From 5b1d7d90b89aff1259c62068f9614aab3bff64eb Mon Sep 17 00:00:00 2001 From: edward-burn <9583964+edward-burn@users.noreply.github.com> Date: Fri, 1 Nov 2024 22:05:05 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20OHDSI/Co?= =?UTF-8?q?hortConstructor@9c1d98fef9b3982032ee505030309744b4c88916=20?= =?UTF-8?q?=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- articles/a01_building_base_cohorts.html | 6 ++-- articles/a02_cohort_table_requirements.html | 24 +++++++-------- articles/a03_require_demographics.html | 20 ++++++------ articles/a04_require_intersections.html | 22 ++++++------- articles/a06_concatanate_cohorts.html | 24 +++++++-------- articles/a07_filter_cohorts.html | 34 ++++++++++----------- articles/a08_split_cohorts.html | 6 ++-- articles/a09_combine_cohorts.html | 12 ++++---- index.html | 18 +++++------ pkgdown.yml | 2 +- reference/collapseCohorts.html | 2 +- reference/conceptCohort.html | 2 +- reference/demographicsCohort.html | 2 +- reference/entryAtFirstDate.html | 8 ++--- reference/entryAtLastDate.html | 10 +++--- reference/exitAtDeath.html | 24 +++++++-------- reference/exitAtFirstDate.html | 12 ++++---- reference/exitAtLastDate.html | 8 ++--- reference/exitAtObservationEnd.html | 12 ++++---- reference/intersectCohorts.html | 4 +-- reference/matchCohorts.html | 24 +++++++-------- reference/measurementCohort.html | 2 +- reference/padCohortEnd.html | 14 ++++----- reference/padCohortStart.html | 4 +-- reference/reexports.html | 2 +- reference/requireAge.html | 4 +-- reference/requireCohortIntersect.html | 24 +++++++-------- reference/requireConceptIntersect.html | 2 +- reference/requireDeathFlag.html | 4 +-- reference/requireDemographics.html | 4 +-- reference/requireFutureObservation.html | 14 ++++----- reference/requireInDateRange.html | 4 +-- reference/requireIsEntry.html | 2 +- reference/requireIsFirstEntry.html | 2 +- reference/requireIsLastEntry.html | 2 +- reference/requireMinCohortCount.html | 4 +-- reference/requirePriorObservation.html | 4 +-- reference/requireSex.html | 4 +-- reference/requireTableIntersect.html | 4 +-- reference/sampleCohorts.html | 20 ++++++------ reference/stratifyCohorts.html | 8 ++--- reference/subsetCohorts.html | 4 +-- reference/trimDemographics.html | 4 +-- reference/trimToDateRange.html | 4 +-- reference/unionCohorts.html | 4 +-- reference/yearCohorts.html | 4 +-- search.json | 2 +- 47 files changed, 213 insertions(+), 213 deletions(-) diff --git a/articles/a01_building_base_cohorts.html b/articles/a01_building_base_cohorts.html index c711fb1..4f2c504 100644 --- a/articles/a01_building_base_cohorts.html +++ b/articles/a01_building_base_cohorts.html @@ -134,7 +134,7 @@
At this point we have just created our base cohort without having applied any restrictions.
-summary_attrition <- summariseCohortAttrition(cdm$acetaminophen)
-plotCohortAttrition(summary_attrition)
summary_attrition <- summariseCohortAttrition(cdm$acetaminophen)
+plotCohortAttrition(summary_attrition)
cdm$acetaminophen <- cdm$acetaminophen |>
requireIsFirstEntry()
-summary_attrition <- summariseCohortAttrition(cdm$acetaminophen)
-plotCohortAttrition(summary_attrition)
While the number of individuals remains unchanged, records after an individual’s first have been excluded.
@@ -156,8 +156,8 @@cdm$acetaminophen <- cdm$acetaminophen |>
requireInDateRange(dateRange = as.Date(c("2010-01-01", "2015-01-01")))
-summary_attrition <- summariseCohortAttrition(cdm$acetaminophen)
-plotCohortAttrition(summary_attrition)
+summary_attrition <- summariseCohortAttrition(cdm$acetaminophen)
+plotCohortAttrition(summary_attrition)
@@ -180,20 +180,20 @@
-summary_attrition_1 <- summariseCohortAttrition(cdm$acetaminophen_1)
-summary_attrition_2 <- summariseCohortAttrition(cdm$acetaminophen_2)
summary_attrition_1 <- summariseCohortAttrition(cdm$acetaminophen_1)
+summary_attrition_2 <- summariseCohortAttrition(cdm$acetaminophen_2)
Here we see attrition if we apply our entry requirement before our date requirement. In this case we have a cohort of people with their first ever record of acetaminophen which occurs in our study period.
-plotCohortAttrition(summary_attrition_1)
plotCohortAttrition(summary_attrition_1)
And here we see attrition if we apply our date requirement before our entry requirement. In this case we have a cohort of people with their first record of acetaminophen in the study period, although this will not necessarily be their first record ever.
-plotCohortAttrition(summary_attrition_2)
plotCohortAttrition(summary_attrition_2)
@@ -227,7 +227,7 @@ cdm$medications <- cdm$medications |>
requireMinCohortCount(minCohortCount = 500)
-cohortCount(cdm$medications) |>
+cohortCount(cdm$medications) |>
filter(number_subjects > 0) |>
ggplot() +
geom_histogram(aes(number_subjects),
diff --git a/articles/a03_require_demographics.html b/articles/a03_require_demographics.html
index 5b2fc9f..32e198a 100644
--- a/articles/a03_require_demographics.html
+++ b/articles/a03_require_demographics.html
@@ -112,8 +112,8 @@
conceptSet = fracture_codes,
name = "fracture")
-summary_attrition <- summariseCohortAttrition(cdm$fracture)
-plotCohortAttrition(summary_attrition)
+summary_attrition <- summariseCohortAttrition(cdm$fracture)
+plotCohortAttrition(summary_attrition)
Note that by default individuals are filtered based on the age they were when they entered the cohort.
@@ -140,8 +140,8 @@As well as specifying a minimum amount of prior observation, we can require some mimimum amount of follow-up by using @@ -179,8 +179,8 @@
The flow chart above illustrates the changes to the cohort of users of acetaminophen when restricted to only include individuals who have at @@ -157,8 +157,8 @@
The flow chart above illustrates the changes to cohort 1 when restricted to only include individuals who have had events of GI @@ -197,8 +197,8 @@
cdm$medications |>
filter(subject_id == 1)
#> # Source: SQL [4 x 4]
-#> # Database: DuckDB v1.1.1 [unknown@Linux 6.5.0-1025-azure:R 4.4.1//tmp/RtmpX98f7c/file1d7543588adc.duckdb]
+#> # Database: DuckDB v1.1.2 [unknown@Linux 6.5.0-1025-azure:R 4.4.2//tmp/RtmpTFmCk3/file294b67620621.duckdb]
#> cohort_definition_id subject_id cohort_start_date cohort_end_date
#> <int> <int> <date> <date>
-#> 1 1 1 1976-10-20 1976-11-03
+#> 1 1 1 1980-03-15 1980-03-29
#> 2 1 1 1971-01-04 1971-01-18
#> 3 1 1 1982-09-11 1982-10-02
-#> 4 1 1 1980-03-15 1980-03-29
+#> 4 1 1 1976-10-20 1976-11-03
cdm$medications_collapsed |>
filter(subject_id == 1)
#> # Source: SQL [3 x 4]
-#> # Database: DuckDB v1.1.1 [unknown@Linux 6.5.0-1025-azure:R 4.4.1//tmp/RtmpX98f7c/file1d7543588adc.duckdb]
+#> # Database: DuckDB v1.1.2 [unknown@Linux 6.5.0-1025-azure:R 4.4.2//tmp/RtmpTFmCk3/file294b67620621.duckdb]
#> cohort_definition_id subject_id cohort_start_date cohort_end_date
#> <int> <int> <date> <date>
-#> 1 1 1 1976-10-20 1976-11-03
-#> 2 1 1 1980-03-15 1982-10-02
-#> 3 1 1 1971-01-04 1971-01-18
+#> 1 1 1 1971-01-04 1971-01-18
+#> 2 1 1 1976-10-20 1976-11-03
+#> 3 1 1 1980-03-15 1982-10-02
Subject 1 initially had 4 records between 1971 and 1982. After specifying that records within three years of each other are to be merged, the number of records decreases to three. The record from @@ -153,15 +153,15 @@ are merged to create a new record from 1980-03-15 to 1982-10-02.
Now let’s look at how the cohorts have been changed.
-summary_attrition <- summariseCohortAttrition(cdm$medications_collapsed)
-plotCohortAttrition(summary_attrition, cohortId = 1)
summary_attrition <- summariseCohortAttrition(cdm$medications_collapsed)
+plotCohortAttrition(summary_attrition, cohortId = 1)
The flow chart above illustrates the changes to cohort 1 (users of acetaminophen) when entries within 3 years of each other are merged. We see that collapsing the cohort has led to 1,390 fewer records.
-summary_attrition <- summariseCohortAttrition(cdm$medications_collapsed)
-plotCohortAttrition(summary_attrition, cohortId = 2)
summary_attrition <- summariseCohortAttrition(cdm$medications_collapsed)
+plotCohortAttrition(summary_attrition, cohortId = 2)
The flow chart above illustrates the changes to cohort 2 (users of diclofenac) when entries within 3 years of each other are merged. Since diff --git a/articles/a07_filter_cohorts.html b/articles/a07_filter_cohorts.html index 865a8fe..04a18d2 100644 --- a/articles/a07_filter_cohorts.html +++ b/articles/a07_filter_cohorts.html @@ -105,7 +105,7 @@ conceptSet = list("diclofenac" = 1124300, "acetaminophen" = 1127433), name = "medications") -cohortCount(cdm$medications) +cohortCount(cdm$medications) #> # A tibble: 2 × 3 #> cohort_definition_id number_records number_subjects #> <int> <int> <int> @@ -117,26 +117,26 @@
cdm$medications |> sampleCohorts(cohortId = NULL, n = 100)
#> # Source: table<main.my_study_medications> [?? x 4]
-#> # Database: DuckDB v1.1.1 [unknown@Linux 6.5.0-1025-azure:R 4.4.1//tmp/RtmpEAPUaU/file1db85e0d1500.duckdb]
+#> # Database: DuckDB v1.1.2 [unknown@Linux 6.5.0-1025-azure:R 4.4.2//tmp/RtmpJmrUxd/file298d1509de16.duckdb]
#> cohort_definition_id subject_id cohort_start_date cohort_end_date
#> <int> <int> <date> <date>
-#> 1 1 393 1962-08-13 1962-08-20
-#> 2 1 2052 2015-03-03 2015-03-10
-#> 3 1 2069 1963-06-22 1963-07-06
-#> 4 1 3835 1984-10-06 1984-10-27
-#> 5 2 764 2003-12-24 2003-12-24
-#> 6 2 4571 1995-04-02 1995-04-02
-#> 7 1 2295 1994-09-16 1994-09-30
-#> 8 1 161 2013-07-31 2013-08-28
-#> 9 1 1355 1965-11-28 1965-12-12
-#> 10 1 1194 2003-06-30 2003-07-14
+#> 1 1 1024 1971-03-15 1971-03-29
+#> 2 1 1024 1995-02-21 1995-03-07
+#> 3 1 3761 1958-10-10 1958-10-24
+#> 4 1 951 1967-12-30 1968-01-20
+#> 5 1 951 1990-12-09 1990-12-23
+#> 6 1 675 1950-08-06 1950-08-20
+#> 7 1 1128 1975-02-21 1975-02-28
+#> 8 1 1558 2006-04-06 2006-04-13
+#> 9 1 3010 2000-01-07 2000-01-14
+#> 10 2 390 2016-05-15 2016-05-15
#> # ℹ more rows
-cohortCount(cdm$medications)
+cohortCount(cdm$medications)
#> # A tibble: 2 × 3
#> cohort_definition_id number_records number_subjects
#> <int> <int> <int>
-#> 1 1 350 100
+#> 1 1 374 100
#> 2 2 100 100
When cohortId = NULL all cohorts in the table are used. Note that this function does not reduced the number of records in each cohort, @@ -146,7 +146,7 @@
cdm$medications <- cdm$medications |> sampleCohorts(cohortId = 2, n = 100)
-cohortCount(cdm$medications)
+cohortCount(cdm$medications)
#> # A tibble: 2 × 3
#> cohort_definition_id number_records number_subjects
#> <int> <int> <int>
@@ -160,7 +160,7 @@
subsetCohorts
.
cdm$medications <- cdm$medications |> subsetCohorts(cohortId = 2)
-cohortCount(cdm$medications)
+cohortCount(cdm$medications)
#> # A tibble: 1 × 3
#> cohort_definition_id number_records number_subjects
#> <int> <int> <int>
@@ -172,7 +172,7 @@
cdm$medications <- cdm$medications |> sampleCohorts(cohortId = 2, n = 100)
-cohortCount(cdm$medications)
+cohortCount(cdm$medications)
#> # A tibble: 1 × 3
#> cohort_definition_id number_records number_subjects
#> <int> <int> <int>
diff --git a/articles/a08_split_cohorts.html b/articles/a08_split_cohorts.html
index 6efd397..ae29e5b 100644
--- a/articles/a08_split_cohorts.html
+++ b/articles/a08_split_cohorts.html
@@ -101,7 +101,7 @@
conceptSet = list("diclofenac" = 1124300,
"acetaminophen" = 1127433),
name = "medications")
-cohortCount(cdm$medications)
+cohortCount(cdm$medications)
#> # A tibble: 2 × 3
#> cohort_definition_id number_records number_subjects
#> <int> <int> <int>
@@ -116,7 +116,7 @@
addSex(name = "stratified") |>
stratifyCohorts(strata = list("sex", "age_group", c("sex", "age_group")), name = "stratified")
-settings(cdm$stratified)
+settings(cdm$stratified)
#> # A tibble: 22 × 10
#> cohort_definition_id cohort_name target_cohort_id target_cohort_name
#> <int> <chr> <int> <chr>
@@ -143,7 +143,7 @@
cdm$years <- cdm$medications |>
yearCohorts(years = 2005:2010, name = "years")
-settings(cdm$years)
+settings(cdm$years)
#> # A tibble: 12 × 7
#> cohort_definition_id cohort_name target_cohort_definitio…¹ cdm_version
#> <int> <chr> <int> <chr>
diff --git a/articles/a09_combine_cohorts.html b/articles/a09_combine_cohorts.html
index 8ad4342..676105a 100644
--- a/articles/a09_combine_cohorts.html
+++ b/articles/a09_combine_cohorts.html
@@ -105,7 +105,7 @@
conceptSet = list("diclofenac" = 1124300,
"acetaminophen" = 1127433),
name = "medications")
-cohortCount(cdm$medications)
+cohortCount(cdm$medications)
#> # A tibble: 2 × 3
#> cohort_definition_id number_records number_subjects
#> <int> <int> <int>
@@ -119,7 +119,7 @@
name = "medintersect"
)
-cohortCount(cdm$medintersect)
+cohortCount(cdm$medintersect)
#> # A tibble: 1 × 3
#> cohort_definition_id number_records number_subjects
#> <int> <int> <int>
@@ -135,7 +135,7 @@
name = "medintersect"
)
-cohortCount(cdm$medintersect)
+cohortCount(cdm$medintersect)
#> # A tibble: 1 × 3
#> cohort_definition_id number_records number_subjects
#> <int> <int> <int>
@@ -150,7 +150,7 @@
name = "medunion"
)
-cohortCount(cdm$medunion)
+cohortCount(cdm$medunion)
#> # A tibble: 1 × 3
#> cohort_definition_id number_records number_subjects
#> <int> <int> <int>
@@ -166,7 +166,7 @@
keepOriginalCohorts = TRUE
)
-cohortCount(cdm$medunion)
+cohortCount(cdm$medunion)
#> # A tibble: 3 × 3
#> cohort_definition_id number_records number_subjects
#> <int> <int> <int>
@@ -183,7 +183,7 @@
keepOriginalCohorts = TRUE
)
-cohortCount(cdm$medunion)
+cohortCount(cdm$medunion)
#> # A tibble: 3 × 3
#> cohort_definition_id number_records number_subjects
#> <int> <int> <int>
diff --git a/index.html b/index.html
index 01a2baf..b2c9128 100644
--- a/index.html
+++ b/index.html
@@ -152,7 +152,7 @@ Generating concept-based frac
#>
#> Time taken: 0 minutes and 0 seconds
-fx_codes <- newCodelist(list("hip_fracture" = hip_fx_codes$concept_id,
+fx_codes <- newCodelist(list("hip_fracture" = hip_fx_codes$concept_id,
"forearm_fracture"= forearm_fx_codes$concept_id))
fx_codes
#>
@@ -172,7 +172,7 @@ Generating concept-based frac
padCohortEnd(days = 180)
We can see that our starting cohorts, before we add any additional restrictions, have the following associated settings, counts, and attrition.
-settings(cdm$fractures) |> glimpse()
+settings(cdm$fractures) |> glimpse()
#> Rows: 2
#> Columns: 4
#> $ cohort_definition_id <int> 1, 2
@@ -185,7 +185,7 @@ Generating concept-based frac
#> $ cohort_definition_id <int> 1, 2
#> $ number_records <int> 569, 138
#> $ number_subjects <int> 510, 132
-attrition(cdm$fractures) |> glimpse()
+attrition(cdm$fractures) |> glimpse()
#> Rows: 4
#> Columns: 7
#> $ cohort_definition_id <int> 1, 1, 2, 2
@@ -206,14 +206,14 @@ Create an overall fracture cohort keepOriginalCohorts = TRUE,
name ="fractures")
-settings(cdm$fractures)
+settings(cdm$fractures)
#> # A tibble: 3 × 5
#> cohort_definition_id cohort_name cdm_version vocabulary_version gap
#> <int> <chr> <chr> <chr> <dbl>
#> 1 1 forearm_fracture 5.3 v5.0 18-JAN-19 NA
#> 2 2 hip_fracture 5.3 v5.0 18-JAN-19 NA
#> 3 3 any_fracture <NA> <NA> 0
-cohortCount(cdm$fractures)
+cohortCount(cdm$fractures)
#> # A tibble: 3 × 3
#> cohort_definition_id number_records number_subjects
#> <int> <int> <int>
@@ -236,7 +236,7 @@ Require in date range#> $ cohort_definition_id <int> 1, 2, 3
#> $ number_records <int> 152, 62, 214
#> $ number_subjects <int> 143, 60, 196
-attrition(cdm$fractures) |>
+attrition(cdm$fractures) |>
filter(reason == "cohort_start_date between 2000-01-01 & 2020-01-01") |>
glimpse()
#> Rows: 0
@@ -259,7 +259,7 @@ Applying demographic requirements sex = "Female")
Again we can see how many individuals we’ve lost after applying these criteria.
-attrition(cdm$fractures) |>
+attrition(cdm$fractures) |>
filter(reason == "Age requirement: 40 to 65") |>
glimpse()
#> Rows: 3
@@ -272,7 +272,7 @@ Applying demographic requirements#> $ excluded_records <int> 88, 40, 128
#> $ excluded_subjects <int> 81, 38, 113
-attrition(cdm$fractures) |>
+attrition(cdm$fractures) |>
filter(reason == "Sex requirement: Female") |>
glimpse()
#> Rows: 3
@@ -299,7 +299,7 @@ Require presence in another cohort intersections = 0,
window = c(-Inf, 0))
-attrition(cdm$fractures) |>
+attrition(cdm$fractures) |>
filter(reason == "Not in cohort gibleed between -Inf & 0 days relative to cohort_start_date") |>
glimpse()
#> Rows: 3
diff --git a/pkgdown.yml b/pkgdown.yml
index fc66bbe..b533e49 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -14,7 +14,7 @@ articles:
a09_combine_cohorts: a09_combine_cohorts.html
a10_match_cohorts: a10_match_cohorts.html
a11_benchmark: a11_benchmark.html
-last_built: 2024-10-29T18:33Z
+last_built: 2024-11-01T21:58Z
urls:
reference: https://ohdsi.github.io/CohortConstructor/reference
article: https://ohdsi.github.io/CohortConstructor/articles
diff --git a/reference/collapseCohorts.html b/reference/collapseCohorts.html
index e56ea58..c5f0a90 100644
--- a/reference/collapseCohorts.html
+++ b/reference/collapseCohorts.html
@@ -61,7 +61,7 @@
Usage
- collapseCohorts(cohort, cohortId = NULL, gap = 0, name = tableName(cohort))
+ collapseCohorts(cohort, cohortId = NULL, gap = 0, name = tableName(cohort))
diff --git a/reference/conceptCohort.html b/reference/conceptCohort.html
index 9028653..07b3b25 100644
--- a/reference/conceptCohort.html
+++ b/reference/conceptCohort.html
@@ -192,7 +192,7 @@ Examples#> ✖ Domain NA (1 concept) excluded because it is not supported.
#> ℹ No cohort entries found, returning empty cohort table.
-cohort |> attrition()
+cohort |> attrition()
#> # A tibble: 1 × 7
#> cohort_definition_id number_records number_subjects reason_id reason
#> <int> <int> <int> <int> <chr>
diff --git a/reference/demographicsCohort.html b/reference/demographicsCohort.html
index 27a6245..df20755 100644
--- a/reference/demographicsCohort.html
+++ b/reference/demographicsCohort.html
@@ -124,7 +124,7 @@ Examples#> Trim age
#> ✔ Cohort trimmed
-attrition(cohort)
+attrition(cohort)
#> # A tibble: 3 × 7
#> cohort_definition_id number_records number_subjects reason_id reason
#> <int> <int> <int> <int> <chr>
diff --git a/reference/entryAtFirstDate.html b/reference/entryAtFirstDate.html
index 0ee5adb..4503aae 100644
--- a/reference/entryAtFirstDate.html
+++ b/reference/entryAtFirstDate.html
@@ -66,7 +66,7 @@ Usage
dateColumns,
cohortId = NULL,
returnReason = TRUE,
- name = tableName(cohort)
+ name = tableName(cohort)
)
@@ -160,13 +160,13 @@ Examples#> • `valid_end_date` is character but expected date
cdm$cohort |> entryAtLastDate(dateColumns = c("date_1", "date_2"))
#> # Source: table<main.cohort> [4 x 11]
-#> # Database: DuckDB v1.1.1 [unknown@Linux 6.5.0-1025-azure:R 4.4.1/:memory:]
+#> # Database: DuckDB v1.1.2 [unknown@Linux 6.5.0-1025-azure:R 4.4.2/:memory:]
#> cohort_definition_id subject_id cohort_start_date cohort_end_date
#> <int> <int> <date> <date>
-#> 1 1 2 2001-01-01 2001-01-12
+#> 1 1 1 2001-08-01 2001-09-01
#> 2 1 3 2015-02-14 2015-02-15
#> 3 1 4 2002-12-09 2002-12-09
-#> 4 1 1 2001-08-01 2001-09-01
+#> 4 1 2 2001-01-01 2001-01-12
#> # ℹ 7 more variables: cohort_definition_name <chr>,
#> # cohort_definition_description <chr>, definition_type_concept_id <int>,
#> # cohort_definition_syntax <chr>, subject_concept_id <int>,
diff --git a/reference/entryAtLastDate.html b/reference/entryAtLastDate.html
index 7c6565b..c0eac6a 100644
--- a/reference/entryAtLastDate.html
+++ b/reference/entryAtLastDate.html
@@ -66,7 +66,7 @@ Usage
dateColumns,
cohortId = NULL,
returnReason = TRUE,
- name = tableName(cohort)
+ name = tableName(cohort)
)
padCohortEnd(cohort, days, cohortId = NULL, name = tableName(cohort))
padCohortEnd(cohort, days, cohortId = NULL, name = tableName(cohort))
padCohortStart(cohort, days, cohortId = NULL, name = tableName(cohort))
padCohortStart(cohort, days, cohortId = NULL, name = tableName(cohort))
These objects are imported from other packages. Follow the links below to see their documentation.
attrition
, bind
, cohortCodelist
, cohortCount
, settings
, tableName
attrition
, bind
, cohortCodelist
, cohortCount
, settings
, tableName
requireIsEntry(cohort, entryRange, cohortId = NULL, name = tableName(cohort))
requireIsEntry(cohort, entryRange, cohortId = NULL, name = tableName(cohort))
requireIsFirstEntry(cohort, cohortId = NULL, name = tableName(cohort))
requireIsFirstEntry(cohort, cohortId = NULL, name = tableName(cohort))
requireIsLastEntry(cohort, cohortId = NULL, name = tableName(cohort))
requireIsLastEntry(cohort, cohortId = NULL, name = tableName(cohort))
requireSex(cohort, sex, cohortId = NULL, name = tableName(cohort))
requireSex(cohort, sex, cohortId = NULL, name = tableName(cohort))
sampleCohorts(cohort, n, cohortId = NULL, name = tableName(cohort))
sampleCohorts(cohort, n, cohortId = NULL, name = tableName(cohort))
subsetCohorts(cohort, cohortId, name = tableName(cohort))
subsetCohorts(cohort, cohortId, name = tableName(cohort))
yearCohorts(cohort, years, cohortId = NULL, name = tableName(cohort))
yearCohorts(cohort, years, cohortId = NULL, name = tableName(cohort))