mirror of
https://github.com/msberends/AMR.git
synced 2024-12-27 13:26:11 +01:00
147 lines
5.0 KiB
R
147 lines
5.0 KiB
R
# ==================================================================== #
|
|
# TITLE: #
|
|
# AMR: An R Package for Working with Antimicrobial Resistance Data #
|
|
# #
|
|
# SOURCE CODE: #
|
|
# https://github.com/msberends/AMR #
|
|
# #
|
|
# PLEASE CITE THIS SOFTWARE 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. #
|
|
# https://doi.org/10.18637/jss.v104.i03 #
|
|
# #
|
|
# Developed at the University of Groningen and the University Medical #
|
|
# Center Groningen in The Netherlands, in collaboration with many #
|
|
# colleagues from around the world, see our website. #
|
|
# #
|
|
# 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/ #
|
|
# ==================================================================== #
|
|
|
|
patients <- unlist(lapply(LETTERS, paste0, 1:10))
|
|
|
|
patients_table <- data.frame(
|
|
patient_id = patients,
|
|
gender = c(
|
|
rep("M", 135),
|
|
rep("F", 125)
|
|
)
|
|
)
|
|
|
|
dates <- seq(as.Date("2011-01-01"), as.Date("2020-01-01"), by = "day")
|
|
|
|
bacteria_a <- c(
|
|
"E. coli", "S. aureus",
|
|
"S. pneumoniae", "K. pneumoniae"
|
|
)
|
|
|
|
bacteria_b <- c("esccol", "staaur", "strpne", "klepne")
|
|
|
|
bacteria_c <- c(
|
|
"Escherichia coli", "Staphylococcus aureus",
|
|
"Streptococcus pneumoniae", "Klebsiella pneumoniae"
|
|
)
|
|
|
|
ab_interpretations <- c("S", "I", "R")
|
|
|
|
ab_interpretations_messy <- c("R", "< 0.5 S", "I")
|
|
|
|
sample_size <- 1000
|
|
|
|
data_a <- data.frame(
|
|
date = sample(dates, size = sample_size, replace = TRUE),
|
|
hospital = "A",
|
|
bacteria = sample(bacteria_a,
|
|
size = sample_size, replace = TRUE,
|
|
prob = c(0.50, 0.25, 0.15, 0.10)
|
|
),
|
|
AMX = sample(ab_interpretations,
|
|
size = sample_size, replace = TRUE,
|
|
prob = c(0.60, 0.05, 0.35)
|
|
),
|
|
AMC = sample(ab_interpretations,
|
|
size = sample_size, replace = TRUE,
|
|
prob = c(0.75, 0.10, 0.15)
|
|
),
|
|
CIP = sample(ab_interpretations,
|
|
size = sample_size, replace = TRUE,
|
|
prob = c(0.80, 0.00, 0.20)
|
|
),
|
|
GEN = sample(ab_interpretations,
|
|
size = sample_size, replace = TRUE,
|
|
prob = c(0.92, 0.00, 0.08)
|
|
)
|
|
)
|
|
|
|
|
|
data_b <- data.frame(
|
|
date = sample(dates, size = sample_size, replace = TRUE),
|
|
hospital = "B",
|
|
bacteria = sample(bacteria_b,
|
|
size = sample_size, replace = TRUE,
|
|
prob = c(0.50, 0.25, 0.15, 0.10)
|
|
),
|
|
AMX = sample(ab_interpretations_messy,
|
|
size = sample_size, replace = TRUE,
|
|
prob = c(0.60, 0.05, 0.35)
|
|
),
|
|
AMC = sample(ab_interpretations_messy,
|
|
size = sample_size, replace = TRUE,
|
|
prob = c(0.75, 0.10, 0.15)
|
|
),
|
|
CIP = sample(ab_interpretations_messy,
|
|
size = sample_size, replace = TRUE,
|
|
prob = c(0.80, 0.00, 0.20)
|
|
),
|
|
GEN = sample(ab_interpretations_messy,
|
|
size = sample_size, replace = TRUE,
|
|
prob = c(0.92, 0.00, 0.08)
|
|
)
|
|
)
|
|
|
|
data_c <- data.frame(
|
|
date = sample(dates, size = sample_size, replace = TRUE),
|
|
hospital = "C",
|
|
bacteria = sample(bacteria_c,
|
|
size = sample_size, replace = TRUE,
|
|
prob = c(0.50, 0.25, 0.15, 0.10)
|
|
),
|
|
AMX = sample(ab_interpretations,
|
|
size = sample_size, replace = TRUE,
|
|
prob = c(0.60, 0.05, 0.35)
|
|
),
|
|
AMC = sample(ab_interpretations,
|
|
size = sample_size, replace = TRUE,
|
|
prob = c(0.75, 0.10, 0.15)
|
|
),
|
|
CIP = sample(ab_interpretations,
|
|
size = sample_size, replace = TRUE,
|
|
prob = c(0.80, 0.00, 0.20)
|
|
),
|
|
GEN = sample(ab_interpretations,
|
|
size = sample_size, replace = TRUE,
|
|
prob = c(0.92, 0.00, 0.08)
|
|
)
|
|
)
|
|
|
|
|
|
example_isolates_unclean <- data_a %>%
|
|
bind_rows(data_b, data_c)
|
|
|
|
example_isolates_unclean$patient_id <- sample(patients, size = nrow(example_isolates_unclean), replace = TRUE)
|
|
|
|
example_isolates_unclean <- example_isolates_unclean %>%
|
|
select(patient_id, hospital, date, bacteria, everything()) %>%
|
|
dataset_UTF8_to_ASCII()
|
|
|
|
usethis::use_data(example_isolates_unclean, overwrite = TRUE, internal = FALSE, version = 2, compress = "xz")
|