Extract aggregate statistics of binary feature analysis IDs of interest for targets

This function extracts the feature extraction results for targets corresponding to specified target and outcome cohorts.

Usage

getTargetBinaryFeatures(
  connectionHandler,
  schema,
  cTablePrefix = "c_",
  cgTablePrefix = "cg_",
  databaseTable = "database_meta_data",
  targetIds = NULL,
  outcomeIds = NULL,
  analysisIds = c(3)
)

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')

targetIds

A vector of integers corresponding to the target cohort IDs

outcomeIds

A vector of integers corresponding to the outcome cohort IDs

analysisIds

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

Value

Returns a data.frame with the columns:

• databaseName the name of the database

• targetName the target cohort name

• targetId the target cohort unique identifier

• outcomeName the outcome name

• outcomeId the outcome unique identifier

• minPriorObservation the minimum required observation days prior to index for an entry

• outcomeWashoutDays patients with the outcome occurring within this number of days prior to index are excluded (NA means no exclusion)

• covariateName the name of the feature

• sumValue the number of cases who have the feature value of 1

Details

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

See also

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

Examples

conDet <- getExampleConnectionDetails()

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

tbf <- getTargetBinaryFeatures (
connectionHandler = connectionHandler, 
schema = 'main'
)