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(v2.1.1.9232) is.mic() iteration, documentation cleanup

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dr. M.S. (Matthijs) Berends
2025-03-31 10:51:31 +02:00
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man/resistance_predict.Rd
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@ -26,35 +26,35 @@ ggplot_sir_predict(x, main = paste("Resistance Prediction of", x_name),
main = paste("Resistance Prediction of", x_name), ribbon = TRUE, ...)
}
\arguments{
\item{x}{a \link{data.frame} containing isolates. Can be left blank for automatic determination, see \emph{Examples}.}
\item{x}{A \link{data.frame} containing isolates. Can be left blank for automatic determination, see \emph{Examples}.}
\item{col_ab}{column name of \code{x} containing antimicrobial interpretations (\code{"R"}, \code{"I"} and \code{"S"})}
\item{col_ab}{Column name of \code{x} containing antimicrobial interpretations (\code{"R"}, \code{"I"} and \code{"S"})}
\item{col_date}{column name of the date, will be used to calculate years if this column doesn't consist of years already - the default is the first column of with a date class}
\item{col_date}{Column name of the date, will be used to calculate years if this column doesn't consist of years already - the default is the first column of with a date class}
\item{year_min}{lowest year to use in the prediction model, dafaults to the lowest year in \code{col_date}}
\item{year_min}{Lowest year to use in the prediction model, dafaults to the lowest year in \code{col_date}}
\item{year_max}{highest year to use in the prediction model - the default is 10 years after today}
\item{year_max}{Highest year to use in the prediction model - the default is 10 years after today}
\item{year_every}{unit of sequence between lowest year found in the data and \code{year_max}}
\item{year_every}{Unit of sequence between lowest year found in the data and \code{year_max}}
\item{minimum}{minimal amount of available isolates per year to include. Years containing less observations will be estimated by the model.}
\item{minimum}{Minimal amount of available isolates per year to include. Years containing less observations will be estimated by the model.}
\item{model}{the statistical model of choice. This could be a generalised linear regression model with binomial distribution (i.e. using \code{glm(..., family = binomial)}, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See \emph{Details} for all valid options.}
\item{model}{The statistical model of choice. This could be a generalised linear regression model with binomial distribution (i.e. using \code{glm(..., family = binomial)}, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See \emph{Details} for all valid options.}
\item{I_as_S}{a \link{logical} to indicate whether values \code{"I"} should be treated as \code{"S"} (will otherwise be treated as \code{"R"}). The default, \code{TRUE}, follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section \emph{Interpretation of S, I and R} below.}
\item{I_as_S}{A \link{logical} to indicate whether values \code{"I"} should be treated as \code{"S"} (will otherwise be treated as \code{"R"}). The default, \code{TRUE}, follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section \emph{Interpretation of S, I and R} below.}
\item{preserve_measurements}{a \link{logical} to indicate whether predictions of years that are actually available in the data should be overwritten by the original data. The standard errors of those years will be \code{NA}.}
\item{preserve_measurements}{A \link{logical} to indicate whether predictions of years that are actually available in the data should be overwritten by the original data. The standard errors of those years will be \code{NA}.}
\item{info}{a \link{logical} to indicate whether textual analysis should be printed with the name and \code{\link[=summary]{summary()}} of the statistical model.}
\item{info}{A \link{logical} to indicate whether textual analysis should be printed with the name and \code{\link[=summary]{summary()}} of the statistical model.}
\item{...}{arguments passed on to functions}
\item{...}{Arguments passed on to functions}
\item{main}{title of the plot}
\item{main}{Title of the plot}
\item{ribbon}{a \link{logical} to indicate whether a ribbon should be shown (default) or error bars}
\item{ribbon}{A \link{logical} to indicate whether a ribbon should be shown (default) or error bars}
\item{object}{model data to be plotted}
\item{object}{Model data to be plotted}
}
\value{
A \link{data.frame} with extra class \code{\link{resistance_predict}} with columns: