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(v1.6.0.9021) join functions update

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2021-05-12 18:15:03 +02:00
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119 changed files with 973 additions and 1040 deletions

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#' @format A [data.frame] with `r format(nrow(example_isolates), big.mark = ",")` observations and `r ncol(example_isolates)` variables:
#' - `date`\cr date of receipt at the laboratory
#' - `hospital_id`\cr ID of the hospital, from A to D
#' - `ward_icu`\cr logical to determine if ward is an intensive care unit
#' - `ward_clinical`\cr logical to determine if ward is a regular clinical ward
#' - `ward_outpatient`\cr logical to determine if ward is an outpatient clinic
#' - `ward_icu`\cr [logical] to determine if ward is an intensive care unit
#' - `ward_clinical`\cr [logical] to determine if ward is a regular clinical ward
#' - `ward_outpatient`\cr [logical] to determine if ward is an outpatient clinic
#' - `age`\cr age of the patient
#' - `gender`\cr gender of the patient
#' - `patient_id`\cr ID of the patient
@ -217,8 +217,8 @@
#' - `Sex`\cr Fictitious gender of patient
#' - `Age`\cr Fictitious age of patient
#' - `Age category`\cr Age group, can also be looked up using [age_groups()]
#' - `Date of admission`\cr Date of hospital admission
#' - `Specimen date`\cr Date when specimen was received at laboratory
#' - `Date of admission`\cr [Date] of hospital admission
#' - `Specimen date`\cr [Date] when specimen was received at laboratory
#' - `Specimen type`\cr Specimen type or group
#' - `Specimen type (Numeric)`\cr Translation of `"Specimen type"`
#' - `Reason`\cr Reason of request with Differential Diagnosis
@ -231,7 +231,7 @@
#' - `MRSA screening test`\cr Microorganism is possible MRSA?
#' - `Inducible clindamycin resistance`\cr Clindamycin can be induced?
#' - `Comment`\cr Other comments
#' - `Date of data entry`\cr Date this data was entered in WHONET
#' - `Date of data entry`\cr [Date] this data was entered in WHONET
#' - `AMP_ND10:CIP_EE`\cr `r sum(vapply(FUN.VALUE = logical(1), WHONET, is.rsi))` different antibiotics. You can lookup the abbreviations in the [antibiotics] data set, or use e.g. [`ab_name("AMP")`][ab_name()] to get the official name immediately. Before analysis, you should transform this to a valid antibiotic class, using [as.rsi()].
#' @inheritSection AMR Reference Data Publicly Available
#' @inheritSection AMR Read more on Our Website!
@ -250,7 +250,7 @@
#' - `disk_dose`\cr Dose of the used disk diffusion method
#' - `breakpoint_S`\cr Lowest MIC value or highest number of millimetres that leads to "S"
#' - `breakpoint_R`\cr Highest MIC value or lowest number of millimetres that leads to "R"
#' - `uti`\cr A logical value (`TRUE`/`FALSE`) to indicate whether the rule applies to a urinary tract infection (UTI)
#' - `uti`\cr A [logical] value (`TRUE`/`FALSE`) to indicate whether the rule applies to a urinary tract infection (UTI)
#' @details The repository of this `AMR` package contains a file comprising this exact data set: <https://github.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt>. This file **allows for machine reading EUCAST and CLSI guidelines**, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. The file is updated automatically.
#' @inheritSection AMR Reference Data Publicly Available
#' @inheritSection AMR Read more on Our Website!