standardize_age_groups: Standardize Age Groups

In GerkeLab/fcds: Process Data from the Florida Cancer Data System

Description

Standardizes age groups to match seer_std_ages. Adds an age_group column, or overwites the existing age_group column if present. The age_var column can be either an actual age or an age group. If the column is numeric, it assumed to be an actual age, otherwise if it contains any non-numeric characters it is assumed to be an age group that will be expanded using separate_age_groups(). If multiple standardized age groups match a given age, the function will throw an error.

Usage

standardize_age_groups(data = NULL, age_group = age_group,
  std_age_groups = fcds_const("age_group"), ...)

Arguments

data	A data frame.
age_group	The column containing age or age group. This column will be overwritten if named age_group. If the column is numeric or can be coerced to numeric, it is treated as actual age. Otherwise it is assumed to contain age groups.
std_age_groups	Standard age groups, in the desired order.
...	Arguments passed on to separate_age_groups sep Separator between columns. If character, is interpreted as a regular expression. The default value is a regular expression that matches any sequence of non-alphanumeric values. If numeric, interpreted as positions to split at. Positive values start at 1 at the far-left of the string; negative value start at -1 at the far-right of the string. The length of sep should be one less than into.

See Also

format_age_groups() for the specification of the age group label format and to convert age boundaries into age group labels.

Other age processors: complete_age_groups, filter_age_groups, format_age_groups, recode_age_groups, separate_age_groups

Examples

dplyr::tibble(
  id = 1:4,
  age_group = c("0 - 4", "10-14", "65-69", "85+")
) %>%
  standardize_age_groups()

GerkeLab/fcds documentation built on July 30, 2020, 7:04 p.m.