Tidy covariate data — tidyCovariateData • FeatureExtraction

Tidy covariate data

tidyCovariateData(
  covariateData,
  minFraction = 0.001,
  normalize = TRUE,
  removeRedundancy = TRUE
)

Arguments

covariateData: An object as generated using the getDbCovariateData function.
minFraction: Minimum fraction of the population that should have a non-zero value for a covariate for that covariate to be kept. Set to 0 to don't filter on frequency.
normalize: Normalize the covariates? (dividing by the max).
removeRedundancy: Should redundant covariates be removed?

Details

Normalize covariate values by dividing by the max and/or remove redundant covariates and/or remove infrequent covariates. For temporal covariates, redundancy is evaluated per time ID.

Examples

if (FALSE) {
covariateData <- FeatureExtraction:::createEmptyCovariateData(
  cohortIds = 1,
  aggregated = FALSE,
  temporal = FALSE
)

covData <- tidyCovariateData(
  covariateData = covariateData,
  minFraction = 0.001,
  normalize = TRUE,
  removeRedundancy = TRUE
)
}