Format a summarised_treatment result into a visual table.

Usage

tableTreatment(
  result,
  header = c("window_name"),
  splitStrata = TRUE,
  cdmName = TRUE,
  groupColumn = c("cdm_name", "cohort_name"),
  type = "gt",
  formatEstimateName = c(`N (%)` = "<count> (<percentage> %)"),
  .options = list()
)

Arguments

result

A summarised_result object with results from summariseTreatmentFromCohort() or summariseTreatmentFromConceptSet().

header

A vector containing which elements should go into the header in order. Allowed values: cdm_name, cohort_name, strata, variable, estimate and window_name.

splitStrata

If TRUE strata columns will be split.

cdmName

If TRUE database names will be displayed.

groupColumn

Column to use as group labels. Allowed values: cdm_name, cohort_name, strata, variable, estimate and window_name.

type

Type of desired formatted table, possibilities: "gt", "flextable", "tibble".

formatEstimateName

Named list of estimate name's to join, sorted by computation order. Indicate estimate_name's between <...>.

.options

Named list with additional formatting options. DrugUtilisation::defaultTableOptions() shows allowed arguments and their default values.

Value

A table with a formatted version of summariseTreatment() results.

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 |>
  summariseTreatment(
    treatmentCohortName = "cohort2",
    window = list(c(0, 30), c(31, 365))
  )

tableTreatment(result)
#> ! Results have not been suppressed.


  
Treatment
      
Estimate name
      

        
Window name
      
    
0 to 30
      
31 to 365
    
DUS MOCK; cohort_1
    
cohort_1
N (%)
0 (0.00 %)
0 (0.00 %)
cohort_2
N (%)
0 (0.00 %)
0 (0.00 %)
cohort_3
N (%)
1 (20.00 %)
0 (0.00 %)
untreated
N (%)
4 (80.00 %)
5 (100.00 %)
DUS MOCK; cohort_2
    
cohort_1
N (%)
0 (0.00 %)
0 (0.00 %)
cohort_2
N (%)
0 (0.00 %)
0 (0.00 %)
cohort_3
N (%)
0 (0.00 %)
1 (33.33 %)
untreated
N (%)
3 (100.00 %)
2 (66.67 %)
DUS MOCK; cohort_3
    
cohort_1
N (%)
0 (0.00 %)
0 (0.00 %)
cohort_2
N (%)
0 (0.00 %)
0 (0.00 %)
cohort_3
N (%)
0 (0.00 %)
0 (0.00 %)
untreated
N (%)
2 (100.00 %)
2 (100.00 %)
# }