Using generateSequenceCohortSet to obtain sequence ratios for the desired outcomes.
Examples
# \donttest{
library(CohortSymmetry)
cdm <- mockCohortSymmetry()
cdm <- generateSequenceCohortSet(cdm = cdm,
name = "joined_cohorts",
indexTable = "cohort_1",
markerTable = "cohort_2")
pssa_result <- summariseSequenceRatios(cohort = cdm$joined_cohorts)
#> Warning: For at least some combinations, index is always before marker or marker always
#> before index
#> -- 5 combinations of 8 had index always before marker
#> -- 5 combinations of 8 had marker always before index
pssa_result
#> # A tibble: 80 × 13
#> result_id cdm_name group_name group_level strata_name strata_level
#> <int> <chr> <chr> <chr> <chr> <chr>
#> 1 1 mock database index_cohort_na… cohort_1 &… overall overall
#> 2 1 mock database index_cohort_na… cohort_1 &… overall overall
#> 3 1 mock database index_cohort_na… cohort_1 &… overall overall
#> 4 1 mock database index_cohort_na… cohort_1 &… overall overall
#> 5 1 mock database index_cohort_na… cohort_1 &… overall overall
#> 6 1 mock database index_cohort_na… cohort_1 &… overall overall
#> 7 1 mock database index_cohort_na… cohort_1 &… overall overall
#> 8 1 mock database index_cohort_na… cohort_1 &… overall overall
#> 9 1 mock database index_cohort_na… cohort_1 &… overall overall
#> 10 1 mock database index_cohort_na… cohort_1 &… overall overall
#> # ℹ 70 more rows
#> # ℹ 7 more variables: variable_name <chr>, variable_level <chr>,
#> # estimate_name <chr>, estimate_type <chr>, estimate_value <chr>,
#> # additional_name <chr>, additional_level <chr>
CDMConnector::cdmDisconnect(cdm)
# }