mirror of
https://github.com/msberends/AMR.git
synced 2025-07-21 20:53:15 +02:00
(v1.1.0.9005) lose dependencies
This commit is contained in:
132
R/proportion.R
132
R/proportion.R
@ -21,7 +21,7 @@
|
||||
|
||||
#' Calculate microbial resistance
|
||||
#'
|
||||
#' @description These functions can be used to calculate the (co-)resistance or susceptibility of microbial isolates (i.e. percentage of S, SI, I, IR or R). All functions support quasiquotation with pipes, can be used in [summarise()] from the `dplyr` package and also supports grouped variables, please see *Examples*.
|
||||
#' @description These functions can be used to calculate the (co-)resistance or susceptibility of microbial isolates (i.e. percentage of S, SI, I, IR or R). All functions support quasiquotation with pipes, can be used in `summarise()` from the `dplyr` package and also support grouped variables, please see *Examples*.
|
||||
#'
|
||||
#' [resistance()] should be used to calculate resistance, [susceptibility()] should be used to calculate susceptibility.\cr
|
||||
#' @inheritSection lifecycle Stable lifecycle
|
||||
@ -99,71 +99,71 @@
|
||||
#' proportion_IR(example_isolates$AMX)
|
||||
#' proportion_R(example_isolates$AMX)
|
||||
#'
|
||||
#' \dontrun{
|
||||
#' library(dplyr)
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(r = resistance(CIP),
|
||||
#' n = n_rsi(CIP)) # n_rsi works like n_distinct in dplyr, see ?n_rsi
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(R = resistance(CIP, as_percent = TRUE),
|
||||
#' SI = susceptibility(CIP, as_percent = TRUE),
|
||||
#' n1 = count_all(CIP), # the actual total; sum of all three
|
||||
#' n2 = n_rsi(CIP), # same - analogous to n_distinct
|
||||
#' total = n()) # NOT the number of tested isolates!
|
||||
#'
|
||||
#' # Calculate co-resistance between amoxicillin/clav acid and gentamicin,
|
||||
#' # so we can see that combination therapy does a lot more than mono therapy:
|
||||
#' example_isolates %>% susceptibility(AMC) # %SI = 76.3%
|
||||
#' example_isolates %>% count_all(AMC) # n = 1879
|
||||
#'
|
||||
#' example_isolates %>% susceptibility(GEN) # %SI = 75.4%
|
||||
#' example_isolates %>% count_all(GEN) # n = 1855
|
||||
#'
|
||||
#' example_isolates %>% susceptibility(AMC, GEN) # %SI = 94.1%
|
||||
#' example_isolates %>% count_all(AMC, GEN) # n = 1939
|
||||
#'
|
||||
#'
|
||||
#' # See Details on how `only_all_tested` works. Example:
|
||||
#' example_isolates %>%
|
||||
#' summarise(numerator = count_susceptible(AMC, GEN),
|
||||
#' denominator = count_all(AMC, GEN),
|
||||
#' proportion = susceptibility(AMC, GEN))
|
||||
|
||||
#' example_isolates %>%
|
||||
#' summarise(numerator = count_susceptible(AMC, GEN, only_all_tested = TRUE),
|
||||
#' denominator = count_all(AMC, GEN, only_all_tested = TRUE),
|
||||
#' proportion = susceptibility(AMC, GEN, only_all_tested = TRUE))
|
||||
#'
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(cipro_p = susceptibility(CIP, as_percent = TRUE),
|
||||
#' cipro_n = count_all(CIP),
|
||||
#' genta_p = susceptibility(GEN, as_percent = TRUE),
|
||||
#' genta_n = count_all(GEN),
|
||||
#' combination_p = susceptibility(CIP, GEN, as_percent = TRUE),
|
||||
#' combination_n = count_all(CIP, GEN))
|
||||
#'
|
||||
#' # Get proportions S/I/R immediately of all rsi columns
|
||||
#' example_isolates %>%
|
||||
#' select(AMX, CIP) %>%
|
||||
#' proportion_df(translate = FALSE)
|
||||
#'
|
||||
#' # It also supports grouping variables
|
||||
#' example_isolates %>%
|
||||
#' select(hospital_id, AMX, CIP) %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' proportion_df(translate = FALSE)
|
||||
#'
|
||||
#' # calculate current empiric combination therapy of Helicobacter gastritis:
|
||||
#' my_table %>%
|
||||
#' filter(first_isolate == TRUE,
|
||||
#' genus == "Helicobacter") %>%
|
||||
#' summarise(p = susceptibility(AMX, MTR), # amoxicillin with metronidazole
|
||||
#' n = count_all(AMX, MTR))
|
||||
#' if (!require("dplyr")) {
|
||||
#' library(dplyr)
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(r = resistance(CIP),
|
||||
#' n = n_rsi(CIP)) # n_rsi works like n_distinct in dplyr, see ?n_rsi
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(R = resistance(CIP, as_percent = TRUE),
|
||||
#' SI = susceptibility(CIP, as_percent = TRUE),
|
||||
#' n1 = count_all(CIP), # the actual total; sum of all three
|
||||
#' n2 = n_rsi(CIP), # same - analogous to n_distinct
|
||||
#' total = n()) # NOT the number of tested isolates!
|
||||
#'
|
||||
#' # Calculate co-resistance between amoxicillin/clav acid and gentamicin,
|
||||
#' # so we can see that combination therapy does a lot more than mono therapy:
|
||||
#' example_isolates %>% susceptibility(AMC) # %SI = 76.3%
|
||||
#' example_isolates %>% count_all(AMC) # n = 1879
|
||||
#'
|
||||
#' example_isolates %>% susceptibility(GEN) # %SI = 75.4%
|
||||
#' example_isolates %>% count_all(GEN) # n = 1855
|
||||
#'
|
||||
#' example_isolates %>% susceptibility(AMC, GEN) # %SI = 94.1%
|
||||
#' example_isolates %>% count_all(AMC, GEN) # n = 1939
|
||||
#'
|
||||
#'
|
||||
#' # See Details on how `only_all_tested` works. Example:
|
||||
#' example_isolates %>%
|
||||
#' summarise(numerator = count_susceptible(AMC, GEN),
|
||||
#' denominator = count_all(AMC, GEN),
|
||||
#' proportion = susceptibility(AMC, GEN))
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' summarise(numerator = count_susceptible(AMC, GEN, only_all_tested = TRUE),
|
||||
#' denominator = count_all(AMC, GEN, only_all_tested = TRUE),
|
||||
#' proportion = susceptibility(AMC, GEN, only_all_tested = TRUE))
|
||||
#'
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(cipro_p = susceptibility(CIP, as_percent = TRUE),
|
||||
#' cipro_n = count_all(CIP),
|
||||
#' genta_p = susceptibility(GEN, as_percent = TRUE),
|
||||
#' genta_n = count_all(GEN),
|
||||
#' combination_p = susceptibility(CIP, GEN, as_percent = TRUE),
|
||||
#' combination_n = count_all(CIP, GEN))
|
||||
#'
|
||||
#' # Get proportions S/I/R immediately of all rsi columns
|
||||
#' example_isolates %>%
|
||||
#' select(AMX, CIP) %>%
|
||||
#' proportion_df(translate = FALSE)
|
||||
#'
|
||||
#' # It also supports grouping variables
|
||||
#' example_isolates %>%
|
||||
#' select(hospital_id, AMX, CIP) %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' proportion_df(translate = FALSE)
|
||||
#'
|
||||
#' # calculate current empiric combination therapy of Helicobacter gastritis:
|
||||
#' my_table %>%
|
||||
#' filter(first_isolate == TRUE,
|
||||
#' genus == "Helicobacter") %>%
|
||||
#' summarise(p = susceptibility(AMX, MTR), # amoxicillin with metronidazole
|
||||
#' n = count_all(AMX, MTR))
|
||||
#' }
|
||||
resistance <- function(...,
|
||||
minimum = 30,
|
||||
|
||||
Reference in New Issue
Block a user