age_groups | R Documentation |
Split ages into age groups defined by the split
argument. This allows for easier demographic (antimicrobial resistance) analysis.
age_groups(x, split_at = c(12, 25, 55, 75), na.rm = FALSE)
x |
age, e.g. calculated with |
split_at |
values to split |
na.rm |
a logical to indicate whether missing values should be removed |
To split ages, the input for the split_at
argument can be:
A numeric vector. A value of e.g. c(10, 20)
will split x
on 0-9, 10-19 and 20+. A value of only 50
will split x
on 0-49 and 50+.
The default is to split on young children (0-11), youth (12-24), young adults (25-54), middle-aged adults (55-74) and elderly (75+).
A character:
"children"
or "kids"
, equivalent of: c(0, 1, 2, 4, 6, 13, 18)
. This will split on 0, 1, 2-3, 4-5, 6-12, 13-17 and 18+.
"elderly"
or "seniors"
, equivalent of: c(65, 75, 85)
. This will split on 0-64, 65-74, 75-84, 85+.
"fives"
, equivalent of: 1:20 * 5
. This will split on 0-4, 5-9, ..., 95-99, 100+.
"tens"
, equivalent of: 1:10 * 10
. This will split on 0-9, 10-19, ..., 90-99, 100+.
Ordered factor
To determine ages, based on one or more reference dates, use the age()
function.
ages <- c(3, 8, 16, 54, 31, 76, 101, 43, 21)
# split into 0-49 and 50+
age_groups(ages, 50)
# split into 0-19, 20-49 and 50+
age_groups(ages, c(20, 50))
# split into groups of ten years
age_groups(ages, 1:10 * 10)
age_groups(ages, split_at = "tens")
# split into groups of five years
age_groups(ages, 1:20 * 5)
age_groups(ages, split_at = "fives")
# split specifically for children
age_groups(ages, c(1, 2, 4, 6, 13, 18))
age_groups(ages, "children")
# resistance of ciprofloxacin per age group
if (require("dplyr") && require("ggplot2")) {
example_isolates %>%
filter_first_isolate() %>%
filter(mo == as.mo("Escherichia coli")) %>%
group_by(age_group = age_groups(age)) %>%
select(age_group, CIP) %>%
ggplot_sir(
x = "age_group",
minimum = 0,
x.title = "Age Group",
title = "Ciprofloxacin resistance per age group"
)
}
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