaryRiskFactors(), getCaseBinaryFeatures(), getCaseContinuousFeatures(), getCaseCounts(), getCharacterizationDemographics(), getContinuousCaseSeries(), getDechallengeRechallenge(), getIncidenceRates(), getTargetBinaryFeatures(), getTargetContinuousFeatures(), getTargetCounts(), getTimeToEvent(), plotAgeDistributions(), plotSexDistributions()

Examples

conDet <- getExampleConnectionDetails()

connectionHandler <- ResultModelManager::ConnectionHandler$new(conDet)
#> Connecting using SQLite driver

rf <- getContinuousRiskFactors(
  connectionHandler = connectionHandler, 
  schema = 'main',
  targetId = 1, 
  outcomeId = 3
)