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@ -27,11 +27,11 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Mean AMR Distance
#' Calculate the Mean AMR Distance
#'
#' This function calculates a normalised mean for antimicrobial resistance between multiple observations.
#' Calculates a normalised mean for antimicrobial resistance between multiple observations, to help to identify similar isolates without comparing antibiograms by hand.
#' @param x a vector of class [rsi][as.rsi()], [rsi][as.rsi()] or [rsi][as.rsi()], or a [data.frame] containing columns of any of these classes
#' @param ... variables to select (supports tidy selection such as `column1:column4` and [`where(is.mic)`][tidyselect::language]), and can thus also be [antibiotic selectors][ab_selector()]
#' @param ... variables to select (supports [tidyselect language][tidyselect::language] such as `column1:column4` and `where(is.mic)`, and can thus also be [antibiotic selectors][ab_selector()]
#' @param combine_SI a [logical] to indicate whether all values of S and I must be merged into one, so the input only consists of S+I vs. R (susceptible vs. resistant), defaults to `TRUE`
#' @details The mean AMR distance is a normalised numeric value to compare AMR test results and can help to identify similar isolates, without comparing antibiograms by hand. For common numeric data this distance is equal to [Z scores](https://en.wikipedia.org/wiki/Standard_score) (the number of standard deviations from the mean).
#'
@ -83,20 +83,20 @@ mean_amr_distance <- function(x, ...) {
UseMethod("mean_amr_distance")
}
#' @rdname mean_amr_distance
#' @noRd
#' @export
mean_amr_distance.default <- function(x, ...) {
x <- as.double(x)
(x - mean(x, na.rm = TRUE)) / stats::sd(x, na.rm = TRUE)
}
#' @rdname mean_amr_distance
#' @noRd
#' @export
mean_amr_distance.mic <- function(x, ...) {
mean_amr_distance(log2(x))
}
#' @rdname mean_amr_distance
#' @noRd
#' @export
mean_amr_distance.disk <- function(x, ...) {
mean_amr_distance(as.double(x))