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(v1.4.0.9043) documentation update

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dr. M.S. (Matthijs) Berends
2020-12-22 00:51:17 +01:00
parent ee70883246
commit 128ebcfd62
107 changed files with 518 additions and 475 deletions
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16
R/first_isolate.R
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@ -37,16 +37,16 @@
#' @param col_keyantibiotics column name of the key antibiotics to determine first *weighted* isolates, see [key_antibiotics()]. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' (case insensitive). Use `col_keyantibiotics = FALSE` to prevent this.
#' @param episode_days episode in days after which a genus/species combination will be determined as 'first isolate' again. The default of 365 days is based on the guideline by CLSI, see Source.
#' @param testcodes_exclude character vector with test codes that should be excluded (case-insensitive)
#' @param icu_exclude logical whether ICU isolates should be excluded (rows with value `TRUE` in column `col_icu`)
#' @param specimen_group value in column `col_specimen` to filter on
#' @param icu_exclude logical whether ICU isolates should be excluded (rows with value `TRUE` in the column set with `col_icu`)
#' @param specimen_group value in the column set with `col_specimen` to filter on
#' @param type type to determine weighed isolates; can be `"keyantibiotics"` or `"points"`, see Details
#' @param ignore_I logical to determine whether antibiotic interpretations with `"I"` will be ignored when `type = "keyantibiotics"`, see Details
#' @param points_threshold points until the comparison of key antibiotics will lead to inclusion of an isolate when `type = "points"`, see Details
#' @param info print progress
#' @param include_unknown logical to determine whether 'unknown' microorganisms should be included too, i.e. microbial code `"UNKNOWN"`, which defaults to `FALSE`. For WHONET users, this means that all records with organism code `"con"` (*contamination*) will be excluded at default. Isolates with a microbial ID of `NA` will always be excluded as first isolate.
#' @param ... parameters passed on to [first_isolate()] when using [filter_first_isolate()], or parameters passed on to [key_antibiotics()] when using [filter_first_weighted_isolate()]
#' @param ... arguments passed on to [first_isolate()] when using [filter_first_isolate()], or arguments passed on to [key_antibiotics()] when using [filter_first_weighted_isolate()]
#' @details
#' These functions are context-aware when used inside `dplyr` verbs, such as `filter()`, `mutate()` and `summarise()`. This means that then the `x` parameter can be omitted, please see *Examples*.
#' These functions are context-aware when used inside `dplyr` verbs, such as `filter()`, `mutate()` and `summarise()`. This means that then the `x` argument can be omitted, please see *Examples*.
#'
#' The [first_isolate()] function is a wrapper around the [is_new_episode()] function, but more efficient for data sets containing microorganism codes or names.
#'
@ -80,11 +80,11 @@
#' @section Key antibiotics:
#' There are two ways to determine whether isolates can be included as first *weighted* isolates which will give generally the same results:
#'
#' 1. Using `type = "keyantibiotics"` and parameter `ignore_I`
#' 1. Using `type = "keyantibiotics"` and argument `ignore_I`
#'
#' Any difference from S to R (or vice versa) will (re)select an isolate as a first weighted isolate. With `ignore_I = FALSE`, also differences from I to S|R (or vice versa) will lead to this. This is a reliable method and 30-35 times faster than method 2. Read more about this in the [key_antibiotics()] function.
#'
#' 2. Using `type = "points"` and parameter `points_threshold`
#' 2. Using `type = "points"` and argument `points_threshold`
#'
#' A difference from I to S|R (or vice versa) means 0.5 points, a difference from S to R (or vice versa) means 1 point. When the sum of points exceeds `points_threshold`, which default to `2`, an isolate will be (re)selected as a first weighted isolate.
#' @rdname first_isolate
@ -184,7 +184,7 @@ first_isolate <- function(x,
dots <- unlist(list(...))
if (length(dots) != 0) {
# backwards compatibility with old parameters
# backwards compatibility with old arguments
dots.names <- dots %pm>% names()
if ("filter_specimen" %in% dots.names) {
specimen_group <- dots[which(dots.names == "filter_specimen")]
@ -238,7 +238,7 @@ first_isolate <- function(x,
check_columns_existance <- function(column, tblname = x) {
if (!is.null(column)) {
stop_ifnot(column %in% colnames(tblname),
"Column `", column, "` not found.", call = FALSE)
"Column '", column, "' not found.", call = FALSE)
}
}