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Using generateSequenceCohortSet to obtain temporal symmetry (aggregated counts) of two cohorts.

Usage

summariseTemporalSymmetry(
  cohort,
  cohortId = NULL,
  timescale = "month",
  minCellCount = 5
)

Arguments

cohort

A cohort table in the cdm.

cohortId

The Ids in the cohort that are to be included in the analyses.

timescale

Timescale for the x axis of the plot (month, day, year).

minCellCount

The minimum number of events to reported, below which results will be obscured. If 0, all results will be reported.

Value

An aggregated table with difference in time (marker - index) and the relevant counts.

Examples

# \donttest{
library(CohortSymmetry)
cdm <- mockCohortSymmetry()
#> Warning: ! 9 column in cdm_source do not match expected column type:
#>  `cdm_source_abbreviation` is logical but expected character
#>  `cdm_holder` is logical but expected character
#>  `source_description` is logical but expected character
#>  `source_documentation_reference` is logical but expected character
#>  `cdm_etl_reference` is logical but expected character
#>  `source_release_date` is logical but expected date
#>  `cdm_release_date` is logical but expected date
#>  `cdm_version` is numeric but expected character
#>  `vocabulary_version` is logical but expected character
#> Warning: ! 3 column in concept do not match expected column type:
#>  `concept_id` is numeric but expected integer
#>  `valid_start_date` is character but expected date
#>  `valid_end_date` is character but expected date
#> Warning: ! 1 column in vocabulary do not match expected column type:
#>  `vocabulary_concept_id` is numeric but expected integer
#> Warning: ! 5 column in concept_relationship do not match expected column type:
#>  `concept_id_1` is numeric but expected integer
#>  `concept_id_2` is numeric but expected integer
#>  `valid_start_date` is logical but expected date
#>  `valid_end_date` is logical but expected date
#>  `invalid_reason` is logical but expected character
#> Warning: ! 2 column in concept_synonym do not match expected column type:
#>  `concept_id` is numeric but expected integer
#>  `language_concept_id` is numeric but expected integer
#> Warning: ! 4 column in concept_ancestor do not match expected column type:
#>  `ancestor_concept_id` is numeric but expected integer
#>  `descendant_concept_id` is numeric but expected integer
#>  `min_levels_of_separation` is numeric but expected integer
#>  `max_levels_of_separation` is numeric but expected integer
#> Warning: ! 9 column in drug_strength do not match expected column type:
#>  `drug_concept_id` is numeric but expected integer
#>  `ingredient_concept_id` is numeric but expected integer
#>  `amount_unit_concept_id` is numeric but expected integer
#>  `numerator_unit_concept_id` is numeric but expected integer
#>  `denominator_value` is logical but expected numeric
#>  `denominator_unit_concept_id` is numeric but expected integer
#>  `box_size` is numeric but expected integer
#>  `valid_start_date` is character but expected date
#>  `valid_end_date` is character but expected date
#> Warning: There are observation period end dates after the current date: 2024-10-30
#>  The latest max observation period end date found is 2026-10-26
#> Warning: There are observation period end dates after the current date: 2024-10-30
#>  The latest max observation period end date found is 2026-10-26
cdm <- generateSequenceCohortSet(cdm = cdm,
                                 name = "joined_cohorts",
                                 indexTable = "cohort_1",
                                 markerTable = "cohort_2")
temporal_symmetry <- summariseTemporalSymmetry(cohort = cdm$joined_cohorts)
#> Warning: `cdm_name` is present in both 'settings' and 'summarised_result'. This will be
#> an error in the next release.
#> Warning: `cdm_name` is present in both 'settings' and 'summarised_result'. This will be
#> an error in the next release.
CDMConnector::cdmDisconnect(cdm)
# }