epikit (version 0.2.0)

age_categories: Create an age group variable

Description

Create an age group variable

Usage

age_categories(
  x,
  breakers = NULL,
  lower = 0,
  upper = NULL,
  by = 10,
  separator = "-",
  floor = FALSE,
  below.char = "<", ceiling="FALSE," above.char="+" )<="" p="">
group_age_categories(
  dat,
  years = NULL,
  months = NULL,
  weeks = NULL,
  days = NULL,
  one_column = TRUE,
  drop_empty_overlaps = TRUE
)

Value

a factor representing age ranges, open at the upper end of the range.

a data frame

Arguments

x

Your age variable

breakers

A string. Age category breaks you can define within c(). Alternatively use "lower", "upper" and "by" to set these breaks based on a sequence.

lower

A number. The lowest age value you want to consider (default is 0)

upper

A number. The highest age value you want to consider

by

A number. The number of years you want between groups

separator

A character that you want to have between ages in group names. The default is "-" producing e.g. 0-10.

floor

A TRUE/FALSE variable. Specify whether you would like the lowest value in your breakers, or alternatively the lower value specified, to be formatted with below.char instead of as a range. This would produce the lowest group of "<1" rather than "0-0". The default is TRUE.

below.char

Only considered when floor == TRUE. A character that you want to have before your lowest age group. The default is "<" producing e.g. <1

ceiling

A TRUE/FALSE variable. Specify whether you would like the highest value in your breakers, or alternatively the upper value specified, to be the endpoint. This would produce the highest group of "70-80" rather than "80+". The default is FALSE (to produce a group of 80+).

above.char

Only considered when ceiling == FALSE. A character that you want to have after your highest age group. The default is "+" producing e.g. 80+

dat

a data frame with at least one column defining an age category

years, months, weeks, days

the bare name of the column defining years, months, weeks, or days (or NULL if the column doesn't exist)

one_column

if TRUE (default), the categories will be joined into a single column called "age_category" that appends the type of age category used. If FALSE, there will be one column with the grouped age categories called "age_category" and a second column indicating age unit called "age_unit".

drop_empty_overlaps

if TRUE, unused levels are dropped if they have been replaced by a more fine-grained definition and are empty. Practically, this means that the first level for years, months, and weeks are in consideration for being removed via forcats::fct_drop()

Examples

if (interactive() && require("dplyr")) {
withAutoprint({
set.seed(50)
years <- sample(0:90, 100, replace = TRUE)
months <- ifelse(years < 2, sample(0:23, 100, replace = TRUE), NA)
days <- ifelse(years < 2 & months < 2, sample(0:30, 100, replace = TRUE), NA)
dat <- data.frame(age_years = years, age_months = months, age_days = days)
ages <- dat %>%
  select(starts_with("age")) %>%
  mutate(age_years = age_categories(age_years, breakers = c(0, 5, 10, 15, 20))) %>%
  mutate(age_months = age_categories(age_months, breakers = c(0, 5, 10, 15, 20))) %>%
  mutate(age_days = age_categories(age_days, breakers = c(0, 5, 15)))

ages %>%
  group_age_categories(years = age_years, months = age_months, days = age_days) %>%
  pull(age_category) %>%
  table()
})
}