Create a table showing indication results
tableIndication.Rd![[Experimental]](figures/lifecycle-experimental.svg)
Arguments
- result
A summarised_result created by summariseIndication().
- header
A vector containing which elements should go into the header in order. Allowed are:
cdm_name,group,strata,variable.- splitStrata
If TRUE strata columns will be split.
- cohortName
If TRUE cohort names will be displayed.
- cdmName
If TRUE database names will be displayed.
- groupColumn
Column to use as group labels.
- type
Type of desired formatted table, possibilities: "gt", "flextable", "tibble".
- .options
Named list with additional formatting options. DrugUtilisation::defaultTableOptions() shows allowed arguments and their default values.
Examples
# \donttest{
library(DrugUtilisation)
cdm <- mockDrugUtilisation()
#> Warning: ! 6 column in person do not match expected column type:
#> • `gender_concept_id` is numeric but expected integer
#> • `race_concept_id` is numeric but expected integer
#> • `ethnicity_concept_id` is numeric but expected integer
#> • `location_id` is numeric but expected integer
#> • `provider_id` is numeric but expected integer
#> • `care_site_id` is numeric but expected integer
#> Warning: ! 1 column in observation_period do not match expected column type:
#> • `period_type_concept_id` is numeric but expected integer
#> Warning: ! 2 column in visit_occurrence do not match expected column type:
#> • `visit_concept_id` is numeric but expected integer
#> • `visit_type_concept_id` is numeric but expected integer
#> Warning: ! 10 column in condition_occurrence do not match expected column type:
#> • `condition_concept_id` is numeric but expected integer
#> • `condition_type_concept_id` is numeric but expected integer
#> • `condition_status_concept_id` is numeric but expected integer
#> • `stop_reason` is logical but expected character
#> • `provider_id` is logical but expected integer
#> • `visit_occurrence_id` is logical but expected integer
#> • `visit_detail_id` is logical but expected integer
#> • `condition_source_value` is logical but expected character
#> • `condition_source_concept_id` is logical but expected integer
#> • `condition_status_source_value` is logical but expected character
#> Warning: ! 2 column in drug_exposure do not match expected column type:
#> • `drug_concept_id` is numeric but expected integer
#> • `drug_type_concept_id` is numeric but expected integer
#> Warning: ! 2 column in observation do not match expected column type:
#> • `observation_concept_id` is numeric but expected integer
#> • `observation_type_concept_id` is numeric but expected integer
#> Warning: ! 4 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
#> • `invalid_reason` is logical but expected character
#> Warning: ! 2 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
#> 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_unit_concept_id` is numeric but expected integer
#> • `box_size` is logical but expected integer
#> • `valid_start_date` is character but expected date
#> • `valid_end_date` is character but expected date
#> • `invalid_reason` is logical but expected character
#> Warning: ! 6 column in person do not match expected column type:
#> • `gender_concept_id` is numeric but expected integer
#> • `race_concept_id` is numeric but expected integer
#> • `ethnicity_concept_id` is numeric but expected integer
#> • `location_id` is numeric but expected integer
#> • `provider_id` is numeric but expected integer
#> • `care_site_id` is numeric but expected integer
#> Warning: ! 1 column in observation_period do not match expected column type:
#> • `period_type_concept_id` is numeric but expected integer
result <- cdm$cohort1 |>
summariseIndication(
indicationCohortName = "cohort2",
indicationWindow = list(c(-30, 0)),
unknownIndicationTable = "condition_occurrence"
)
#> Getting specified indications
#> Creating indication summary variables
#> Getting unknown indications
#> Summarising indication results
tableIndication(result, type = "tibble")
#> ! Results have not been suppressed.
#> # A tibble: 9 × 6
#> `Database name` `Variable name` Indication [header]Cohort name\…¹
#> <chr> <chr> <chr> <chr>
#> 1 DUS MOCK Indication from 30 days bef… Cohort 1 0 (0.00 %)
#> 2 DUS MOCK Indication from 30 days bef… Cohort 2 0 (0.00 %)
#> 3 DUS MOCK Indication from 30 days bef… Cohort 3 0 (0.00 %)
#> 4 DUS MOCK Indication from 30 days bef… Cohort 1 … 0 (0.00 %)
#> 5 DUS MOCK Indication from 30 days bef… Cohort 1 … 0 (0.00 %)
#> 6 DUS MOCK Indication from 30 days bef… Cohort 2 … 0 (0.00 %)
#> 7 DUS MOCK Indication from 30 days bef… Cohort 1 … 0 (0.00 %)
#> 8 DUS MOCK Indication from 30 days bef… Unknown 1 (16.67 %)
#> 9 DUS MOCK Indication from 30 days bef… None 5 (83.33 %)
#> # ℹ abbreviated name: ¹`[header]Cohort name\n[header_level]Cohort 2`
#> # ℹ 2 more variables: `[header]Cohort name\n[header_level]Cohort 1` <chr>,
#> # `[header]Cohort name\n[header_level]Cohort 3` <chr>
# }