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(v2.1.1.9232) is.mic() iteration, documentation cleanup
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@ -44,9 +44,9 @@ retrieve_wisca_parameters(wisca_model, ...)
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na = getOption("knitr.kable.NA", default = ""), ...)
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}
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\arguments{
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\item{x}{a \link{data.frame} containing at least a column with microorganisms and columns with antimicrobial results (class 'sir', see \code{\link[=as.sir]{as.sir()}})}
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\item{x}{A \link{data.frame} containing at least a column with microorganisms and columns with antimicrobial results (class 'sir', see \code{\link[=as.sir]{as.sir()}})}
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\item{antimicrobials}{a vector specifying the antimicrobials to include in the antibiogram (see \emph{Examples}). Will be evaluated using \code{\link[=guess_ab_col]{guess_ab_col()}}. This can be:
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\item{antimicrobials}{A vector specifying the antimicrobials to include in the antibiogram (see \emph{Examples}). Will be evaluated using \code{\link[=guess_ab_col]{guess_ab_col()}}. This can be:
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\itemize{
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\item Any antimicrobial name or code
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\item A column name in \code{x} that contains SIR values
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@ -67,49 +67,49 @@ retrieve_wisca_parameters(wisca_model, ...)
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}
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}}
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\item{mo_transform}{a character to transform microorganism input - must be \code{"name"}, \code{"shortname"} (default), \code{"gramstain"}, or one of the column names of the \link{microorganisms} data set: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "oxygen_tolerance", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "mycobank", "mycobank_parent", "mycobank_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence", or "snomed". Can also be \code{NULL} to not transform the input or \code{NA} to consider all microorganisms 'unknown'.}
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\item{mo_transform}{A character to transform microorganism input - must be \code{"name"}, \code{"shortname"} (default), \code{"gramstain"}, or one of the column names of the \link{microorganisms} data set: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "oxygen_tolerance", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "mycobank", "mycobank_parent", "mycobank_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence", or "snomed". Can also be \code{NULL} to not transform the input or \code{NA} to consider all microorganisms 'unknown'.}
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\item{ab_transform}{a character to transform antimicrobial input - must be one of the column names of the \link{antimicrobials} data set (defaults to \code{"name"}): "ab", "cid", "name", "group", "atc", "atc_group1", "atc_group2", "abbreviations", "synonyms", "oral_ddd", "oral_units", "iv_ddd", "iv_units", or "loinc". Can also be \code{NULL} to not transform the input.}
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\item{ab_transform}{A character to transform antimicrobial input - must be one of the column names of the \link{antimicrobials} data set (defaults to \code{"name"}): "ab", "cid", "name", "group", "atc", "atc_group1", "atc_group2", "abbreviations", "synonyms", "oral_ddd", "oral_units", "iv_ddd", "iv_units", or "loinc". Can also be \code{NULL} to not transform the input.}
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\item{syndromic_group}{a column name of \code{x}, or values calculated to split rows of \code{x}, e.g. by using \code{\link[=ifelse]{ifelse()}} or \code{\link[dplyr:case_when]{case_when()}}. See \emph{Examples}.}
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\item{syndromic_group}{A column name of \code{x}, or values calculated to split rows of \code{x}, e.g. by using \code{\link[=ifelse]{ifelse()}} or \code{\link[dplyr:case_when]{case_when()}}. See \emph{Examples}.}
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\item{add_total_n}{a \link{logical} to indicate whether \code{n_tested} available numbers per pathogen should be added to the table (default is \code{TRUE}). This will add the lowest and highest number of available isolates per antimicrobial (e.g, if for \emph{E. coli} 200 isolates are available for ciprofloxacin and 150 for amoxicillin, the returned number will be "150-200"). This option is unavailable when \code{wisca = TRUE}; in that case, use \code{\link[=retrieve_wisca_parameters]{retrieve_wisca_parameters()}} to get the parameters used for WISCA.}
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\item{add_total_n}{A \link{logical} to indicate whether \code{n_tested} available numbers per pathogen should be added to the table (default is \code{TRUE}). This will add the lowest and highest number of available isolates per antimicrobial (e.g, if for \emph{E. coli} 200 isolates are available for ciprofloxacin and 150 for amoxicillin, the returned number will be "150-200"). This option is unavailable when \code{wisca = TRUE}; in that case, use \code{\link[=retrieve_wisca_parameters]{retrieve_wisca_parameters()}} to get the parameters used for WISCA.}
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\item{only_all_tested}{(for combination antibiograms): a \link{logical} to indicate that isolates must be tested for all antimicrobials, see \emph{Details}}
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\item{digits}{number of digits to use for rounding the antimicrobial coverage, defaults to 1 for WISCA and 0 otherwise}
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\item{digits}{Number of digits to use for rounding the antimicrobial coverage, defaults to 1 for WISCA and 0 otherwise}
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\item{formatting_type}{numeric value (1–22 for WISCA, 1-12 for non-WISCA) indicating how the 'cells' of the antibiogram table should be formatted. See \emph{Details} > \emph{Formatting Type} for a list of options.}
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\item{formatting_type}{Numeric value (1–22 for WISCA, 1-12 for non-WISCA) indicating how the 'cells' of the antibiogram table should be formatted. See \emph{Details} > \emph{Formatting Type} for a list of options.}
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\item{col_mo}{column name of the names or codes of the microorganisms (see \code{\link[=as.mo]{as.mo()}}) - the default is the first column of class \code{\link{mo}}. Values will be coerced using \code{\link[=as.mo]{as.mo()}}.}
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\item{col_mo}{Column name of the names or codes of the microorganisms (see \code{\link[=as.mo]{as.mo()}}) - the default is the first column of class \code{\link{mo}}. Values will be coerced using \code{\link[=as.mo]{as.mo()}}.}
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\item{language}{language to translate text, which defaults to the system language (see \code{\link[=get_AMR_locale]{get_AMR_locale()}})}
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\item{language}{Language to translate text, which defaults to the system language (see \code{\link[=get_AMR_locale]{get_AMR_locale()}})}
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\item{minimum}{the minimum allowed number of available (tested) isolates. Any isolate count lower than \code{minimum} will return \code{NA} with a warning. The default number of \code{30} isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see \emph{Source}.}
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\item{minimum}{The minimum allowed number of available (tested) isolates. Any isolate count lower than \code{minimum} will return \code{NA} with a warning. The default number of \code{30} isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see \emph{Source}.}
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\item{combine_SI}{a \link{logical} to indicate whether all susceptibility should be determined by results of either S, SDD, or I, instead of only S (default is \code{TRUE})}
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\item{combine_SI}{A \link{logical} to indicate whether all susceptibility should be determined by results of either S, SDD, or I, instead of only S (default is \code{TRUE})}
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\item{sep}{a separating character for antimicrobial columns in combination antibiograms}
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\item{sep}{A separating character for antimicrobial columns in combination antibiograms}
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\item{wisca}{a \link{logical} to indicate whether a Weighted-Incidence Syndromic Combination Antibiogram (WISCA) must be generated (default is \code{FALSE}). This will use a Bayesian decision model to estimate regimen coverage probabilities using \href{https://en.wikipedia.org/wiki/Monte_Carlo_method}{Monte Carlo simulations}. Set \code{simulations}, \code{conf_interval}, and \code{interval_side} to adjust.}
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\item{wisca}{A \link{logical} to indicate whether a Weighted-Incidence Syndromic Combination Antibiogram (WISCA) must be generated (default is \code{FALSE}). This will use a Bayesian decision model to estimate regimen coverage probabilities using \href{https://en.wikipedia.org/wiki/Monte_Carlo_method}{Monte Carlo simulations}. Set \code{simulations}, \code{conf_interval}, and \code{interval_side} to adjust.}
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\item{simulations}{(for WISCA) a numerical value to set the number of Monte Carlo simulations}
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\item{conf_interval}{a numerical value to set confidence interval (default is \code{0.95})}
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\item{conf_interval}{A numerical value to set confidence interval (default is \code{0.95})}
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\item{interval_side}{the side of the confidence interval, either \code{"two-tailed"} (default), \code{"left"} or \code{"right"}}
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\item{interval_side}{The side of the confidence interval, either \code{"two-tailed"} (default), \code{"left"} or \code{"right"}}
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\item{info}{a \link{logical} to indicate info should be printed - the default is \code{TRUE} only in interactive mode}
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\item{info}{A \link{logical} to indicate info should be printed - the default is \code{TRUE} only in interactive mode}
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\item{...}{when used in \link[knitr:kable]{R Markdown or Quarto}: arguments passed on to \code{\link[knitr:kable]{knitr::kable()}} (otherwise, has no use)}
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\item{...}{When used in \link[knitr:kable]{R Markdown or Quarto}: arguments passed on to \code{\link[knitr:kable]{knitr::kable()}} (otherwise, has no use)}
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\item{wisca_model}{the outcome of \code{\link[=wisca]{wisca()}} or \code{\link[=antibiogram]{antibiogram(..., wisca = TRUE)}}}
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\item{wisca_model}{The outcome of \code{\link[=wisca]{wisca()}} or \code{\link[=antibiogram]{antibiogram(..., wisca = TRUE)}}}
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\item{object}{an \code{\link[=antibiogram]{antibiogram()}} object}
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\item{object}{An \code{\link[=antibiogram]{antibiogram()}} object}
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\item{italicise}{a \link{logical} to indicate whether the microorganism names in the \link[knitr:kable]{knitr} table should be made italic, using \code{\link[=italicise_taxonomy]{italicise_taxonomy()}}.}
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\item{italicise}{A \link{logical} to indicate whether the microorganism names in the \link[knitr:kable]{knitr} table should be made italic, using \code{\link[=italicise_taxonomy]{italicise_taxonomy()}}.}
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\item{na}{character to use for showing \code{NA} values}
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\item{na}{Character to use for showing \code{NA} values}
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}
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\description{
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Create detailed antibiograms with options for traditional, combination, syndromic, and Bayesian WISCA methods.
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