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(v0.7.1.9016) deps
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@ -70,7 +70,7 @@
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#' @keywords isolate isolates first
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#' @seealso \code{\link{key_antibiotics}}
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#' @export
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#' @importFrom dplyr arrange_at lag between row_number filter mutate arrange pull
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#' @importFrom dplyr arrange_at lag between row_number filter mutate arrange pull ungroup
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#' @importFrom crayon blue bold silver
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#' @return Logical vector
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#' @source Methodology of this function is based on: \strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition}, 2014, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
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2
R/mic.R
2
R/mic.R
@ -51,6 +51,8 @@
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#'
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#' plot(mic_data)
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#' barplot(mic_data)
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#'
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#' library(clean)
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#' freq(mic_data)
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as.mic <- function(x, na.rm = FALSE) {
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if (is.mic(x)) {
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1
R/mo.R
1
R/mo.R
@ -1412,6 +1412,7 @@ print.mo <- function(x, ...) {
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#' @exportMethod summary.mo
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#' @importFrom dplyr n_distinct
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#' @importFrom clean freq top_freq
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#' @export
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#' @noRd
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summary.mo <- function(object, ...) {
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@ -58,7 +58,7 @@
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#' @rdname resistance_predict
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#' @export
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#' @importFrom stats predict glm lm
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#' @importFrom dplyr %>% pull mutate mutate_at n group_by_at summarise filter filter_at all_vars n_distinct arrange case_when n_groups transmute
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#' @importFrom dplyr %>% pull mutate mutate_at n group_by_at summarise filter filter_at all_vars n_distinct arrange case_when n_groups transmute ungroup
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#' @inheritSection AMR Read more on our website!
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#' @examples
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#' x <- resistance_predict(septic_patients, col_ab = "AMX", year_min = 2010)
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4
R/rsi.R
4
R/rsi.R
@ -50,7 +50,7 @@
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#' @return Ordered factor with new class \code{rsi}
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#' @keywords rsi
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#' @export
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#' @importFrom dplyr %>%
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#' @importFrom dplyr %>% desc arrange filter
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#' @seealso \code{\link{as.mic}}
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#' @inheritSection AMR Read more on our website!
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#' @examples
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@ -73,6 +73,8 @@
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#'
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#' plot(rsi_data) # for percentages
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#' barplot(rsi_data) # for frequencies
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#'
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#' library(clean)
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#' freq(rsi_data) # frequency table with informative header
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#'
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#' # using dplyr's mutate
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