| Title: | Build and Manipulate Study Cohorts Using a Common Data Model |
|---|---|
| Description: | Create and manipulate study cohorts in data mapped to the Observational Medical Outcomes Partnership Common Data Model. |
| Authors: | Edward Burn [aut, cre] (ORCID: <https://orcid.org/0000-0002-9286-1128>), Martí Català [aut] (ORCID: <https://orcid.org/0000-0003-3308-9905>), Nuria Mercade-Besora [aut] (ORCID: <https://orcid.org/0009-0006-7948-3747>), Marta Alcalde-Herraiz [aut] (ORCID: <https://orcid.org/0009-0002-4405-1814>), Mike Du [aut] (ORCID: <https://orcid.org/0000-0002-9517-8834>), Yuchen Guo [aut] (ORCID: <https://orcid.org/0000-0002-0847-4855>), Xihang Chen [aut] (ORCID: <https://orcid.org/0009-0001-8112-8959>), Kim Lopez-Guell [aut] (ORCID: <https://orcid.org/0000-0002-8462-8668>), Elin Rowlands [aut] (ORCID: <https://orcid.org/0009-0005-5166-0417>) |
| Maintainer: | Edward Burn <[email protected]> |
| License: | Apache License (>= 2) |
| Version: | 0.6.3.900 |
| Built: | 2026-05-31 07:16:32 UTC |
| Source: | https://github.com/ohdsi/cohortconstructor |
Adds an index on subject_id and cohort_start_date to a cohort table. Note, currently only indexes will be added if the table is in a postgres database.
addCohortTableIndex(cohort)addCohortTableIndex(cohort)
cohort |
A cohort table in a cdm reference. |
The cohort table
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 <- addCohortTableIndex(cdm$cohort1)library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 <- addCohortTableIndex(cdm$cohort1)
Run benchmark of CohortConstructor cohort instantiation time compared to CIRCE from JSON. More information in the benchmarking vignette.
benchmarkCohortConstructor( cdm, runCIRCE = TRUE, runCohortConstructorDefinition = TRUE, runCohortConstructorDomain = TRUE, dropCohorts = TRUE )benchmarkCohortConstructor( cdm, runCIRCE = TRUE, runCohortConstructorDefinition = TRUE, runCohortConstructorDomain = TRUE, dropCohorts = TRUE )
cdm |
A cdm reference. |
runCIRCE |
Whether to run cohorts from JSON definitions generated with Atlas. |
runCohortConstructorDefinition |
Whether to run the benchmark part where cohorts are created with CohortConstructor by definition (one by one, separately). |
runCohortConstructorDomain |
Whether to run the benchmark part where cohorts are created with CohortConstructor by domain (instantianting base cohort all together, as a set). |
dropCohorts |
Whether to drop cohorts created during benchmark. |
Benchmarking results
benchmarkDatabenchmarkData
A list of results from benchmarking
collapseCohorts() concatenates cohort records, allowing for some number
of days between one finishing and the next starting.
collapseCohorts( cohort, cohortId = NULL, gap = 0, name = tableName(cohort), .softValidation = FALSE )collapseCohorts( cohort, cohortId = NULL, gap = 0, name = tableName(cohort), .softValidation = FALSE )
cohort |
A cohort table in a cdm reference. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
gap |
Number of days between two subsequent cohort entries to be merged in a single cohort record. |
name |
Name of the new cohort table created in the cdm object. |
.softValidation |
Whether to perform a soft validation of consistency. If set to FALSE four additional checks will be performed: 1) a check that cohort end date is not before cohort start date, 2) a check that there are no missing values in required columns, 3) a check that cohort duration is all within observation period, and 4) that there are no overlapping cohort entries |
A cohort table
library(CohortConstructor) cdm <- mockCohortConstructor() # collapse just cohort 1, with a gap of 7 days cdm$cohort1 <- cdm$cohort1 |> collapseCohorts(cohortId = 1, gap = 7) # collapse both cohorts with a gap of 1 year, and change table name cdm$collapsed_cohort <- cdm$cohort1 |> collapseCohorts(gap = 365, name = "collapsed_cohort")library(CohortConstructor) cdm <- mockCohortConstructor() # collapse just cohort 1, with a gap of 7 days cdm$cohort1 <- cdm$cohort1 |> collapseCohorts(cohortId = 1, gap = 7) # collapse both cohorts with a gap of 1 year, and change table name cdm$collapsed_cohort <- cdm$cohort1 |> collapseCohorts(gap = 365, name = "collapsed_cohort")
conceptCohort() creates a cohort table from patient records
from the clinical tables in the OMOP CDM.
The following tables are currently supported for creating concept cohorts:
condition_occurrence
device_exposure
drug_exposure
measurement
observation
procedure_occurrence
visit_occurrence
Cohort duration is based on record start and end (e.g. condition_start_date and condition_end_date for records coming from the condition_occurrence tables). So that the resulting table satisfies the requirements of an OMOP CDM cohort table:
Cohort entries will not overlap. Overlapping records will be combined based on the overlap argument.
Cohort entries will not go out of observation. If a record starts outside of an observation period it will be silently ignored. If a record ends outside of an observation period it will be trimmed so as to end at the preceding observation period end date.
conceptCohort( cdm, conceptSet, name, exit = "event_end_date", overlap = "merge", table = NULL, useRecordsBeforeObservation = FALSE, useSourceFields = FALSE, subsetCohort = NULL, subsetCohortId = NULL )conceptCohort( cdm, conceptSet, name, exit = "event_end_date", overlap = "merge", table = NULL, useRecordsBeforeObservation = FALSE, useSourceFields = FALSE, subsetCohort = NULL, subsetCohortId = NULL )
cdm |
A cdm reference. |
conceptSet |
A conceptSet, which can either be a codelist or a conceptSetExpression. |
name |
Name of the new cohort table created in the cdm object. |
exit |
How the cohort end date is defined. Can be either "event_end_date" or "event_start_date". |
overlap |
How to deal with overlapping records. In all cases cohort start will be set as the earliest start date. If "merge", cohort end will be the latest end date. If "extend", cohort end date will be set by adding together the total days from each of the overlapping records. |
table |
Name of OMOP tables to search for records of the concepts provided. If NULL, each concept will be search at the assigned domain in the concept table. |
useRecordsBeforeObservation |
If FALSE, only records that fall entirely (start and end) within an observation period are used. If TRUE, records that start before an observation period are included by shifting their start date to the beginning of the individual's subsequent observation period, and records that start or end outside an observation period are trimmed so that cohort records fall entirely within the corresponding observation period. |
useSourceFields |
If TRUE, the source concept_id fields will also be used when identifying relevant clinical records. If FALSE, only the standard concept_id fields will be used. |
subsetCohort |
A character refering to a cohort table containing individuals for whom cohorts will be generated. Only individuals in this table will appear in the generated cohort. |
subsetCohortId |
Optional. Specifies cohort IDs from the |
A cohort table
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort <- conceptCohort(cdm = cdm, conceptSet = list(a = 444074), name = "cohort") cdm$cohort |> attrition() # Create a cohort based on a concept set. The cohort exit is set to the event start date. # If two records overlap, the cohort end date is set as the sum of the duration of # all overlapping records. Only individuals included in the existing `cohort` will be considered. conceptSet <- list( "nitrogen" = c(35604434, 35604439), "potassium" = c(40741270, 42899580, 44081436) ) cdm$study_cohort <- conceptCohort(cdm = cdm, conceptSet = conceptSet, name = "study_cohort", exit = "event_start_date", overlap = "extend", subsetCohort = "cohort") cdm$study_cohort |> attrition()library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort <- conceptCohort(cdm = cdm, conceptSet = list(a = 444074), name = "cohort") cdm$cohort |> attrition() # Create a cohort based on a concept set. The cohort exit is set to the event start date. # If two records overlap, the cohort end date is set as the sum of the duration of # all overlapping records. Only individuals included in the existing `cohort` will be considered. conceptSet <- list( "nitrogen" = c(35604434, 35604439), "potassium" = c(40741270, 42899580, 44081436) ) cdm$study_cohort <- conceptCohort(cdm = cdm, conceptSet = conceptSet, name = "study_cohort", exit = "event_start_date", overlap = "extend", subsetCohort = "cohort") cdm$study_cohort |> attrition()
copyCohorts() copies an existing cohort table to a new location.
copyCohorts(cohort, name, n = 1, cohortId = NULL)copyCohorts(cohort, name, n = 1, cohortId = NULL)
cohort |
A cohort table in a cdm reference. |
name |
Name of the new cohort table created in the cdm object. |
n |
Number of times to duplicate the selected cohorts. |
cohortId |
Vector identifying which cohorts to include (cohort_definition_id or cohort_name). Cohorts not included will be removed from the cohort set. |
A new cohort table containing cohorts from the original cohort table.
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort3 <- copyCohorts(cdm$cohort1, n = 2, cohortId = 1, name = "cohort3")library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort3 <- copyCohorts(cdm$cohort1, n = 2, cohortId = 1, name = "cohort3")
Create cohort based on the death table
deathCohort(cdm, name, subsetCohort = NULL, subsetCohortId = NULL)deathCohort(cdm, name, subsetCohort = NULL, subsetCohortId = NULL)
cdm |
A cdm reference. |
name |
Name of the new cohort table created in the cdm object. |
subsetCohort |
A character refering to a cohort table containing individuals for whom cohorts will be generated. Only individuals in this table will appear in the generated cohort. |
subsetCohortId |
Optional. Specifies cohort IDs from the |
A cohort table with a death cohort in cdm
library(CohortConstructor) cdm <- mockCohortConstructor() # Generate a death cohort death_cohort <- deathCohort(cdm, name = "death_cohort") death_cohort # Create a demographics cohort with age range and sex filters cdm$my_cohort <- demographicsCohort(cdm, "my_cohort", ageRange = c(50,100), sex = "Female") # Generate a death cohort, restricted to individuals in 'my_cohort' death_cohort <- deathCohort(cdm, name = "death_cohort", subsetCohort = "my_cohort") death_cohort |> attrition()library(CohortConstructor) cdm <- mockCohortConstructor() # Generate a death cohort death_cohort <- deathCohort(cdm, name = "death_cohort") death_cohort # Create a demographics cohort with age range and sex filters cdm$my_cohort <- demographicsCohort(cdm, "my_cohort", ageRange = c(50,100), sex = "Female") # Generate a death cohort, restricted to individuals in 'my_cohort' death_cohort <- deathCohort(cdm, name = "death_cohort", subsetCohort = "my_cohort") death_cohort |> attrition()
demographicsCohort() creates a cohort table based on patient
characteristics. If and when an individual satisfies all the criteria they
enter the cohort. When they stop satisfying any of the criteria their
cohort entry ends.
demographicsCohort( cdm, name, ageRange = NULL, sex = NULL, minPriorObservation = NULL )demographicsCohort( cdm, name, ageRange = NULL, sex = NULL, minPriorObservation = NULL )
cdm |
A cdm reference. |
name |
Name of the new cohort table created in the cdm object. |
ageRange |
A list of vectors specifying minimum and maximum age. |
sex |
Can be "Both", "Male" or "Female". |
minPriorObservation |
A minimum number of continuous prior observation days in the database. |
A cohort table
library(CohortConstructor) cdm <- mockCohortConstructor() cohort <- cdm |> demographicsCohort(name = "cohort3", ageRange = c(18,40), sex = "Male") attrition(cohort) # Can also create multiple demographic cohorts, and add minimum prior history requirements. cohort <- cdm |> demographicsCohort(name = "cohort4", ageRange = list(c(0, 19),c(20, 64),c(65, 150)), sex = c("Male", "Female", "Both"), minPriorObservation = 365) attrition(cohort)library(CohortConstructor) cdm <- mockCohortConstructor() cohort <- cdm |> demographicsCohort(name = "cohort3", ageRange = c(18,40), sex = "Male") attrition(cohort) # Can also create multiple demographic cohorts, and add minimum prior history requirements. cohort <- cdm |> demographicsCohort(name = "cohort4", ageRange = list(c(0, 19),c(20, 64),c(65, 150)), sex = c("Male", "Female", "Both"), minPriorObservation = 365) attrition(cohort)
entryAtFirstDate() resets cohort start date based on a set of specified
column dates. The first date that occurs is chosen.
entryAtFirstDate( cohort, dateColumns, cohortId = NULL, returnReason = FALSE, keepDateColumns = TRUE, name = tableName(cohort), .softValidation = FALSE )entryAtFirstDate( cohort, dateColumns, cohortId = NULL, returnReason = FALSE, keepDateColumns = TRUE, name = tableName(cohort), .softValidation = FALSE )
cohort |
A cohort table in a cdm reference. |
dateColumns |
Character vector indicating date columns in the cohort table to consider. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
returnReason |
If TRUE it will return a column indicating which of the
|
keepDateColumns |
If TRUE the returned cohort will keep columns in
|
name |
Name of the new cohort table created in the cdm object. |
.softValidation |
Whether to perform a soft validation of consistency. If set to FALSE four additional checks will be performed: 1) a check that cohort end date is not before cohort start date, 2) a check that there are no missing values in required columns, 3) a check that cohort duration is all within observation period, and 4) that there are no overlapping cohort entries |
The cohort table.
library(CohortConstructor) library(PatientProfiles) cdm <- mockCohortConstructor() cdm$cohort1 <- cdm$cohort1 |> addTableIntersectDate( tableName = "drug_exposure", nameStyle = "prior_drug", order = "last", window = c(-Inf, 0) ) |> addPriorObservation(priorObservationType = "date", name = "cohort1") cdm$cohort1 |> entryAtFirstDate(dateColumns = c("prior_drug", "prior_observation"))library(CohortConstructor) library(PatientProfiles) cdm <- mockCohortConstructor() cdm$cohort1 <- cdm$cohort1 |> addTableIntersectDate( tableName = "drug_exposure", nameStyle = "prior_drug", order = "last", window = c(-Inf, 0) ) |> addPriorObservation(priorObservationType = "date", name = "cohort1") cdm$cohort1 |> entryAtFirstDate(dateColumns = c("prior_drug", "prior_observation"))
entryAtLastDate() resets cohort end date based on a set of specified
column dates. The last date is chosen.
entryAtLastDate( cohort, dateColumns, cohortId = NULL, returnReason = FALSE, keepDateColumns = TRUE, name = tableName(cohort), .softValidation = FALSE )entryAtLastDate( cohort, dateColumns, cohortId = NULL, returnReason = FALSE, keepDateColumns = TRUE, name = tableName(cohort), .softValidation = FALSE )
cohort |
A cohort table in a cdm reference. |
dateColumns |
Character vector indicating date columns in the cohort table to consider. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
returnReason |
If TRUE it will return a column indicating which of the
|
keepDateColumns |
If TRUE the returned cohort will keep columns in
|
name |
Name of the new cohort table created in the cdm object. |
.softValidation |
Whether to perform a soft validation of consistency. If set to FALSE four additional checks will be performed: 1) a check that cohort end date is not before cohort start date, 2) a check that there are no missing values in required columns, 3) a check that cohort duration is all within observation period, and 4) that there are no overlapping cohort entries |
The cohort table.
library(CohortConstructor) library(PatientProfiles) cdm <- mockCohortConstructor() cdm$cohort1 <- cdm$cohort1 |> addTableIntersectDate( tableName = "drug_exposure", nameStyle = "prior_drug", order = "last", window = c(-Inf, 0) ) |> addPriorObservation(priorObservationType = "date", name = "cohort1") cdm$cohort1 |> entryAtLastDate(dateColumns = c("prior_drug", "prior_observation"))library(CohortConstructor) library(PatientProfiles) cdm <- mockCohortConstructor() cdm$cohort1 <- cdm$cohort1 |> addTableIntersectDate( tableName = "drug_exposure", nameStyle = "prior_drug", order = "last", window = c(-Inf, 0) ) |> addPriorObservation(priorObservationType = "date", name = "cohort1") cdm$cohort1 |> entryAtLastDate(dateColumns = c("prior_drug", "prior_observation"))
This functions changes cohort end date to subject's death date. In the case were this generates overlapping records in the cohort, those overlapping entries will be merged.
exitAtDeath( cohort, cohortId = NULL, requireDeath = FALSE, name = tableName(cohort), .softValidation = FALSE )exitAtDeath( cohort, cohortId = NULL, requireDeath = FALSE, name = tableName(cohort), .softValidation = FALSE )
cohort |
A cohort table in a cdm reference. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
requireDeath |
If TRUE, subjects without a death record will be dropped, while if FALSE their end date will be left as is. |
name |
Name of the new cohort table created in the cdm object. |
.softValidation |
Whether to perform a soft validation of consistency. If set to FALSE four additional checks will be performed: 1) a check that cohort end date is not before cohort start date, 2) a check that there are no missing values in required columns, 3) a check that cohort duration is all within observation period, and 4) that there are no overlapping cohort entries |
The cohort table.
library(PatientProfiles) library(CohortConstructor) cdm <- mockPatientProfiles() cdm$cohort1 |> exitAtDeath()library(PatientProfiles) library(CohortConstructor) cdm <- mockPatientProfiles() cdm$cohort1 |> exitAtDeath()
exitAtFirstDate() resets cohort end date based on a set of specified
column dates. The first date that occurs is chosen.
exitAtFirstDate( cohort, dateColumns, cohortId = NULL, returnReason = FALSE, keepDateColumns = TRUE, name = tableName(cohort), .softValidation = FALSE )exitAtFirstDate( cohort, dateColumns, cohortId = NULL, returnReason = FALSE, keepDateColumns = TRUE, name = tableName(cohort), .softValidation = FALSE )
cohort |
A cohort table in a cdm reference. |
dateColumns |
Character vector indicating date columns in the cohort table to consider. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
returnReason |
If TRUE it will return a column indicating which of the
|
keepDateColumns |
If TRUE the returned cohort will keep columns in
|
name |
Name of the new cohort table created in the cdm object. |
.softValidation |
Whether to perform a soft validation of consistency. If set to FALSE four additional checks will be performed: 1) a check that cohort end date is not before cohort start date, 2) a check that there are no missing values in required columns, 3) a check that cohort duration is all within observation period, and 4) that there are no overlapping cohort entries |
The cohort table.
library(CohortConstructor) library(PatientProfiles) cdm <- mockCohortConstructor() cdm$cohort1 <- cdm$cohort1 |> addTableIntersectDate(tableName = "observation", nameStyle = "next_obs", order = "first") |> addFutureObservation(futureObservationType = "date", name = "cohort1") cdm$cohort1 |> exitAtFirstDate(dateColumns = c("next_obs", "future_observation"))library(CohortConstructor) library(PatientProfiles) cdm <- mockCohortConstructor() cdm$cohort1 <- cdm$cohort1 |> addTableIntersectDate(tableName = "observation", nameStyle = "next_obs", order = "first") |> addFutureObservation(futureObservationType = "date", name = "cohort1") cdm$cohort1 |> exitAtFirstDate(dateColumns = c("next_obs", "future_observation"))
exitAtLastDate() resets cohort end date based on a set of specified
column dates. The last date that occurs is chosen.
exitAtLastDate( cohort, dateColumns, cohortId = NULL, returnReason = FALSE, keepDateColumns = TRUE, name = tableName(cohort), .softValidation = FALSE )exitAtLastDate( cohort, dateColumns, cohortId = NULL, returnReason = FALSE, keepDateColumns = TRUE, name = tableName(cohort), .softValidation = FALSE )
cohort |
A cohort table in a cdm reference. |
dateColumns |
Character vector indicating date columns in the cohort table to consider. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
returnReason |
If TRUE it will return a column indicating which of the
|
keepDateColumns |
If TRUE the returned cohort will keep columns in
|
name |
Name of the new cohort table created in the cdm object. |
.softValidation |
Whether to perform a soft validation of consistency. If set to FALSE four additional checks will be performed: 1) a check that cohort end date is not before cohort start date, 2) a check that there are no missing values in required columns, 3) a check that cohort duration is all within observation period, and 4) that there are no overlapping cohort entries |
The cohort table.
library(CohortConstructor) library(PatientProfiles) cdm <- mockCohortConstructor() cdm$cohort1 <- cdm$cohort1 |> addTableIntersectDate(tableName = "observation", nameStyle = "next_obs", order = "first") |> addFutureObservation(futureObservationType = "date", name = "cohort1") cdm$cohort1 |> exitAtLastDate(dateColumns = c("next_obs", "future_observation"))library(CohortConstructor) library(PatientProfiles) cdm <- mockCohortConstructor() cdm$cohort1 <- cdm$cohort1 |> addTableIntersectDate(tableName = "observation", nameStyle = "next_obs", order = "first") |> addFutureObservation(futureObservationType = "date", name = "cohort1") cdm$cohort1 |> exitAtLastDate(dateColumns = c("next_obs", "future_observation"))
exitAtObservationEnd() resets cohort end date based on a set of specified
column dates. The last date that occurs is chosen.
This functions changes cohort end date to the end date of the observation period corresponding to the cohort entry. In the case were this generates overlapping records in the cohort, overlapping entries will be merged.
exitAtObservationEnd( cohort, cohortId = NULL, persistAcrossObservationPeriods = FALSE, name = tableName(cohort), .softValidation = FALSE )exitAtObservationEnd( cohort, cohortId = NULL, persistAcrossObservationPeriods = FALSE, name = tableName(cohort), .softValidation = FALSE )
cohort |
A cohort table in a cdm reference. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
persistAcrossObservationPeriods |
If FALSE, limits the cohort to one entry per person, ending at the current observation period. If TRUE, subsequent observation periods will create new cohort entries (starting from the start of that observation period and ending at the end of that observation period). |
name |
Name of the new cohort table created in the cdm object. |
.softValidation |
Whether to perform a soft validation of consistency. If set to FALSE four additional checks will be performed: 1) a check that cohort end date is not before cohort start date, 2) a check that there are no missing values in required columns, 3) a check that cohort duration is all within observation period, and 4) that there are no overlapping cohort entries |
The cohort table.
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> exitAtObservationEnd()library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> exitAtObservationEnd()
intersectCohorts() combines different cohort entries, with those records
that overlap combined and kept. Cohort entries are when an individual was in
both of the cohorts.
intersectCohorts( cohort, cohortId = NULL, gap = 0, returnNonOverlappingCohorts = FALSE, keepOriginalCohorts = FALSE, name = tableName(cohort), .softValidation = FALSE )intersectCohorts( cohort, cohortId = NULL, gap = 0, returnNonOverlappingCohorts = FALSE, keepOriginalCohorts = FALSE, name = tableName(cohort), .softValidation = FALSE )
cohort |
A cohort table in a cdm reference. |
cohortId |
Vector identifying which cohorts to include (cohort_definition_id or cohort_name). Cohorts not included will be removed from the cohort set. |
gap |
Number of days between two subsequent cohort entries to be merged in a single cohort record. |
returnNonOverlappingCohorts |
Whether the generated cohorts are mutually exclusive or not. |
keepOriginalCohorts |
If TRUE the original cohorts will be return together with the new ones. If FALSE only the new cohort will be returned. |
name |
Name of the new cohort table created in the cdm object. |
.softValidation |
Whether to perform a soft validation of consistency. If set to FALSE four additional checks will be performed: 1) a check that cohort end date is not before cohort start date, 2) a check that there are no missing values in required columns, 3) a check that cohort duration is all within observation period, and 4) that there are no overlapping cohort entries |
A cohort table.
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort3 <- intersectCohorts(cohort = cdm$cohort2, name = "cohort3") settings(cdm$cohort3)library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort3 <- intersectCohorts(cohort = cdm$cohort2, name = "cohort3") settings(cdm$cohort3)
matchCohorts() generate a new cohort matched to individuals in an
existing cohort. Individuals can be matched based on year of birth and sex.
Matching is done at the record level, so if individuals have multiple
cohort entries they can be matched to different individuals for each of their
records.
Two new cohorts will be created when matching. The first is those cohort entries which were matched ("_sampled" is added to the original cohort name for this cohort). The other is the matches found from the database population ("_matched" is added to the original cohort name for this cohort).
matchCohorts( cohort, cohortId = NULL, matchSex = TRUE, matchYearOfBirth = TRUE, ratio = 1, keepOriginalCohorts = FALSE, name = tableName(cohort), .softValidation = FALSE )matchCohorts( cohort, cohortId = NULL, matchSex = TRUE, matchYearOfBirth = TRUE, ratio = 1, keepOriginalCohorts = FALSE, name = tableName(cohort), .softValidation = FALSE )
cohort |
A cohort table in a cdm reference. |
cohortId |
Vector identifying which cohorts to include (cohort_definition_id or cohort_name). Cohorts not included will be removed from the cohort set. |
matchSex |
Whether to match in sex. |
matchYearOfBirth |
Whether to match in year of birth. |
ratio |
Number of allowed matches per individual in the target cohort. |
keepOriginalCohorts |
If TRUE the original cohorts will be return together with the new ones. If FALSE only the new cohort will be returned. |
name |
Name of the new cohort table created in the cdm object. |
.softValidation |
Whether to perform a soft validation of consistency. If set to FALSE four additional checks will be performed: 1) a check that cohort end date is not before cohort start date, 2) a check that there are no missing values in required columns, 3) a check that cohort duration is all within observation period, and 4) that there are no overlapping cohort entries |
A cohort table.
library(CohortConstructor) library(dplyr) cdm <- mockCohortConstructor() cdm$new_matched_cohort <- cdm$cohort2 |> matchCohorts( name = "new_matched_cohort", cohortId = 2, matchSex = TRUE, matchYearOfBirth = TRUE, ratio = 1) cdm$new_matched_cohortlibrary(CohortConstructor) library(dplyr) cdm <- mockCohortConstructor() cdm$new_matched_cohort <- cdm$cohort2 |> matchCohorts( name = "new_matched_cohort", cohortId = 2, matchSex = TRUE, matchYearOfBirth = TRUE, ratio = 1) cdm$new_matched_cohort
measurementCohort() creates cohorts based on patient records from the
measurement or observation tables. It extends the function conceptCohort()
by allowing users to specify measurement values associated with those records.
This function supports both concept-based and value-based filtering:
Either valueAsConcept or valueAsNumber must be provided.
If one of them is specified (not NULL), only records that satisfy the other filter will be included.
If both are provided, records that meet either filter will be included.
measurementCohort( cdm, conceptSet, name, valueAsConcept = NULL, valueAsNumber = NULL, table = NULL, useRecordsBeforeObservation = FALSE, useSourceFields = FALSE, subsetCohort = NULL, subsetCohortId = NULL )measurementCohort( cdm, conceptSet, name, valueAsConcept = NULL, valueAsNumber = NULL, table = NULL, useRecordsBeforeObservation = FALSE, useSourceFields = FALSE, subsetCohort = NULL, subsetCohortId = NULL )
cdm |
A cdm reference. |
conceptSet |
A conceptSet, which can either be a codelist or a conceptSetExpression. |
name |
Name of the new cohort table created in the cdm object. |
valueAsConcept |
A named list defining cohorts based on measurement
values as concept IDs. Each element name defines the name of cohort to
create, and its value is a vector of concept IDs used to filter measurements
by For instance, to create two bmi cohorts from a bmi See more examples in the function examples. |
valueAsNumber |
A named list defining cohorts based on numeric
measurement ranges.
Each list element should contain one or more numeric vectors of length two,
specifying the allowed range(s) for the measurement value.
If the numeric vector is named, the name should correspond to the
For example, the following creates a cohort named "low_weight" based on
measurements recorded in kilograms (unit_concept_id = 9529) and stones
(unit_concept_id = 21498905):
See the examples below for how to define multiple cohorts based on different measurement filters. |
table |
Character vector specifying which OMOP tables to use. Accepts "measurement", "observation", or both. |
useRecordsBeforeObservation |
If FALSE, only records that fall entirely (start and end) within an observation period are used. If TRUE, records that start before an observation period are included by shifting their start date to the beginning of the individual's subsequent observation period, and records that start or end outside an observation period are trimmed so that cohort records fall entirely within the corresponding observation period. |
useSourceFields |
If TRUE, the source concept_id fields will also be used when identifying relevant clinical records. If FALSE, only the standard concept_id fields will be used. |
subsetCohort |
A character refering to a cohort table containing individuals for whom cohorts will be generated. Only individuals in this table will appear in the generated cohort. |
subsetCohortId |
Optional. Specifies cohort IDs from the |
A cohort table.
library(CohortConstructor) library(omock) library(dplyr) cdm <- mockVocabularyTables(concept = tibble( concept_id = c(4326744, 4298393, 45770407, 8876, 4124457), concept_name = c("Blood pressure", "Systemic blood pressure", "Baseline blood pressure", "millimeter mercury column", "Normal range"), domain_id = "Measurement", vocabulary_id = c("SNOMED", "SNOMED", "SNOMED", "UCUM", "SNOMED"), standard_concept = "S", concept_class_id = c("Observable Entity", "Observable Entity", "Observable Entity", "Unit", "Qualifier Value"), concept_code = NA_character_, valid_start_date = as.Date(NA_character_), valid_end_date = as.Date(NA_character_), invalid_reason = NA_character_ )) |> mockCdmFromTables(tables = list( measurement = tibble( measurement_id = 1:4L, person_id = c(1L, 1L, 2L, 3L), measurement_concept_id = c(4326744L, 4298393L, 4298393L, 45770407L), measurement_date = as.Date(c("2000-07-01", "2000-12-11", "2002-09-08", "2015-02-19")), measurement_type_concept_id = 0L, value_as_number = c(100, 125, NA, NA), value_as_concept_id = c(0L, 0L, 0L, 4124457L), unit_concept_id = c(8876L, 8876L, 0L, 0L) ) )) # create one cohort of blood pressure measurements indicating normal levels cdm$cohort <- measurementCohort( cdm = cdm, name = "cohort", conceptSet = list("blood_pressure" = c(4326744, 4298393, 45770407)), valueAsConcept = list("normal_blood_preassure" = c(4124457)), valueAsNumber = list("normal_blood_preassure" = list("8876" = c(70, 120))), useRecordsBeforeObservation = FALSE ) cdm$cohort # create two cohorts of blood preassure measurements, one with results # indicating normal blood pressure and the other inidcating high cdm$cohort2 <- measurementCohort( cdm = cdm, name = "cohort2", conceptSet = list("blood_pressure" = c(4326744, 4298393, 45770407)), valueAsConcept = list( "normal_blood_pressure" = 4124457, "high_blood_pressure" = 4328749 ), valueAsNumber = list( "normal_blood_pressure" = list("8876" = c(70, 120)), "high_blood_pressure" = list("8876" = c(121, 200)) ), useRecordsBeforeObservation = TRUE ) cdm$cohort2 |> settings()library(CohortConstructor) library(omock) library(dplyr) cdm <- mockVocabularyTables(concept = tibble( concept_id = c(4326744, 4298393, 45770407, 8876, 4124457), concept_name = c("Blood pressure", "Systemic blood pressure", "Baseline blood pressure", "millimeter mercury column", "Normal range"), domain_id = "Measurement", vocabulary_id = c("SNOMED", "SNOMED", "SNOMED", "UCUM", "SNOMED"), standard_concept = "S", concept_class_id = c("Observable Entity", "Observable Entity", "Observable Entity", "Unit", "Qualifier Value"), concept_code = NA_character_, valid_start_date = as.Date(NA_character_), valid_end_date = as.Date(NA_character_), invalid_reason = NA_character_ )) |> mockCdmFromTables(tables = list( measurement = tibble( measurement_id = 1:4L, person_id = c(1L, 1L, 2L, 3L), measurement_concept_id = c(4326744L, 4298393L, 4298393L, 45770407L), measurement_date = as.Date(c("2000-07-01", "2000-12-11", "2002-09-08", "2015-02-19")), measurement_type_concept_id = 0L, value_as_number = c(100, 125, NA, NA), value_as_concept_id = c(0L, 0L, 0L, 4124457L), unit_concept_id = c(8876L, 8876L, 0L, 0L) ) )) # create one cohort of blood pressure measurements indicating normal levels cdm$cohort <- measurementCohort( cdm = cdm, name = "cohort", conceptSet = list("blood_pressure" = c(4326744, 4298393, 45770407)), valueAsConcept = list("normal_blood_preassure" = c(4124457)), valueAsNumber = list("normal_blood_preassure" = list("8876" = c(70, 120))), useRecordsBeforeObservation = FALSE ) cdm$cohort # create two cohorts of blood preassure measurements, one with results # indicating normal blood pressure and the other inidcating high cdm$cohort2 <- measurementCohort( cdm = cdm, name = "cohort2", conceptSet = list("blood_pressure" = c(4326744, 4298393, 45770407)), valueAsConcept = list( "normal_blood_pressure" = 4124457, "high_blood_pressure" = 4328749 ), valueAsNumber = list( "normal_blood_pressure" = list("8876" = c(70, 120)), "high_blood_pressure" = list("8876" = c(121, 200)) ), useRecordsBeforeObservation = TRUE ) cdm$cohort2 |> settings()
mockCohortConstructor() creates an example dataset that can be used for
demonstrating and testing the package
mockCohortConstructor(source = "local", seed = 1)mockCohortConstructor(source = "local", seed = 1)
source |
Source for the mock cdm, it can either be 'local' or 'duckdb'. |
seed |
An optional integer used to set the seed for random number generation, ensuring reproducibility of the generated data. If provided, this seed allows the function to produce consistent results each time. If 'NULL', the seed is not set, which can lead to different outputs on each run. |
cdm object
library(CohortConstructor) cdm <- mockCohortConstructor() cdmlibrary(CohortConstructor) cdm <- mockCohortConstructor() cdm
Set cohort start or cohort end
padCohortDate( cohort, days, cohortDate = "cohort_start_date", indexDate = "cohort_start_date", collapse = TRUE, requireFullContribution = FALSE, cohortId = NULL, name = tableName(cohort), .softValidation = FALSE )padCohortDate( cohort, days, cohortDate = "cohort_start_date", indexDate = "cohort_start_date", collapse = TRUE, requireFullContribution = FALSE, cohortId = NULL, name = tableName(cohort), .softValidation = FALSE )
cohort |
A cohort table in a cdm reference. |
days |
Integer with the number of days to add or name of a column (that must be numeric) to add. |
cohortDate |
'cohort_start_date' or 'cohort_end_date'. |
indexDate |
Variable in cohort that contains the index date to add. |
collapse |
Whether to collapse the overlapping records (TRUE) or drop the records that have an ongoing prior record. |
requireFullContribution |
Whether to require individuals to contribute all required days. If TRUE, those individuals for which adding days would take them out of observation will be dropped. If FALSE, days will only be added up to the day when the individual leaves observation. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
name |
Name of the new cohort table created in the cdm object. |
.softValidation |
Whether to perform a soft validation of consistency. If set to FALSE four additional checks will be performed: 1) a check that cohort end date is not before cohort start date, 2) a check that there are no missing values in required columns, 3) a check that cohort duration is all within observation period, and 4) that there are no overlapping cohort entries |
Cohort table
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> padCohortDate( cohortDate = "cohort_end_date", indexDate = "cohort_start_date", days = 10)library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> padCohortDate( cohortDate = "cohort_end_date", indexDate = "cohort_start_date", days = 10)
padCohortEnd() Adds (or subtracts) a certain number of days to the cohort
end date. Note:
If the days added means that cohort end would be after observation period end date, then observation period end date will be used for cohort exit.
If the days added means that cohort exit would be after the next cohort start then these overlapping cohort entries will be collapsed.
If days subtracted means that cohort end would be before cohort start then the cohort entry will be dropped.
padCohortEnd( cohort, days, collapse = TRUE, requireFullContribution = FALSE, cohortId = NULL, name = tableName(cohort), .softValidation = FALSE )padCohortEnd( cohort, days, collapse = TRUE, requireFullContribution = FALSE, cohortId = NULL, name = tableName(cohort), .softValidation = FALSE )
cohort |
A cohort table in a cdm reference. |
days |
Integer with the number of days to add or name of a column (that must be numeric) to add. |
collapse |
Whether to collapse the overlapping records (TRUE) or drop the records that have an ongoing prior record. |
requireFullContribution |
Whether to require individuals to contribute all required days. If TRUE, those individuals for which adding days would take them out of observation will be dropped. If FALSE, days will only be added up to the day when the individual leaves observation. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
name |
Name of the new cohort table created in the cdm object. |
.softValidation |
Whether to perform a soft validation of consistency. If set to FALSE four additional checks will be performed: 1) a check that cohort end date is not before cohort start date, 2) a check that there are no missing values in required columns, 3) a check that cohort duration is all within observation period, and 4) that there are no overlapping cohort entries |
Cohort table
library(CohortConstructor) cdm <- mockCohortConstructor() # add 10 days to each cohort exit cdm$cohort1 |> padCohortEnd(days = 10)library(CohortConstructor) cdm <- mockCohortConstructor() # add 10 days to each cohort exit cdm$cohort1 |> padCohortEnd(days = 10)
padCohortStart() Adds (or subtracts) a certain number of days to the cohort
start date. Note:
If the days added means that cohort start would be after cohort end then the cohort entry will be dropped.
If subtracting day means that cohort start would be before observation period start then the cohort entry will be dropped.
padCohortStart( cohort, days, collapse = TRUE, requireFullContribution = FALSE, cohortId = NULL, name = tableName(cohort), .softValidation = FALSE )padCohortStart( cohort, days, collapse = TRUE, requireFullContribution = FALSE, cohortId = NULL, name = tableName(cohort), .softValidation = FALSE )
cohort |
A cohort table in a cdm reference. |
days |
Integer with the number of days to add or name of a column (that must be numeric) to add. |
collapse |
Whether to collapse the overlapping records (TRUE) or drop the records that have an ongoing prior record. |
requireFullContribution |
Whether to require individuals to contribute all required days. If TRUE, those individuals for which adding days would take them out of observation will be dropped. If FALSE, days will only be added up to the day when the individual leaves observation. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
name |
Name of the new cohort table created in the cdm object. |
.softValidation |
Whether to perform a soft validation of consistency. If set to FALSE four additional checks will be performed: 1) a check that cohort end date is not before cohort start date, 2) a check that there are no missing values in required columns, 3) a check that cohort duration is all within observation period, and 4) that there are no overlapping cohort entries |
Cohort table
library(CohortConstructor) cdm <- mockCohortConstructor() # add 10 days to each cohort entry cdm$cohort1 |> padCohortStart(days = 10)library(CohortConstructor) cdm <- mockCohortConstructor() # add 10 days to each cohort entry cdm$cohort1 |> padCohortStart(days = 10)
Utility function to change the name of a cohort.
renameCohort(cohort, newCohortName, cohortId = NULL)renameCohort(cohort, newCohortName, cohortId = NULL)
cohort |
A cohort table in a cdm reference. |
newCohortName |
Character vector with same |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
A cohort_table object.
library(CohortConstructor) cdm <- mockCohortConstructor() settings(cdm$cohort1) cdm$cohort1 <- cdm$cohort1 |> renameCohort(newCohortName = "new_name") settings(cdm$cohort1)library(CohortConstructor) cdm <- mockCohortConstructor() settings(cdm$cohort1) cdm$cohort1 <- cdm$cohort1 |> renameCohort(newCohortName = "new_name") settings(cdm$cohort1)
requireAge() filters cohort records, keeping only records where individuals
satisfy the specified age criteria.
requireAge( cohort, ageRange, cohortId = NULL, indexDate = "cohort_start_date", atFirst = FALSE, name = tableName(cohort) )requireAge( cohort, ageRange, cohortId = NULL, indexDate = "cohort_start_date", atFirst = FALSE, name = tableName(cohort) )
cohort |
A cohort table in a cdm reference. |
ageRange |
A list of vectors specifying minimum and maximum age. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
indexDate |
Variable in cohort that contains the date to compute the demographics characteristics on which to restrict on. |
atFirst |
If FALSE the requirement will be applied to all records, if TRUE, it will only be required for the first entry of each subject. |
name |
Name of the new cohort table created in the cdm object. |
The cohort table with only records for individuals satisfying the age requirement
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireAge(indexDate = "cohort_start_date", ageRange = list(c(18, 65)))library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireAge(indexDate = "cohort_start_date", ageRange = list(c(18, 65)))
requireCohortIntersect() filters a cohort table based on a requirement
that an individual is seen (or not seen) in another cohort in some time
window around an index date.
requireCohortIntersect( cohort, targetCohortTable, window, intersections = c(1, Inf), cohortId = NULL, targetCohortId = NULL, cohortCombinationCriteria = "all", indexDate = "cohort_start_date", targetStartDate = "cohort_start_date", targetEndDate = "cohort_end_date", censorDate = NULL, atFirst = FALSE, name = tableName(cohort) )requireCohortIntersect( cohort, targetCohortTable, window, intersections = c(1, Inf), cohortId = NULL, targetCohortId = NULL, cohortCombinationCriteria = "all", indexDate = "cohort_start_date", targetStartDate = "cohort_start_date", targetEndDate = "cohort_end_date", censorDate = NULL, atFirst = FALSE, name = tableName(cohort) )
cohort |
A cohort table in a cdm reference. |
targetCohortTable |
Name of the cohort that we want to check for intersect. |
window |
A list of vectors specifying minimum and maximum days from
|
intersections |
A range indicating number of intersections for criteria to be fulfilled. If a single number is passed, the number of intersections must match this. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
targetCohortId |
Vector of cohort definition ids to include. |
cohortCombinationCriteria |
Can be 'all', 'any', or a numeric vector (length 1 or 2) that specifies how many of the target cohorts must meet the intersection requirement. Examples:
|
indexDate |
Name of the column in the cohort that contains the date to compute the intersection. |
targetStartDate |
Start date of reference in cohort table. |
targetEndDate |
End date of reference in cohort table. If NULL, incidence of target event in the window will be considered as intersection, otherwise prevalence of that event will be used as intersection (overlap between cohort and event). |
censorDate |
Whether to censor overlap events at a specific date or a column date of the cohort. |
atFirst |
If FALSE the requirement will be applied to all records, if TRUE, it will only be required for the first entry of each subject. |
name |
Name of the new cohort table created in the cdm object. |
Cohort table with only those entries satisfying the criteria
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireCohortIntersect(targetCohortTable = "cohort2", targetCohortId = 1, indexDate = "cohort_start_date", window = c(-Inf, 0))library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireCohortIntersect(targetCohortTable = "cohort2", targetCohortId = 1, indexDate = "cohort_start_date", window = c(-Inf, 0))
requireConceptIntersect() filters a cohort table based on a requirement
that an individual is seen (or not seen) to have events related to a concept
list in some time window around an index date.
requireConceptIntersect( cohort, conceptSet, window, intersections = c(1, Inf), cohortId = NULL, cohortCombinationCriteria = "all", indexDate = "cohort_start_date", targetStartDate = "event_start_date", targetEndDate = "event_end_date", inObservation = TRUE, censorDate = NULL, atFirst = FALSE, name = tableName(cohort) )requireConceptIntersect( cohort, conceptSet, window, intersections = c(1, Inf), cohortId = NULL, cohortCombinationCriteria = "all", indexDate = "cohort_start_date", targetStartDate = "event_start_date", targetEndDate = "event_end_date", inObservation = TRUE, censorDate = NULL, atFirst = FALSE, name = tableName(cohort) )
cohort |
A cohort table in a cdm reference. |
conceptSet |
A conceptSet, which can either be a codelist or a conceptSetExpression. |
window |
A list of vectors specifying minimum and maximum days from
|
intersections |
A range indicating number of intersections for criteria to be fulfilled. If a single number is passed, the number of intersections must match this. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
cohortCombinationCriteria |
Can be 'all', 'any', or a numeric vector (length 1 or 2) that specifies how many of the target cohorts must meet the intersection requirement. Examples:
|
indexDate |
Name of the column in the cohort that contains the date to compute the intersection. |
targetStartDate |
Start date of reference in cohort table. |
targetEndDate |
End date of reference in cohort table. If NULL, incidence of target event in the window will be considered as intersection, otherwise prevalence of that event will be used as intersection (overlap between cohort and event). |
inObservation |
If TRUE only records inside an observation period will be considered |
censorDate |
Whether to censor overlap events at a specific date or a column date of the cohort. |
atFirst |
If FALSE the requirement will be applied to all records, if TRUE, it will only be required for the first entry of each subject. |
name |
Name of the new cohort table created in the cdm object. |
Cohort table
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort2 <- requireConceptIntersect( cohort = cdm$cohort1, conceptSet = list(a = 194152), window = c(-Inf, 0), name = "cohort2")library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort2 <- requireConceptIntersect( cohort = cdm$cohort1, conceptSet = list(a = 194152), window = c(-Inf, 0), name = "cohort2")
requireDemographics() filters cohort records, keeping only records where
individuals satisfy the specified demographic criteria.
requireDemographics( cohort, cohortId = NULL, indexDate = "cohort_start_date", ageRange = list(c(0, 150)), sex = c("Both"), minPriorObservation = 0, minFutureObservation = 0, atFirst = FALSE, name = tableName(cohort) )requireDemographics( cohort, cohortId = NULL, indexDate = "cohort_start_date", ageRange = list(c(0, 150)), sex = c("Both"), minPriorObservation = 0, minFutureObservation = 0, atFirst = FALSE, name = tableName(cohort) )
cohort |
A cohort table in a cdm reference. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
indexDate |
Variable in cohort that contains the date to compute the demographics characteristics on which to restrict on. |
ageRange |
A list of vectors specifying minimum and maximum age. |
sex |
Can be "Both", "Male" or "Female". |
minPriorObservation |
A minimum number of continuous prior observation days in the database. |
minFutureObservation |
A minimum number of continuous future observation days in the database. |
atFirst |
If FALSE the requirement will be applied to all records, if TRUE, it will only be required for the first entry of each subject. |
name |
Name of the new cohort table created in the cdm object. |
The cohort table with only records for individuals satisfying the demographic requirements
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireDemographics(indexDate = "cohort_start_date", ageRange = list(c(18, 65)), sex = "Female", minPriorObservation = 365)library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireDemographics(indexDate = "cohort_start_date", ageRange = list(c(18, 65)), sex = "Female", minPriorObservation = 365)
requireDuration() filters cohort records, keeping only those which last
for the specified amount of days
requireDuration( cohort, daysInCohort, cohortId = NULL, name = tableName(cohort) )requireDuration( cohort, daysInCohort, cohortId = NULL, name = tableName(cohort) )
cohort |
A cohort table in a cdm reference. |
daysInCohort |
Number of days cohort entries must last. Can be a vector of length two if a range, or a vector of length one if a specific number of days. Note, cohort entry and exit on the same day counts as one day in the cohort. So if, for example, you wish to require individuals are in the cohort for at least one night then set daysInCohort to c(2, Inf). Meanwhile, if set to c(30, 90) then only cohort entries that are 30 days or more longer and shorter or equal to 90 days will be kept. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
name |
Name of the new cohort table created in the cdm object. |
The cohort table with any cohort entries that last less or more than the required duration dropped
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireDuration(daysInCohort = c(2, Inf))library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireDuration(daysInCohort = c(2, Inf))
requireFutureObservation() filters cohort records, keeping only records
where individuals satisfy the specified future observation criteria.
requireFutureObservation( cohort, minFutureObservation, cohortId = NULL, indexDate = "cohort_start_date", atFirst = FALSE, name = tableName(cohort) )requireFutureObservation( cohort, minFutureObservation, cohortId = NULL, indexDate = "cohort_start_date", atFirst = FALSE, name = tableName(cohort) )
cohort |
A cohort table in a cdm reference. |
minFutureObservation |
A minimum number of continuous future observation days in the database. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
indexDate |
Variable in cohort that contains the date to compute the demographics characteristics on which to restrict on. |
atFirst |
If FALSE the requirement will be applied to all records, if TRUE, it will only be required for the first entry of each subject. |
name |
Name of the new cohort table created in the cdm object. |
The cohort table with only records for individuals satisfying the future observation requirement
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireFutureObservation(indexDate = "cohort_start_date", minFutureObservation = 30)library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireFutureObservation(indexDate = "cohort_start_date", minFutureObservation = 30)
requireInDateRange() filters cohort records, keeping only those for
which the index date is within the specified date range.
requireInDateRange( cohort, dateRange, cohortId = NULL, indexDate = "cohort_start_date", atFirst = FALSE, name = tableName(cohort) )requireInDateRange( cohort, dateRange, cohortId = NULL, indexDate = "cohort_start_date", atFirst = FALSE, name = tableName(cohort) )
cohort |
A cohort table in a cdm reference. |
dateRange |
A date vector with the minimum and maximum dates between which the index date must have been observed. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
indexDate |
Name of the column in the cohort that contains the date of interest. |
atFirst |
If FALSE the requirement will be applied to all records, if TRUE, it will only be required for the first entry of each subject. |
name |
Name of the new cohort table created in the cdm object. |
The cohort table with any cohort entries outside of the date range dropped
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort2 <- cdm$cohort1 |> requireInDateRange( indexDate = "cohort_start_date", dateRange = as.Date(c("2010-01-01", "2019-01-01")), name = "cohort2" ) # modify same input cohort table to start between 2010 until end of data cdm$cohort1 <- cdm$cohort1 |> requireInDateRange( indexDate = "cohort_start_date", dateRange = as.Date(c("2010-01-01", NA)) )library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort2 <- cdm$cohort1 |> requireInDateRange( indexDate = "cohort_start_date", dateRange = as.Date(c("2010-01-01", "2019-01-01")), name = "cohort2" ) # modify same input cohort table to start between 2010 until end of data cdm$cohort1 <- cdm$cohort1 |> requireInDateRange( indexDate = "cohort_start_date", dateRange = as.Date(c("2010-01-01", NA)) )
requireIsEntry() filters cohort records, keeping only a range a specified
cohort entries per person.
requireIsEntry(cohort, entryRange, cohortId = NULL, name = tableName(cohort))requireIsEntry(cohort, entryRange, cohortId = NULL, name = tableName(cohort))
cohort |
A cohort table in a cdm reference. |
entryRange |
Range for entries to include. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
name |
Name of the new cohort table created in the cdm object. |
A cohort table in a cdm reference.
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 <- requireIsEntry(cdm$cohort1, c(1, Inf))library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 <- requireIsEntry(cdm$cohort1, c(1, Inf))
requireIsFirstEntry() filters cohort records, keeping only the first
cohort entry per person.
requireIsFirstEntry(cohort, cohortId = NULL, name = tableName(cohort))requireIsFirstEntry(cohort, cohortId = NULL, name = tableName(cohort))
cohort |
A cohort table in a cdm reference. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
name |
Name of the new cohort table created in the cdm object. |
A cohort table in a cdm reference.
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 <- requireIsFirstEntry(cdm$cohort1)library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 <- requireIsFirstEntry(cdm$cohort1)
requireIsLastEntry() filters cohort records, keeping only the last
cohort entry per person.
requireIsLastEntry(cohort, cohortId = NULL, name = tableName(cohort))requireIsLastEntry(cohort, cohortId = NULL, name = tableName(cohort))
cohort |
A cohort table in a cdm reference. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
name |
Name of the new cohort table created in the cdm object. |
A cohort table in a cdm reference.
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 <- requireIsLastEntry(cdm$cohort1)library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 <- requireIsLastEntry(cdm$cohort1)
requireMinCohortCount() filters an existing cohort table, keeping only
records from cohorts with a minimum number of individuals
requireMinCohortCount( cohort, minCohortCount, cohortId = NULL, updateSettings = FALSE, name = tableName(cohort) )requireMinCohortCount( cohort, minCohortCount, cohortId = NULL, updateSettings = FALSE, name = tableName(cohort) )
cohort |
A cohort table in a cdm reference. |
minCohortCount |
The minimum count of sbjects for a cohort to be included. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
updateSettings |
If TRUE, dropped cohorts will also be removed from all cohort table attributes (i.e., settings, attrition, counts, and codelist). If FALSE, these attributes will be retained but updated to reflect that the affected cohorts have been suppressed. |
name |
Name of the new cohort table created in the cdm object. |
Cohort table
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireMinCohortCount(5)library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireMinCohortCount(5)
requirePriorObservation() filters cohort records, keeping only records
where individuals satisfy the specified prior observation criteria.
requirePriorObservation( cohort, minPriorObservation, cohortId = NULL, indexDate = "cohort_start_date", atFirst = FALSE, name = tableName(cohort) )requirePriorObservation( cohort, minPriorObservation, cohortId = NULL, indexDate = "cohort_start_date", atFirst = FALSE, name = tableName(cohort) )
cohort |
A cohort table in a cdm reference. |
minPriorObservation |
A minimum number of continuous prior observation days in the database. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
indexDate |
Variable in cohort that contains the date to compute the demographics characteristics on which to restrict on. |
atFirst |
If FALSE the requirement will be applied to all records, if TRUE, it will only be required for the first entry of each subject. |
name |
Name of the new cohort table created in the cdm object. |
The cohort table with only records for individuals satisfying the prior observation requirement
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requirePriorObservation(indexDate = "cohort_start_date", minPriorObservation = 365)library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requirePriorObservation(indexDate = "cohort_start_date", minPriorObservation = 365)
requireSex() filters cohort records, keeping only records where individuals
satisfy the specified sex criteria.
requireSex( cohort, sex, cohortId = NULL, atFirst = FALSE, name = tableName(cohort) )requireSex( cohort, sex, cohortId = NULL, atFirst = FALSE, name = tableName(cohort) )
cohort |
A cohort table in a cdm reference. |
sex |
Can be "Both", "Male" or "Female". |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
atFirst |
If FALSE the requirement will be applied to all records, if TRUE, it will only be required for the first entry of each subject. |
name |
Name of the new cohort table created in the cdm object. |
The cohort table with only records for individuals satisfying the sex requirement
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireSex(sex = "Female")library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireSex(sex = "Female")
requireTableIntersect() filters a cohort table based on a requirement
that an individual is seen (or not seen) to have a record (or no records) in
a clinical table in some time window around an index date.
requireTableIntersect( cohort, tableName, window, intersections = c(1, Inf), cohortId = NULL, indexDate = "cohort_start_date", targetStartDate = startDateColumn(tableName), targetEndDate = endDateColumn(tableName), inObservation = TRUE, censorDate = NULL, atFirst = FALSE, name = tableName(cohort) )requireTableIntersect( cohort, tableName, window, intersections = c(1, Inf), cohortId = NULL, indexDate = "cohort_start_date", targetStartDate = startDateColumn(tableName), targetEndDate = endDateColumn(tableName), inObservation = TRUE, censorDate = NULL, atFirst = FALSE, name = tableName(cohort) )
cohort |
A cohort table in a cdm reference. |
tableName |
Name of the table to check for intersect. |
window |
A list of vectors specifying minimum and maximum days from
|
intersections |
A range indicating number of intersections for criteria to be fulfilled. If a single number is passed, the number of intersections must match this. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
indexDate |
Name of the column in the cohort that contains the date to compute the intersection. |
targetStartDate |
Start date of reference in cohort table. |
targetEndDate |
End date of reference in cohort table. If NULL, incidence of target event in the window will be considered as intersection, otherwise prevalence of that event will be used as intersection (overlap between cohort and event). |
inObservation |
If TRUE only records inside an observation period will be considered |
censorDate |
Whether to censor overlap events at a specific date or a column date of the cohort. |
atFirst |
If FALSE the requirement will be applied to all records, if TRUE, it will only be required for the first entry of each subject. |
name |
Name of the new cohort table created in the cdm object. |
Cohort table
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireTableIntersect(tableName = "drug_exposure", indexDate = "cohort_start_date", window = c(-Inf, 0))library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireTableIntersect(tableName = "drug_exposure", indexDate = "cohort_start_date", window = c(-Inf, 0))
sampleCohorts() samples an existing cohort table for a given number of
people. All records of these individuals are preserved.
sampleCohorts( cohort, n, independent = TRUE, cohortId = NULL, name = tableName(cohort) )sampleCohorts( cohort, n, independent = TRUE, cohortId = NULL, name = tableName(cohort) )
cohort |
A cohort table in a cdm reference. |
n |
Number of people to be sampled. |
independent |
If TRUE, cohorts will be sampled independently with each cohort randomly sampled for n. If FALSE, cohorts will be jointly sampled for n across all cohorts. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
name |
Name of the new cohort table created in the cdm object. |
Cohort table with the specified cohorts sampled.
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort2 |> sampleCohorts(cohortId = 1, n = 10)library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort2 |> sampleCohorts(cohortId = 1, n = 10)
stratifyCohorts() creates new cohorts, splitting an existing cohort based
on specified columns on which to stratify on.
stratifyCohorts( cohort, strata, cohortId = NULL, removeStrata = TRUE, name = tableName(cohort) )stratifyCohorts( cohort, strata, cohortId = NULL, removeStrata = TRUE, name = tableName(cohort) )
cohort |
A cohort table in a cdm reference. |
strata |
A strata list that point to columns in cohort table. |
cohortId |
Vector identifying which cohorts to include (cohort_definition_id or cohort_name). Cohorts not included will be removed from the cohort set. |
removeStrata |
Whether to remove strata columns from final cohort table. |
name |
Name of the new cohort table created in the cdm object. |
Cohort table stratified.
library(CohortConstructor) library(PatientProfiles) cdm <- mockCohortConstructor() cdm$my_cohort <- cdm$cohort1 |> addAge(ageGroup = list("child" = c(0, 17), "adult" = c(18, Inf))) |> addSex(name = "my_cohort") |> stratifyCohorts( strata = list("sex", c("sex", "age_group")), name = "my_cohort" ) cdm$my_cohort settings(cdm$my_cohort) attrition(cdm$my_cohort)library(CohortConstructor) library(PatientProfiles) cdm <- mockCohortConstructor() cdm$my_cohort <- cdm$cohort1 |> addAge(ageGroup = list("child" = c(0, 17), "adult" = c(18, Inf))) |> addSex(name = "my_cohort") |> stratifyCohorts( strata = list("sex", c("sex", "age_group")), name = "my_cohort" ) cdm$my_cohort settings(cdm$my_cohort) attrition(cdm$my_cohort)
subsetCohorts() filters an existing cohort table, keeping only the records
from cohorts that are specified.
subsetCohorts(cohort, cohortId, name = tableName(cohort), negate = FALSE)subsetCohorts(cohort, cohortId, name = tableName(cohort), negate = FALSE)
cohort |
A cohort table in a cdm reference. |
cohortId |
Vector identifying which cohorts to include (cohort_definition_id or cohort_name). Cohorts not included will be removed from the cohort set. |
name |
Name of the new cohort table created in the cdm object. |
negate |
If TRUE, the cohorts specified in cohortId will be excluded and the remaining cohorts kept. |
Cohort table with only cohorts in cohortId.
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> subsetCohorts(cohortId = 1)library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> subsetCohorts(cohortId = 1)
Split cohorts based on time-windows
timeWindowCohorts( cohort, window, cohortId = NULL, keepOriginalCohorts = TRUE, name = tableName(cohort) )timeWindowCohorts( cohort, window, cohortId = NULL, keepOriginalCohorts = TRUE, name = tableName(cohort) )
cohort |
A cohort table in a cdm reference. |
window |
A list specifying the time windows (in days) used to split the
cohort. Each element must be a numeric vector of length 2:
|
cohortId |
Vector identifying which cohorts to include (cohort_definition_id or cohort_name). Cohorts not included will be removed from the cohort set. |
keepOriginalCohorts |
If TRUE the original cohorts will be return together with the new ones. If FALSE only the new cohort will be returned. |
name |
Name of the new cohort table created in the cdm object. |
A cohort table
library(CohortConstructor) cdm <- mockCohortConstructor() # if "cohort1" contained pregnancy episodes, we can generate trimester-specific # cohorts with this function cdm$pregnancy_trimesters <- timeWindowCohorts( cohort = cdm$cohort1, window = list( "trimester_1" = c(0, 90), "trimester_2" = c(91,180), "trimester_3" = c(181, Inf) ), cohortId = NULL, keepOriginalCohorts = FALSE, name = "pregnancy_trimesters" )library(CohortConstructor) cdm <- mockCohortConstructor() # if "cohort1" contained pregnancy episodes, we can generate trimester-specific # cohorts with this function cdm$pregnancy_trimesters <- timeWindowCohorts( cohort = cdm$cohort1, window = list( "trimester_1" = c(0, 90), "trimester_2" = c(91,180), "trimester_3" = c(181, Inf) ), cohortId = NULL, keepOriginalCohorts = FALSE, name = "pregnancy_trimesters" )
trimDemographics() resets the cohort start and end date based on the
specified demographic criteria is satisfied.
trimDemographics( cohort, cohortId = NULL, ageRange = NULL, sex = NULL, minPriorObservation = NULL, minFutureObservation = NULL, name = tableName(cohort) )trimDemographics( cohort, cohortId = NULL, ageRange = NULL, sex = NULL, minPriorObservation = NULL, minFutureObservation = NULL, name = tableName(cohort) )
cohort |
A cohort table in a cdm reference. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
ageRange |
A list of vectors specifying minimum and maximum age. |
sex |
Can be "Both", "Male" or "Female". |
minPriorObservation |
A minimum number of continuous prior observation days in the database. |
minFutureObservation |
A minimum number of continuous future observation days in the database. |
name |
Name of the new cohort table created in the cdm object. |
The cohort table with only records for individuals satisfying the demographic requirements
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> trimDemographics(ageRange = list(c(10, 30)))library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> trimDemographics(ageRange = list(c(10, 30)))
trimDuration() resets the cohort start and end date, keeping only those
which include the specified amount of days
trimDuration(cohort, daysInCohort, cohortId = NULL, name = tableName(cohort))trimDuration(cohort, daysInCohort, cohortId = NULL, name = tableName(cohort))
cohort |
A cohort table in a cdm reference. |
daysInCohort |
Number of days cohort relative to current cohort start dates. Cohort entries will be trimmed to these dates. Note, cohort entry and exit on the same day counts as one day in the cohort.Set lower bound to 1 if keeping cohort start to the same as current cohort start. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
name |
Name of the new cohort table created in the cdm object. |
The cohort table with any cohort entries that last less or more than the required duration dropped
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireDuration(daysInCohort = c(2, Inf))library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 |> requireDuration(daysInCohort = c(2, Inf))
trimToDateRange() resets the cohort start and end date based on the
specified date range.
trimToDateRange( cohort, dateRange, cohortId = NULL, startDate = "cohort_start_date", endDate = "cohort_end_date", name = tableName(cohort), .softValidation = FALSE )trimToDateRange( cohort, dateRange, cohortId = NULL, startDate = "cohort_start_date", endDate = "cohort_end_date", name = tableName(cohort), .softValidation = FALSE )
cohort |
A cohort table in a cdm reference. |
dateRange |
A window of time during which the start and end date must have been observed. |
cohortId |
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged. |
startDate |
Variable with earliest date. |
endDate |
Variable with latest date. |
name |
Name of the new cohort table created in the cdm object. |
.softValidation |
Whether to perform a soft validation of consistency. If set to FALSE four additional checks will be performed: 1) a check that cohort end date is not before cohort start date, 2) a check that there are no missing values in required columns, 3) a check that cohort duration is all within observation period, and 4) that there are no overlapping cohort entries |
The cohort table with record timings updated to only be within the date range. Any records with all time outside of the range will have been dropped.
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort2 <- cdm$cohort1 |> trimToDateRange( startDate = "cohort_start_date", endDate = "cohort_end_date", dateRange = as.Date(c("2015-01-01", "2015-12-31")), name = "cohort2" ) cdm$cohort1 <- cdm$cohort1 |> trimToDateRange( dateRange = as.Date(c(NA, "2015-12-31")) )library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort2 <- cdm$cohort1 |> trimToDateRange( startDate = "cohort_start_date", endDate = "cohort_end_date", dateRange = as.Date(c("2015-01-01", "2015-12-31")), name = "cohort2" ) cdm$cohort1 <- cdm$cohort1 |> trimToDateRange( dateRange = as.Date(c(NA, "2015-12-31")) )
unionCohorts() combines different cohort entries, with those records
that overlap combined and kept. Cohort entries are when an individual was in
either of the cohorts.
unionCohorts( cohort, cohortId = NULL, gap = 0, cohortName = NULL, keepOriginalCohorts = FALSE, name = tableName(cohort) )unionCohorts( cohort, cohortId = NULL, gap = 0, cohortName = NULL, keepOriginalCohorts = FALSE, name = tableName(cohort) )
cohort |
A cohort table in a cdm reference. |
cohortId |
Vector identifying which cohorts to include (cohort_definition_id or cohort_name). Cohorts not included will be removed from the cohort set. |
gap |
Number of days between two subsequent cohort entries to be merged in a single cohort record. |
cohortName |
Name of the returned cohort. If NULL, the cohort name will be created by collapsing the individual cohort names, separated by "_". |
keepOriginalCohorts |
If TRUE the original cohorts will be return together with the new ones. If FALSE only the new cohort will be returned. |
name |
Name of the new cohort table created in the cdm object. |
A cohort table.
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort2 <- cdm$cohort2 |> unionCohorts() settings(cdm$cohort2)library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort2 <- cdm$cohort2 |> unionCohorts() settings(cdm$cohort2)
yearCohorts() splits a cohort into multiple cohorts, one for each year.
yearCohorts( cohort, years, cohortId = NULL, name = tableName(cohort), .softValidation = FALSE )yearCohorts( cohort, years, cohortId = NULL, name = tableName(cohort), .softValidation = FALSE )
cohort |
A cohort table in a cdm reference. |
years |
Numeric vector of years to use to restrict observation to. |
cohortId |
Vector identifying which cohorts to include (cohort_definition_id or cohort_name). Cohorts not included will be removed from the cohort set. |
name |
Name of the new cohort table created in the cdm object. |
.softValidation |
Whether to perform a soft validation of consistency. If set to FALSE four additional checks will be performed: 1) a check that cohort end date is not before cohort start date, 2) a check that there are no missing values in required columns, 3) a check that cohort duration is all within observation period, and 4) that there are no overlapping cohort entries |
A cohort table.
library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 <- cdm$cohort1 |> yearCohorts(years = 2000:2002) settings(cdm$cohort1)library(CohortConstructor) cdm <- mockCohortConstructor() cdm$cohort1 <- cdm$cohort1 |> yearCohorts(years = 2000:2002) settings(cdm$cohort1)