Split Ages into Age Groups

Split ages into age groups defined by the split argument. This allows for easier demographic (antimicrobial resistance) analysis. The function returns an ordered factor.

Usage

age_groups(x, split_at = c(0, 12, 25, 55, 75), names = NULL,
  na.rm = FALSE)

Arguments

x:

Age, e.g. calculated with age().
split_at:

Values to split x at - the default is age groups 0-11, 12-24, 25-54, 55-74 and 75+. See Details.
names:

Optional names to be given to the various age groups.
na.rm:

A logical to indicate whether missing values should be removed.

Value

Ordered factor

Details

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+.

Examples

ages <- c(3, 8, 16, 54, 31, 76, 101, 43, 21)

# split into 0-49 and 50+
age_groups(ages, 50)
#> [1] 0-49 0-49 0-49 50+  0-49 50+  50+  0-49 0-49
#> Levels: 0-49 < 50+

# split into 0-19, 20-49 and 50+
age_groups(ages, c(20, 50))
#> [1] 0-19  0-19  0-19  50+   20-49 50+   50+   20-49 20-49
#> Levels: 0-19 < 20-49 < 50+
age_groups(ages, c(20, 50), names = c("Under 20 years", "20 to 50 years", "Over 50 years"))
#> [1] Under 20 years Under 20 years Under 20 years Over 50 years  20 to 50 years
#> [6] Over 50 years  Over 50 years  20 to 50 years 20 to 50 years
#> Levels: Under 20 years < 20 to 50 years < Over 50 years

# split into groups of ten years
age_groups(ages, 1:10 * 10)
#> [1] 0-9   0-9   10-19 50-59 30-39 70-79 100+  40-49 20-29
#> 11 Levels: 0-9 < 10-19 < 20-29 < 30-39 < 40-49 < 50-59 < 60-69 < ... < 100+
age_groups(ages, split_at = "tens")
#> [1] 0-9   0-9   10-19 50-59 30-39 70-79 100+  40-49 20-29
#> 11 Levels: 0-9 < 10-19 < 20-29 < 30-39 < 40-49 < 50-59 < 60-69 < ... < 100+

# split into groups of five years
age_groups(ages, 1:20 * 5)
#> [1] 0-4   5-9   15-19 50-54 30-34 75-79 100+  40-44 20-24
#> 21 Levels: 0-4 < 5-9 < 10-14 < 15-19 < 20-24 < 25-29 < 30-34 < ... < 100+
age_groups(ages, split_at = "fives")
#> [1] 0-4   5-9   15-19 50-54 30-34 75-79 100+  40-44 20-24
#> 21 Levels: 0-4 < 5-9 < 10-14 < 15-19 < 20-24 < 25-29 < 30-34 < ... < 100+

# split specifically for children
age_groups(ages, c(1, 2, 4, 6, 13, 18))
#> [1] 2-3   6-12  13-17 18+   18+   18+   18+   18+   18+  
#> Levels: 0 < 1 < 2-3 < 4-5 < 6-12 < 13-17 < 18+
age_groups(ages, "children")
#> [1] 2-3   6-12  13-17 18+   18+   18+   18+   18+   18+  
#> Levels: 0 < 1 < 2-3 < 4-5 < 6-12 < 13-17 < 18+

# \donttest{
# 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"
    )
}
#> Loading required package: ggplot2

# }

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