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Extract the binary age groups for the cases and targets

Source: R/CharacterzationQueries.R
getCharacterizationDemographics.Rd

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

Usage

getCharacterizationDemographics(
  connectionHandler,
  schema,
  cTablePrefix = "c_",
  cgTablePrefix = "cg_",
  databaseTable = "database_meta_data",
  targetId = NULL,
  outcomeId = NULL,
  type = "age"
)

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

type

A character of 'age' or 'sex'

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)

  • riskWindowStart the number of days ofset the start anchor that is the start of the time-at-risk

  • startAnchor the start anchor is either the target cohort start or cohort end date

  • riskWindowEnd the number of days ofset the end anchor that is the end of the time-at-risk

  • endAnchor the end anchor is either the target cohort start or cohort end date

  • covariateName the name of the feature

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

  • averageValue the mean feature value

Details

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

See also

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

Examples

# example code

conDet <- getExampleConnectionDetails()

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

ageData <- getCharacterizationDemographics(
connectionHandler = connectionHandler, 
schema = 'main'
)