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Split Ages into Age Groups

Source: R/age.R
age_groups.Rd

Split ages into age groups defined by the split argument. This allows for easier demographic (antimicrobial resistance) analysis.

Usage

age_groups(x, split_at = c(12, 25, 55, 75), 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.

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+.

See also

To determine ages, based on one or more reference dates, use the age() function.

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+

# 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
#> Warning: in as.sir(): 271 results in index 'age_group' truncated (100%) that were
#> invalid antimicrobial interpretations: "0-11", "12-24", "25-54", "55-74",
#> and "75+"
#> Error in ggplot2::geom_col(data = function(x) {    sir_df(data = x, translate_ab = translate_ab, language = language,         minimum = minimum, combine_SI = combine_SI)}, mapping = utils::modifyList(ggplot2::aes(), list(x = str2lang(x),     y = str2lang(y), fill = str2lang(fill))), position = position,     ...): Problem while computing layer data.
#> ℹ Error occurred in the 1st layer.
#> Caused by error in `sir_df()`:
#> ! incorrect number of dimensions
# }