## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----eval=FALSE---------------------------------------------------------------
# library(syrona)
# 
# # Both datasets must already be extracted (in data/sources/)
# compare_all("Hospital_A", "Hospital_B")

## ----eval=FALSE---------------------------------------------------------------
# compare_all("Hospital_A", "Hospital_B", domains = "conditions")

## ----eval=FALSE---------------------------------------------------------------
# d1 <- load_dataset("Hospital_A")
# d2 <- load_dataset("Hospital_B")
# 
# # Step 1: Yearly comparison (inner join on concept x year x sex x age_group)
# yearly <- compare_yearly(d1, d2, prev_table = "condition_prevalence")
# 
# # Step 2: Meta across years
# meta_ag <- compare_meta_agegroups(yearly)
# 
# # Step 3: Meta across age groups
# meta_sex <- compare_meta_by_sex(meta_ag)
# 
# # Step 4: Meta across sexes
# meta_sum <- compare_meta_summary(meta_sex)

## ----eval=FALSE---------------------------------------------------------------
# # List available comparisons
# list_comparisons()
# #> [1] "Hospital_A_vs_Hospital_B"
# 
# # Load a comparison
# comp <- load_comparison("Hospital_A", "Hospital_B")
# names(comp)
# #> [1] "condition_yearly" "condition_meta_agegroups"
# #> [3] "condition_meta_by_sex" "condition_meta_summary"