Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
eval = rlang::is_installed("CirceR") & rlang::is_installed("Capr") & rlang::is_installed("duckdb"),
comment = "#>"
)
library(CDMConnector)
library(dplyr, warn.conflicts = FALSE)
if (Sys.getenv("EUNOMIA_DATA_FOLDER") == "") Sys.setenv("EUNOMIA_DATA_FOLDER" = file.path(tempdir(), "eunomia"))
if (!dir.exists(Sys.getenv("EUNOMIA_DATA_FOLDER"))) dir.create(Sys.getenv("EUNOMIA_DATA_FOLDER"))
if (!eunomiaIsAvailable()) downloadEunomiaData()
## -----------------------------------------------------------------------------
# pathToCohortJsonFiles <- system.file("cohorts1", package = "CDMConnector")
# list.files(pathToCohortJsonFiles)
#
# readr::read_csv(file.path(pathToCohortJsonFiles, "CohortsToCreate.csv"),
# show_col_types = FALSE)
## -----------------------------------------------------------------------------
# library(CDMConnector)
# pathToCohortJsonFiles <- system.file("example_cohorts", package = "CDMConnector")
# list.files(pathToCohortJsonFiles)
#
# con <- DBI::dbConnect(duckdb::duckdb(), eunomiaDir("GiBleed"))
# cdm <- cdmFromCon(con, cdmName = "eunomia", cdmSchema = "main", writeSchema = "main")
#
# cohortSet <- readCohortSet(pathToCohortJsonFiles) |>
# mutate(cohort_name = snakecase::to_snake_case(cohort_name))
#
# cohortSet
#
# cdm <- generateCohortSet(
# cdm = cdm,
# cohortSet = cohortSet,
# name = "study_cohorts"
# )
#
# cdm$study_cohorts
## -----------------------------------------------------------------------------
# cohortCount(cdm$study_cohorts)
# settings(cdm$study_cohorts)
# attrition(cdm$study_cohorts)
## ----eval=FALSE---------------------------------------------------------------
# cdm_gibleed <- cdm %>%
# cdmSubsetCohort(cohortTable = "study_cohorts")
## -----------------------------------------------------------------------------
# library(CDMConnector)
# con <- DBI::dbConnect(duckdb::duckdb(), eunomiaDir())
# cdm <- cdmFromCon(con, cdmSchema = "main", writeSchema = "main")
#
# cohortSet <- readCohortSet(system.file("cohorts3", package = "CDMConnector"))
#
#
# cdm <- generateCohortSet(cdm, cohortSet, name = "cohort")
#
# cdm$cohort
#
# cohortCount(cdm$cohort)
#
## -----------------------------------------------------------------------------
# library(dplyr)
#
# cdm$cohort_subset <- cdm$cohort %>%
# # only keep persons who are in the cohort at least 28 days
# filter(!!datediff("cohort_start_date", "cohort_end_date") >= 28) %>%
# compute(name = "cohort_subset", temporary = FALSE, overwrite = TRUE) %>%
# newCohortTable()
#
# cohortCount(cdm$cohort_subset)
## -----------------------------------------------------------------------------
# daysInCohort <- cdm$cohort %>%
# filter(cohort_definition_id %in% c(1,5)) %>%
# mutate(days_in_cohort = !!datediff("cohort_start_date", "cohort_end_date")) %>%
# count(cohort_definition_id, days_in_cohort) %>%
# collect()
#
# daysInCohort
## -----------------------------------------------------------------------------
#
# cdm$cohort_subset <- cdm$cohort %>%
# filter(!!datediff("cohort_start_date", "cohort_end_date") >= 14) %>%
# mutate(cohort_definition_id = 10 + cohort_definition_id) %>%
# union_all(
# cdm$cohort %>%
# filter(!!datediff("cohort_start_date", "cohort_end_date") >= 21) %>%
# mutate(cohort_definition_id = 100 + cohort_definition_id)
# ) %>%
# union_all(
# cdm$cohort %>%
# filter(!!datediff("cohort_start_date", "cohort_end_date") >= 28) %>%
# mutate(cohort_definition_id = 1000 + cohort_definition_id)
# ) %>%
# compute(name = "cohort_subset", temporary = FALSE, overwrite = TRUE) # %>%
# # newCohortTable() # this function creates the cohort object and metadata
#
# cdm$cohort_subset %>%
# mutate(days_in_cohort = !!datediff("cohort_start_date", "cohort_end_date")) %>%
# group_by(cohort_definition_id) %>%
# summarize(mean_days_in_cohort = mean(days_in_cohort, na.rm = TRUE)) %>%
# collect() %>%
# arrange(mean_days_in_cohort)
#
## -----------------------------------------------------------------------------
#
# library(dplyr, warn.conflicts = FALSE)
#
# cdm <- generateConceptCohortSet(
# cdm,
# conceptSet = list(gibleed = 192671),
# name = "gibleed2", # name of the cohort table
# limit = "all", # use all occurrences of the concept instead of just the first
# end = 10 # set explicit cohort end date 10 days after start
# )
#
# cdm$gibleed2 <- cdm$gibleed2 %>%
# semi_join(
# filter(cdm$person, gender_concept_id == 8507),
# by = c("subject_id" = "person_id")
# ) %>%
# recordCohortAttrition(reason = "Male")
#
# attrition(cdm$gibleed2)
## -----------------------------------------------------------------------------
# cohort <- dplyr::tibble(
# cohort_definition_id = 1L,
# subject_id = 1L,
# cohort_start_date = as.Date("1999-01-01"),
# cohort_end_date = as.Date("2001-01-01")
# )
#
# cohort
## -----------------------------------------------------------------------------
# library(omopgenerics)
# cdm <- insertTable(cdm = cdm, name = "cohort", table = cohort, overwrite = TRUE)
#
# cdm$cohort
## -----------------------------------------------------------------------------
# cdm$cohort <- newCohortTable(cdm$cohort)
## -----------------------------------------------------------------------------
# cohortCount(cdm$cohort)
# settings(cdm$cohort)
# attrition(cdm$cohort)
## -----------------------------------------------------------------------------
# cdm <- insertTable(cdm = cdm, name = "cohort2", table = cohort, overwrite = TRUE)
# cdm$cohort2 <- newCohortTable(cdm$cohort2)
# settings(cdm$cohort2)
#
# cohort_set <- data.frame(cohort_definition_id = 1L,
# cohort_name = "made_up_cohort")
# cdm$cohort2 <- newCohortTable(cdm$cohort2, cohortSetRef = cohort_set)
#
# settings(cdm$cohort2)
## -----------------------------------------------------------------------------
# DBI::dbDisconnect(con, shutdown = TRUE)
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