# 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](https://rdrr.io/r/base/factor.html).

## Usage

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

## Arguments

- x:

  Age, e.g. calculated with
  [`age()`](https://amr-for-r.org/reference/age.md).

- 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](https://rdrr.io/r/base/logical.html) to indicate whether
  missing values should be removed.

## Value

Ordered [factor](https://rdrr.io/r/base/factor.html)

## Details

To split ages, the input for the `split_at` argument can be:

- A [numeric](https://rdrr.io/r/base/numeric.html) 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()`](https://amr-for-r.org/reference/age.md) function.

## Examples

``` r
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

# }
```