Validate a cohort table input.
Usage
validateCohortArgument(
cohort,
checkEndAfterStart = FALSE,
checkOverlappingEntries = FALSE,
checkMissingValues = FALSE,
checkInObservation = FALSE,
checkAttributes = FALSE,
dropExtraColumns = FALSE,
validation = "error",
call = parent.frame()
)
Arguments
- cohort
Object to be validated as a valid cohort input.
- checkEndAfterStart
If TRUE a check that all cohort end dates come on or after cohort start date will be performed.
- checkOverlappingEntries
If TRUE a check that no individuals have overlapping cohort entries will be performed.
- checkMissingValues
If TRUE a check that there are no missing values in required fields will be performed.
- checkInObservation
If TRUE a check that cohort entries are within the individuals observation periods will be performed.
- checkAttributes
Whether to check if attributes are present and populated correctly.
- dropExtraColumns
Whether to drop extra columns that are not the required ones.
- validation
How to perform validation: "error", "warning".
- call
A call argument to pass to cli functions.
Examples
cdm <- cdmFromTables(
tables = list(
"person" = dplyr::tibble(
person_id = c(1, 2, 3), gender_concept_id = 0, year_of_birth = 1990,
race_concept_id = 0, ethnicity_concept_id = 0
),
"observation_period" = dplyr::tibble(
observation_period_id = 1:3, person_id = 1:3,
observation_period_start_date = as.Date("2000-01-01"),
observation_period_end_date = as.Date("2023-12-31"),
period_type_concept_id = 0
)
),
cohortTables = list(
cohort = dplyr::tibble(
cohort_definition_id = 1L,
subject_id = 1L,
cohort_start_date = as.Date("2020-01-01"),
cohort_end_date = as.Date("2021-02-10")
)
),
cdmName = "mock"
)
validateCohortArgument(cdm$cohort)
#> # A tibble: 1 × 4
#> cohort_definition_id subject_id cohort_start_date cohort_end_date
#> <int> <int> <date> <date>
#> 1 1 1 2020-01-01 2021-02-10