Plots the sex distributions using the sex features

Creates bar charts for the target and case sex.

Usage

plotSexDistributions(
  sexData,
  riskWindowStart = "1",
  riskWindowEnd = "365",
  startAnchor = "cohort start",
  endAnchor = "cohort start"
)

Arguments

sexData

The sex data extracted using 'getCharacterizationDemographics(type = 'sex')'

riskWindowStart

The time at risk window start

riskWindowEnd

The time at risk window end

startAnchor

The anchor for the time at risk start

endAnchor

The anchor for the time at risk end

Value

Returns a ggplot with the distributions

Details

Input the data returned from 'getCharacterizationDemographics(type = 'sex')' and the time-at-risk

See also

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

Examples

conDet <- getExampleConnectionDetails()

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

sexData <- getCharacterizationDemographics(
  connectionHandler = connectionHandler, 
  schema = 'main',
  targetId = 1, 
  outcomeId = 3, 
  type = 'sex'
)
plotSexDistributions(sexData = sexData)

#> Closing database connection
#> Closing database connection
#> Closing database connection
#> Closing database connection