test_that("check summariseInObservation works", { skip_on_cran() # Load mock database ---- cdm <- cdmEunomia() # Check all tables work ---- expect_true(inherits(summariseInObservation(cdm$observation_period), "summarised_result")) expect_true(inherits(summariseInObservation(cdm$observation_period, interval = "months"), "summarised_result")) expect_true(inherits(summariseInObservation(cdm$observation_period, interval = "years"), "summarised_result")) expect_error(summariseInObservation(cdm$death)) # Check inputs ---- x <- summariseInObservation(cdm$observation_period, interval = "years") |> dplyr::filter(additional_level == "1909-01-01 to 1909-12-31", estimate_name == "count") |> dplyr::pull("estimate_value") |> as.numeric() y <- cdm$observation_period %>% dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% dplyr::mutate(start_year = !!CDMConnector::datepart("observation_period_start_date", "year")) %>% dplyr::mutate(end_year = !!CDMConnector::datepart("observation_period_end_date", "year")) %>% dplyr::filter(start_year <= 1909, end_year >= 1909) |> dplyr::tally() |> dplyr::pull("n") |> as.numeric() expect_equal(x, y) x <- summariseInObservation(cdm$observation_period, interval = "years") expect_equal(x |> dplyr::filter(additional_level != "overall") |> dplyr::pull("additional_name") |> unique(), "time_interval") x <- summariseInObservation(cdm$observation_period, interval = "overall") expect_equal(x |> dplyr::filter(additional_level == "overall") |> dplyr::pull("additional_name") |> unique(), "overall") x <- summariseInObservation(cdm$observation_period, interval = "years") |> dplyr::filter(additional_level == c("1936-01-01 to 1936-12-31"), estimate_name == "count") |> dplyr::pull("estimate_value") |> as.numeric() y <- cdm$observation_period %>% dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% dplyr::mutate(start = !!CDMConnector::datepart("observation_period_start_date", "year")) %>% dplyr::mutate(end = !!CDMConnector::datepart("observation_period_end_date", "year")) %>% dplyr::filter((.data$start < 1936 & .data$end >= 1936) | (.data$start >= 1936 & .data$start <= 1936)) |> dplyr::tally() |> dplyr::pull("n") |> as.numeric() expect_equal(x, y) x <- summariseInObservation(cdm$observation_period, output = "person", interval = "years") |> dplyr::filter(additional_level == c("1996-01-01 to 1996-12-31"), estimate_name == "count") |> dplyr::pull("estimate_value") |> as.numeric() y <- cdm$observation_period %>% dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% dplyr::mutate(start = !!CDMConnector::datepart("observation_period_start_date", "year")) %>% dplyr::mutate(end = !!CDMConnector::datepart("observation_period_end_date", "year")) %>% dplyr::filter((.data$start < 1996 & .data$end >= 1996) | (.data$start >= 1996 & .data$start <= 1996)) |> dplyr::distinct(.data$person_id) |> dplyr::tally() |> dplyr::pull("n") |> as.numeric() expect_equal(x, y) x <- summariseInObservation(cdm$observation_period, interval = "years") |> dplyr::filter(additional_level == c("1998-01-01 to 1998-12-31"), estimate_name == "count") |> dplyr::pull("estimate_value") |> as.numeric() y <- cdm$observation_period %>% dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% dplyr::mutate(start = !!CDMConnector::datepart("observation_period_start_date", "year")) %>% dplyr::mutate(end = !!CDMConnector::datepart("observation_period_end_date", "year")) %>% dplyr::filter((.data$start < 1998 & .data$end >= 1998) | (.data$start >= 1998 & .data$start <= 1998)) |> dplyr::tally() |> dplyr::pull("n") |> as.numeric() expect_equal(x, y) # Check inputs ---- x <- summariseInObservation(cdm$observation_period, interval = "months") |> dplyr::filter(additional_level == "1942-03-01 to 1942-03-31", estimate_name == "count") |> dplyr::pull("estimate_value") |> as.numeric() y <- cdm$observation_period %>% dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% dplyr::filter( (observation_period_start_date < as.Date("1942-03-01") & observation_period_end_date >= as.Date("1942-03-01")) | (observation_period_start_date >= as.Date("1942-03-01") & observation_period_start_date <= as.Date("1942-03-31")) ) |> dplyr::tally() |> dplyr::pull("n") |> as.numeric() expect_equal(x, y) x <- summariseInObservation(cdm$observation_period, interval = "months") |> dplyr::filter(additional_level == "2015-09-01 to 2015-09-30", estimate_name == "count") |> dplyr::pull("estimate_value") |> as.numeric() y <- cdm$observation_period %>% dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% dplyr::filter( (observation_period_start_date < as.Date("2015-09-01") & observation_period_end_date >= as.Date("2015-09-01")) | (observation_period_start_date >= as.Date("2015-09-01") & observation_period_start_date <= as.Date("2015-09-30")) ) |> dplyr::tally() |> dplyr::pull("n") |> as.numeric() expect_equal(x, y) x <- summariseInObservation(cdm$observation_period, interval = "months") |> dplyr::filter(additional_level == "1982-03-01 to 1982-03-31", estimate_name == "count") |> dplyr::pull("estimate_value") |> as.numeric() y <- cdm$observation_period %>% dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% dplyr::filter(observation_period_start_date < as.Date("1982-03-01") & observation_period_end_date >= as.Date("1982-03-01") | (observation_period_start_date >= as.Date("1982-03-01") & observation_period_start_date <= as.Date("1982-03-31"))) |> dplyr::tally() |> dplyr::pull("n") |> as.numeric() expect_equal(x, y) PatientProfiles::mockDisconnect(cdm = cdm) }) test_that("check sex argument works", { skip_on_cran() # Load mock database ---- cdm <- cdmEunomia() # Check overall x <- summariseInObservation(cdm$observation_period, interval = "years", sex = TRUE) expect_equal(x |> dplyr::filter(additional_level != "overall") |> dplyr::pull("additional_name") |> unique(), "time_interval") x <- summariseInObservation(cdm$observation_period, interval = "overall") expect_equal(x |> dplyr::filter(additional_level == "overall") |> dplyr::pull("additional_name") |> unique(), "overall") x <- summariseInObservation(cdm$observation_period, interval = "years", sex = TRUE) |> dplyr::filter(strata_level %in% c("Male", "Female"), additional_level == "1908-01-01 to 1908-12-31", estimate_name == "count") |> dplyr::pull(estimate_value) |> as.numeric() |> sum() y <- summariseInObservation(cdm$observation_period, interval = "years", sex = TRUE) |> dplyr::filter(strata_level %in% c("overall"), additional_level == "1908-01-01 to 1908-12-31", estimate_name == "count") |> dplyr::pull(estimate_value) |> as.numeric() expect_equal(x, y) y <- cdm$observation_period |> dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% dplyr::filter(observation_period_start_date < as.Date("1908-01-01") & observation_period_end_date >= as.Date("1908-01-01") | (observation_period_start_date >= as.Date("1908-01-01") & observation_period_start_date <= as.Date("1908-12-31"))) |> dplyr::tally() |> dplyr::pull() |> as.numeric() expect_equal(x, y) # Check a random group x <- summariseInObservation(cdm$observation_period, interval = "years", sex = TRUE) |> dplyr::filter(strata_level == "Male", additional_level == "1915-01-01 to 1915-12-31", estimate_name == "count") |> dplyr::pull(estimate_value) |> as.numeric() y <- cdm$observation_period |> dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% PatientProfiles::addSexQuery() |> dplyr::filter(sex == "Male") |> dplyr::filter(observation_period_start_date < as.Date("1915-01-01") & observation_period_end_date >= as.Date("1915-01-01") | (observation_period_start_date >= as.Date("1915-01-01") & observation_period_start_date <= as.Date("1915-12-31"))) |> dplyr::tally() |> dplyr::pull() |> as.numeric() expect_equal(x, y) x <- summariseInObservation(cdm$observation_period, interval = "years", sex = TRUE) |> dplyr::filter(strata_level == "Male", additional_level == "1915-01-01 to 1915-12-31", estimate_name == "percentage") |> dplyr::pull(estimate_value) y <- (cdm$observation_period |> dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% PatientProfiles::addSexQuery() |> dplyr::filter(sex == "Male") |> dplyr::filter(observation_period_start_date < as.Date("1915-01-01") & observation_period_end_date >= as.Date("1915-01-01") | (observation_period_start_date >= as.Date("1915-01-01") & observation_period_start_date <= as.Date("1915-12-31"))) |> dplyr::tally() |> dplyr::pull()) / (cdm[["person"]] |> dplyr::tally() |> dplyr::pull() |> as.numeric()) * 100 expect_equal(x, sprintf("%.2f", y)) expect_no_error(x <- summariseInObservation(cdm$observation_period, output = "person", interval = "years", sex = TRUE)) x <- x |> dplyr::filter(strata_level == "Male", additional_level == "1915-01-01 to 1915-12-31", estimate_name == "percentage") |> dplyr::pull(estimate_value) y <- cdm$observation_period |> dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% PatientProfiles::addSexQuery() |> dplyr::filter(sex == "Male") |> dplyr::filter(observation_period_start_date < as.Date("1915-01-01") & observation_period_end_date >= as.Date("1915-01-01") | (observation_period_start_date >= as.Date("1915-01-01") & observation_period_start_date <= as.Date("1915-12-31"))) |> dplyr::summarise(p = dplyr::n_distinct(.data$person_id)) |> dplyr::pull() y <- y / (cdm[["person"]] |> dplyr::tally() |> dplyr::pull()) * 100 expect_equal(x, sprintf("%.2f", y)) PatientProfiles::mockDisconnect(cdm = cdm) }) test_that("check ageGroup argument works", { skip_on_cran() # Load mock database ---- cdm <- cdmEunomia() expect_no_error(summariseInObservation(cdm$observation_period, ageGroup = list(c(0, 20), c(21, Inf)))) x <- summariseInObservation(cdm$observation_period, interval = "years", ageGroup = list("<=20" = c(0, 20), ">20" = c(21, Inf))) |> dplyr::filter(additional_level == "1928-01-01 to 1928-12-31", estimate_name == "count", strata_level == "<=20") |> dplyr::pull(estimate_value) |> as.numeric() y <- cdm$observation_period |> dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% dplyr::filter(observation_period_start_date < as.Date("1928-01-01") & observation_period_end_date >= as.Date("1928-01-01") | (observation_period_start_date >= as.Date("1928-01-01") & observation_period_start_date <= as.Date("1928-12-31"))) |> dplyr::mutate("start" = as.Date("1928-01-01"), "end" = as.Date("1928-12-31")) |> PatientProfiles::addAgeQuery(indexDate = "start", ageName = "age_start") %>% dplyr::mutate(age_end = age_start + 10) |> dplyr::filter((age_end <= 20 & age_end >= 0) | (age_start >= 0 & age_start <= 20)) |> dplyr::tally() |> dplyr::pull() |> as.numeric() expect_equal(x, y) x <- summariseInObservation(cdm$observation_period, interval = "years", sex = TRUE) |> dplyr::filter(strata_level == "Male", additional_level == "1918-01-01 to 1918-12-31", estimate_name == "percentage") |> dplyr::pull(estimate_value) y <- (cdm$observation_period |> dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% PatientProfiles::addSexQuery() |> dplyr::filter(sex == "Male") |> dplyr::filter(observation_period_start_date < as.Date("1918-01-01") & observation_period_end_date >= as.Date("1918-01-01") | (observation_period_start_date >= as.Date("1918-01-01") & observation_period_start_date <= as.Date("1918-12-31"))) |> dplyr::tally() |> dplyr::pull()) / (cdm[["person"]] |> dplyr::tally() |> dplyr::pull() |> as.numeric()) * 100 expect_equal(x, sprintf("%.2f", y)) expect_no_error(x <- summariseInObservation(cdm$observation_period, output = "person", ageGroup = list(c(0, 20), c(21, Inf)), interval = "years")) x <- x |> dplyr::filter(additional_level == "1928-01-01 to 1928-12-31", estimate_name == "count", strata_level == "0 to 20") |> dplyr::pull(estimate_value) |> as.numeric() y <- cdm$observation_period |> dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% dplyr::filter(observation_period_start_date < as.Date("1928-01-01") & observation_period_end_date >= as.Date("1928-01-01") | (observation_period_start_date >= as.Date("1928-01-01") & observation_period_start_date <= as.Date("1928-12-31"))) |> dplyr::mutate("start" = as.Date("1928-01-01"), "end" = as.Date("1928-12-31")) |> PatientProfiles::addAgeQuery(indexDate = "start", ageName = "age_start") %>% dplyr::mutate(age_end = age_start + 10) |> dplyr::filter((age_end <= 20 & age_end >= 0) | (age_start >= 0 & age_start <= 20)) |> dplyr::summarise(dplyr::n_distinct(person_id)) |> dplyr::pull() expect_equal(x, y) PatientProfiles::mockDisconnect(cdm = cdm) }) test_that("check output argument works", { skip_on_cran() # Load mock database ---- cdm <- cdmEunomia() # check value x <- summariseInObservation(cdm$observation_period, interval = "years", output = c("record", "person-days"), ageGroup = NULL, sex = FALSE) |> dplyr::filter(variable_name == "Number person-days", additional_level == "1970-01-01 to 1970-12-31", estimate_type == "integer") |> dplyr::pull("estimate_value") |> as.numeric() y <- cdm$observation_period |> dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% dplyr::filter(observation_period_start_date < as.Date("1970-01-01") & observation_period_end_date >= as.Date("1970-01-01") | (observation_period_start_date >= as.Date("1970-01-01") & observation_period_start_date <= as.Date("1970-12-31"))) |> dplyr::mutate("start_date" = as.Date("1970-01-01"), "end_date" = as.Date("1970-12-31")) %>% dplyr::mutate( "start_date" = pmax(start_date, observation_period_start_date, na.rm = TRUE), "end_date" = pmin(end_date, observation_period_end_date, na.rm = TRUE) ) %>% dplyr::mutate(days = !!CDMConnector::datediff("start_date", "end_date", interval = "day") + 1) |> dplyr::summarise(n = sum(days, na.rm = TRUE)) |> dplyr::pull("n") |> as.numeric() expect_equal(x, y) # Check percentage den <- cdm$observation_period |> dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% dplyr::mutate(days = !!CDMConnector::datediff("observation_period_start_date", "observation_period_end_date", interval = "day") + 1) |> dplyr::summarise(n = sum(days, na.rm = TRUE)) |> dplyr::pull("n") x <- summariseInObservation(cdm$observation_period, interval = "years", output = c("record", "person-days"), ageGroup = NULL, sex = FALSE) |> dplyr::filter(variable_name == "Number person-days", additional_level == "1964-01-01 to 1964-12-31", estimate_type == "percentage") |> dplyr::pull("estimate_value") y <- cdm$observation_period |> dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") %>% dplyr::filter(observation_period_start_date < as.Date("1964-01-01") & observation_period_end_date >= as.Date("1964-01-01") | (observation_period_start_date >= as.Date("1964-01-01") & observation_period_start_date <= as.Date("1964-12-31"))) |> dplyr::mutate("start_date" = as.Date("1964-01-01"), "end_date" = as.Date("1964-12-31")) %>% dplyr::mutate( "start_date" = pmax(start_date, observation_period_start_date, na.rm = TRUE), "end_date" = pmin(end_date, observation_period_end_date, na.rm = TRUE) ) %>% dplyr::mutate(days = !!CDMConnector::datediff("start_date", "end_date", interval = "day") + 1) |> dplyr::summarise(n = sum(days, na.rm = TRUE)) |> dplyr::pull("n") |> as.numeric() / den * 100 expect_equal(x, sprintf("%.2f", y)) # Check sex stratified x <- summariseInObservation(cdm$observation_period, interval = "years", output = "person-days", sex = TRUE) |> dplyr::filter(variable_name == "Number person-days", additional_level == "1964-01-01 to 1964-12-31", estimate_type == "integer") |> dplyr::filter(strata_level == "overall") |> dplyr::pull("estimate_value") |> as.numeric() y <- summariseInObservation(cdm$observation_period, interval = "years", output = "person-days", sex = TRUE) |> dplyr::filter(variable_name == "Number person-days", additional_level == "1964-01-01 to 1964-12-31", estimate_type == "integer") |> dplyr::filter(strata_level != "overall") |> dplyr::pull("estimate_value") |> as.numeric() |> sum() expect_equal(x, y) # Check age stratified x <- summariseInObservation(cdm$observation_period, interval = "years", output = "person-days", ageGroup = list("<=20" = c(0, 20), ">20" = c(21, Inf))) |> dplyr::filter(variable_name == "Number person-days", additional_level == "2000-01-01 to 2000-12-31", estimate_type == "integer") |> dplyr::filter(strata_level == "overall") |> dplyr::pull("estimate_value") |> as.numeric() y <- summariseInObservation(cdm$observation_period, interval = "years", output = "person-days", sex = TRUE) |> dplyr::filter(variable_name == "Number person-days", additional_level == "2000-01-01 to 2000-12-31", estimate_type == "integer") |> dplyr::filter(strata_level != "overall") |> dplyr::pull("estimate_value") |> as.numeric() |> sum() expect_equal(x, y) PatientProfiles::mockDisconnect(cdm = cdm) }) test_that("dateRange argument works", { skip_on_cran() # Load mock database ---- cdm <- cdmEunomia() expect_no_error(summariseInObservation(cdm$observation_period, dateRange = as.Date(c("1940-01-01", "2018-01-01")))) expect_message(x <- summariseInObservation(cdm$observation_period, dateRange = as.Date(c("1940-01-01", "2024-01-01")))) observationRange <- cdm$observation_period |> dplyr::summarise( minobs = min(.data$observation_period_start_date, na.rm = TRUE), maxobs = max(.data$observation_period_end_date, na.rm = TRUE) ) expect_no_error(y <- summariseInObservation(cdm$observation_period, dateRange = as.Date(c("1940-01-01", observationRange |> dplyr::pull("maxobs"))))) expect_equal(x, y, ignore_attr = TRUE) expect_false(settings(x)$study_period_end == settings(y)$study_period_end) expect_error(summariseInObservation(cdm$observation_period, dateRange = as.Date(c("2015-01-01", "2014-01-01")))) expect_warning(z <- summariseInObservation(cdm$observation_period, dateRange = as.Date(c("2020-01-01", "2021-01-01")))) expect_equal(z, omopgenerics::emptySummarisedResult(), ignore_attr = TRUE) expect_equal(summariseInObservation(cdm$observation_period, dateRange = as.Date(c("1940-01-01", NA))), y, ignore_attr = TRUE) checkResultType(z, "summarise_in_observation") expect_equal(colnames(settings(z)), colnames(settings(x))) PatientProfiles::mockDisconnect(cdm = cdm) }) test_that("no tables created", { skip_on_cran() # Load mock database ---- cdm <- cdmEunomia() startNames <- CDMConnector::listSourceTables(cdm) results <- summariseInObservation(cdm$observation_period, output = c("age", "sex", "record", "person-days", "person"), interval = "years", sex = TRUE, ageGroup = list( c(0, 17), c(18, 65), c(66, 100) ), dateRange = as.Date(c("2012-01-01", "2018-01-01")) ) endNames <- CDMConnector::listSourceTables(cdm) expect_true(length(setdiff(endNames, startNames)) == 0) PatientProfiles::mockDisconnect(cdm = cdm) }) test_that("age and sex output work", { skip_on_cran() # Load mock database ---- cdm <- cdmEunomia() expect_no_error(x <- summariseInObservation(cdm$observation_period, output = "age")) expect_equal(cdm$observation_period |> PatientProfiles::addAgeQuery(indexDate = "observation_period_start_date") |> dplyr::pull("age") |> stats::median(), as.numeric(x$estimate_value)) expect_no_error(y <- summariseInObservation(cdm$observation_period, output = "age", sex = TRUE, ageGroup = list(c(0, 50)))) y <- y |> omopgenerics::splitStrata() |> dplyr::filter(.data$sex == "Female" & .data$age_group == "0 to 50") |> dplyr::pull("estimate_value") |> as.numeric() z <- cdm$observation_period |> PatientProfiles::addDemographicsQuery(indexDate = "observation_period_start_date", age = TRUE, ageGroup = list(c(0, 50)), sex = TRUE, priorObservation = FALSE, futureObservation = TRUE) |> dplyr::filter(.data$sex == "Female" & .data$age_group == "0 to 50") |> dplyr::pull("age") |> stats::median() expect_equal(y, z) expect_no_error(y <- summariseInObservation(cdm$observation_period, output = "age", sex = TRUE, ageGroup = list(c(0, 50)), interval = "years")) y <- y |> omopgenerics::splitAll() |> dplyr::filter(.data$time_interval == "2019-01-01 to 2019-12-31" & .data$sex == "Female" & .data$age_group == "0 to 50") |> dplyr::pull("estimate_value") |> as.numeric() z <- cdm$observation_period |> dplyr::filter(observation_period_start_date < as.Date("2019-01-01") & observation_period_end_date >= as.Date("2019-01-01") | (observation_period_start_date >= as.Date("2019-01-01") & observation_period_start_date <= as.Date("2019-12-31"))) |> dplyr::mutate("start_date" = as.Date("2019-01-01")) |> dplyr::mutate( "index_date" = pmax(start_date, observation_period_start_date, na.rm = TRUE) ) |> PatientProfiles::addDemographicsQuery(indexDate = "index_date", age = TRUE, ageGroup = list(c(0, 50)), sex = TRUE, priorObservation = FALSE, futureObservation = TRUE) |> dplyr::filter(.data$sex == "Female" & .data$age_group == "0 to 50") |> dplyr::pull("age") |> stats::median() expect_equal(y, z) expect_no_error(x <- summariseInObservation(cdm$observation_period, output = "sex")) y <- cdm$observation_period |> PatientProfiles::addSexQuery() |> dplyr::mutate("n_tot" = dplyr::n_distinct("person_id")) |> dplyr::filter(.data$sex == "Female") |> dplyr::summarise("n_females" = dplyr::n_distinct("person_id"), n_tot = dplyr::first(.data$n_tot)) |> dplyr::collect() expect_equal(sprintf("%.2f", 100 * y$n_females / y$n_tot), x |> dplyr::filter(estimate_type == "percentage") |> dplyr::pull(estimate_value)) expect_equal(x, summariseInObservation(cdm$observation_period, sex = TRUE, output = "sex")) expect_no_error(y <- summariseInObservation(cdm$observation_period, output = "sex", ageGroup = list(c(0, 50)), interval = "years")) y <- y |> omopgenerics::splitAll() |> dplyr::filter(.data$time_interval == "2019-01-01 to 2019-12-31" & .data$age_group == "0 to 50" & .data$estimate_type == "percentage") |> dplyr::pull("estimate_value") z <- cdm$observation_period |> dplyr::inner_join( cdm$person |> dplyr::filter(.data$gender_concept_id %in% c(8507, 8532)), by = "person_id" ) |> dplyr::mutate("n_tot" = dplyr::n_distinct("person_id")) |> dplyr::mutate("start_date" = as.Date("2019-01-01")) |> dplyr::filter(observation_period_start_date < as.Date("2019-01-01") & observation_period_end_date >= as.Date("2019-01-01") | (observation_period_start_date >= as.Date("2019-01-01") & observation_period_start_date <= as.Date("2019-12-31"))) |> dplyr::mutate( "index_date" = pmax(start_date, observation_period_start_date, na.rm = TRUE) ) |> PatientProfiles::addDemographicsQuery(indexDate = "index_date", age = TRUE, ageGroup = list(c(0, 50)), sex = TRUE, priorObservation = FALSE, futureObservation = TRUE) |> dplyr::filter(.data$age_group == "0 to 50" & .data$sex == "Female") |> dplyr::summarise("n_females" = dplyr::n_distinct("person_id"), n_tot = dplyr::first(.data$n_tot)) |> dplyr::collect() expect_equal(sprintf("%.2f", 100 * z$n_females / z$n_tot), y) PatientProfiles::mockDisconnect(cdm = cdm) }) test_that("overall time interval work", { skip_on_cran() # Load mock database ---- cdm <- cdmEunomia() expect_no_error(x <- summariseInObservation(cdm$observation_period, output = c("record", "person", "sex", "age"), interval = "years")) x <- x |> dplyr::filter(.data$additional_level == "overall" & estimate_type != "percentage") records <- cdm$observation_period |> dplyr::tally() |> dplyr::pull(.data$n) person <- cdm$observation_period %>% dplyr::distinct(.data$person_id) |> dplyr::tally() |> dplyr::pull(.data$n) sex <- cdm$observation_period |> PatientProfiles::addSexQuery() |> dplyr::filter(.data$sex == "Female") |> dplyr::distinct(.data$person_id) |> dplyr::tally() |> dplyr::pull(.data$n) age <- cdm$observation_period |> PatientProfiles::addAgeQuery(indexDate = "observation_period_start_date") |> dplyr::summarise(median = stats::median(.data$age)) |> dplyr::pull(.data$median) expect_equal(x |> dplyr::filter(variable_name == "Number records in observation") |> dplyr::pull(.data$estimate_value), as.character(records)) expect_equal(x |> dplyr::filter(variable_name == "Number subjects in observation") |> dplyr::pull(.data$estimate_value), as.character(person)) expect_equal(x |> dplyr::filter(variable_name == "Number females in observation") |> dplyr::pull(.data$estimate_value), as.character(sex)) expect_equal(x |> dplyr::filter(variable_name == "Median age in observation") |> dplyr::pull(.data$estimate_value), as.character(age)) PatientProfiles::mockDisconnect(cdm = cdm) }) test_that("tableInObservation works", { skip_on_cran() # Load mock database ---- cdm <- cdmEunomia() expect_no_error(x <- tableInObservation(summariseInObservation(cdm$observation_period))) expect_true(inherits(x, "gt_tbl")) expect_no_error(tableInObservation(summariseInObservation(cdm$observation_period), type = "datatable")) expect_no_error(tableInObservation(summariseInObservation(cdm$observation_period), type = "reactable")) PatientProfiles::mockDisconnect(cdm = cdm) })