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make rsi work in more cases, documentation update

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2023-02-22 14:38:57 +01:00
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87 changed files with 401 additions and 327 deletions

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#' 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 [sir][as.sir()], [mic][as.mic()] or [disk][as.disk()], or a [data.frame] containing columns of any of these classes
#' @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`
#' @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) - the default is `TRUE`
#' @details The mean AMR distance is effectively [the Z-score](https://en.wikipedia.org/wiki/Standard_score); a normalised numeric value to compare AMR test results which can help to identify similar isolates, without comparing antibiograms by hand.
#'
#' MIC values (see [as.mic()]) are transformed with [log2()] first; their distance is thus calculated as `(log2(x) - mean(log2(x))) / sd(log2(x))`.