mirror of
https://github.com/msberends/AMR.git
synced 2024-12-26 06:46:11 +01:00
233 lines
9.6 KiB
R
Executable File
233 lines
9.6 KiB
R
Executable File
# ==================================================================== #
|
|
# TITLE #
|
|
# AMR: An R Package for Working with Antimicrobial Resistance Data #
|
|
# #
|
|
# SOURCE #
|
|
# https://github.com/msberends/AMR #
|
|
# #
|
|
# CITE AS #
|
|
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
|
|
# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
|
|
# Data. Journal of Statistical Software, 104(3), 1-31. #
|
|
# doi:10.18637/jss.v104.i03 #
|
|
# #
|
|
# Developed at the University of Groningen, the Netherlands, in #
|
|
# collaboration with non-profit organisations Certe Medical #
|
|
# Diagnostics & Advice, and University Medical Center Groningen. #
|
|
# #
|
|
# This R package is free software; you can freely use and distribute #
|
|
# it for both personal and commercial purposes under the terms of the #
|
|
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
|
# the Free Software Foundation. #
|
|
# We created this package for both routine data analysis and academic #
|
|
# research and it was publicly released in the hope that it will be #
|
|
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
|
# #
|
|
# Visit our website for the full manual and a complete tutorial about #
|
|
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
|
# ==================================================================== #
|
|
|
|
#' Age in Years of Individuals
|
|
#'
|
|
#' Calculates age in years based on a reference date, which is the system date at default.
|
|
#' @param x date(s), [character] (vectors) will be coerced with [as.POSIXlt()]
|
|
#' @param reference reference date(s) (defaults to today), [character] (vectors) will be coerced with [as.POSIXlt()]
|
|
#' @param exact a [logical] to indicate whether age calculation should be exact, i.e. with decimals. It divides the number of days of [year-to-date](https://en.wikipedia.org/wiki/Year-to-date) (YTD) of `x` by the number of days in the year of `reference` (either 365 or 366).
|
|
#' @param na.rm a [logical] to indicate whether missing values should be removed
|
|
#' @param ... arguments passed on to [as.POSIXlt()], such as `origin`
|
|
#' @details Ages below 0 will be returned as `NA` with a warning. Ages above 120 will only give a warning.
|
|
#'
|
|
#' This function vectorises over both `x` and `reference`, meaning that either can have a length of 1 while the other argument has a larger length.
|
|
#' @return An [integer] (no decimals) if `exact = FALSE`, a [double] (with decimals) otherwise
|
|
#' @seealso To split ages into groups, use the [age_groups()] function.
|
|
#' @export
|
|
#' @examples
|
|
#' # 10 random pre-Y2K birth dates
|
|
#' df <- data.frame(birth_date = as.Date("2000-01-01") - runif(10) * 25000)
|
|
#'
|
|
#' # add ages
|
|
#' df$age <- age(df$birth_date)
|
|
#'
|
|
#' # add exact ages
|
|
#' df$age_exact <- age(df$birth_date, exact = TRUE)
|
|
#'
|
|
#' # add age at millenium switch
|
|
#' df$age_at_y2k <- age(df$birth_date, "2000-01-01")
|
|
#'
|
|
#' df
|
|
age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
|
|
meet_criteria(x, allow_class = c("character", "Date", "POSIXt"))
|
|
meet_criteria(reference, allow_class = c("character", "Date", "POSIXt"))
|
|
meet_criteria(exact, allow_class = "logical", has_length = 1)
|
|
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
|
|
|
|
if (length(x) != length(reference)) {
|
|
if (length(x) == 1) {
|
|
x <- rep(x, length(reference))
|
|
} else if (length(reference) == 1) {
|
|
reference <- rep(reference, length(x))
|
|
} else {
|
|
stop_("`x` and `reference` must be of same length, or `reference` must be of length 1.")
|
|
}
|
|
}
|
|
x <- as.POSIXlt(x, ...)
|
|
reference <- as.POSIXlt(reference, ...)
|
|
|
|
# from https://stackoverflow.com/a/25450756/4575331
|
|
years_gap <- reference$year - x$year
|
|
ages <- ifelse(reference$mon < x$mon | (reference$mon == x$mon & reference$mday < x$mday),
|
|
as.integer(years_gap - 1),
|
|
as.integer(years_gap)
|
|
)
|
|
|
|
# add decimals
|
|
if (exact == TRUE) {
|
|
# get dates of `x` when `x` would have the year of `reference`
|
|
x_in_reference_year <- as.POSIXlt(paste0(
|
|
format(as.Date(reference), "%Y"),
|
|
format(as.Date(x), "-%m-%d")
|
|
),
|
|
format = "%Y-%m-%d"
|
|
)
|
|
# get differences in days
|
|
n_days_x_rest <- as.double(difftime(as.Date(reference),
|
|
as.Date(x_in_reference_year),
|
|
units = "days"
|
|
))
|
|
# get numbers of days the years of `reference` has for a reliable denominator
|
|
n_days_reference_year <- as.POSIXlt(paste0(format(as.Date(reference), "%Y"), "-12-31"),
|
|
format = "%Y-%m-%d"
|
|
)$yday + 1
|
|
# add decimal parts of year
|
|
mod <- n_days_x_rest / n_days_reference_year
|
|
# negative mods are cases where `x_in_reference_year` > `reference` - so 'add' a year
|
|
mod[!is.na(mod) & mod < 0] <- mod[!is.na(mod) & mod < 0] + 1
|
|
# and finally add to ages
|
|
ages <- ages + mod
|
|
}
|
|
|
|
if (any(ages < 0, na.rm = TRUE)) {
|
|
ages[!is.na(ages) & ages < 0] <- NA
|
|
warning_("in `age()`: NAs introduced for ages below 0.")
|
|
}
|
|
if (any(ages > 120, na.rm = TRUE)) {
|
|
warning_("in `age()`: some ages are above 120.")
|
|
}
|
|
|
|
if (isTRUE(na.rm)) {
|
|
ages <- ages[!is.na(ages)]
|
|
}
|
|
|
|
if (exact == TRUE) {
|
|
as.double(ages)
|
|
} else {
|
|
as.integer(ages)
|
|
}
|
|
}
|
|
|
|
#' Split Ages into Age Groups
|
|
#'
|
|
#' Split ages into age groups defined by the `split` argument. This allows for easier demographic (antimicrobial resistance) analysis.
|
|
#' @param x age, e.g. calculated with [age()]
|
|
#' @param split_at values to split `x` at, defaults to age groups 0-11, 12-24, 25-54, 55-74 and 75+. See *Details*.
|
|
#' @param na.rm a [logical] to indicate whether missing values should be removed
|
|
#' @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+.
|
|
#' @return Ordered [factor]
|
|
#' @seealso To determine ages, based on one or more reference dates, use the [age()] function.
|
|
#' @export
|
|
|
|
#' @examples
|
|
#' 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")
|
|
#'
|
|
#' \donttest{
|
|
#' # resistance of ciprofloxacin per age group
|
|
#' if (require("dplyr")) {
|
|
#' example_isolates %>%
|
|
#' filter_first_isolate() %>%
|
|
#' filter(mo == as.mo("Escherichia coli")) %>%
|
|
#' group_by(age_group = age_groups(age)) %>%
|
|
#' select(age_group, CIP) %>%
|
|
#' ggplot_rsi(
|
|
#' x = "age_group",
|
|
#' minimum = 0,
|
|
#' x.title = "Age Group",
|
|
#' title = "Ciprofloxacin resistance per age group"
|
|
#' )
|
|
#' }
|
|
#' }
|
|
age_groups <- function(x, split_at = c(12, 25, 55, 75), na.rm = FALSE) {
|
|
meet_criteria(x, allow_class = c("numeric", "integer"), is_positive_or_zero = TRUE, is_finite = TRUE)
|
|
meet_criteria(split_at, allow_class = c("numeric", "integer", "character"), is_positive_or_zero = TRUE, is_finite = TRUE)
|
|
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
|
|
|
|
if (any(x < 0, na.rm = TRUE)) {
|
|
x[x < 0] <- NA
|
|
warning_("in `age_groups()`: NAs introduced for ages below 0.")
|
|
}
|
|
if (is.character(split_at)) {
|
|
split_at <- split_at[1L]
|
|
if (split_at %like% "^(child|kid|junior)") {
|
|
split_at <- c(0, 1, 2, 4, 6, 13, 18)
|
|
} else if (split_at %like% "^(elder|senior)") {
|
|
split_at <- c(65, 75, 85)
|
|
} else if (split_at %like% "^five") {
|
|
split_at <- 1:20 * 5
|
|
} else if (split_at %like% "^ten") {
|
|
split_at <- 1:10 * 10
|
|
}
|
|
}
|
|
split_at <- sort(unique(as.integer(split_at)))
|
|
if (!split_at[1] == 0) {
|
|
# add base number 0
|
|
split_at <- c(0, split_at)
|
|
}
|
|
split_at <- split_at[!is.na(split_at)]
|
|
stop_if(length(split_at) == 1, "invalid value for `split_at`") # only 0 is available
|
|
|
|
# turn input values to 'split_at' indices
|
|
y <- x
|
|
lbls <- split_at
|
|
for (i in seq_len(length(split_at))) {
|
|
y[x >= split_at[i]] <- i
|
|
# create labels
|
|
lbls[i - 1] <- paste0(unique(c(split_at[i - 1], split_at[i] - 1)), collapse = "-")
|
|
}
|
|
|
|
# last category
|
|
lbls[length(lbls)] <- paste0(split_at[length(split_at)], "+")
|
|
|
|
agegroups <- factor(lbls[y], levels = lbls, ordered = TRUE)
|
|
|
|
if (isTRUE(na.rm)) {
|
|
agegroups <- agegroups[!is.na(agegroups)]
|
|
}
|
|
|
|
agegroups
|
|
}
|