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@ -7,15 +7,15 @@
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\alias{ggplot_rsi_predict}
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\title{Predict antimicrobial resistance}
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\usage{
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resistance_predict(tbl, col_ab, col_date = NULL, year_min = NULL,
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resistance_predict(x, col_ab, col_date = NULL, year_min = NULL,
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year_max = NULL, year_every = 1, minimum = 30,
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model = "binomial", I_as_R = TRUE, preserve_measurements = TRUE,
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info = TRUE)
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model = "binomial", I_as_S = TRUE, preserve_measurements = TRUE,
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info = TRUE, ...)
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rsi_predict(tbl, col_ab, col_date = NULL, year_min = NULL,
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rsi_predict(x, col_ab, col_date = NULL, year_min = NULL,
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year_max = NULL, year_every = 1, minimum = 30,
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model = "binomial", I_as_R = TRUE, preserve_measurements = TRUE,
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info = TRUE)
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model = "binomial", I_as_S = TRUE, preserve_measurements = TRUE,
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info = TRUE, ...)
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\method{plot}{resistance_predict}(x,
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main = paste("Resistance prediction of", attributes(x)$ab), ...)
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@ -24,7 +24,9 @@ ggplot_rsi_predict(x, main = paste("Resistance prediction of",
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attributes(x)$ab), ribbon = TRUE, ...)
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}
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\arguments{
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\item{col_ab}{column name of \code{tbl} with antimicrobial interpretations (\code{R}, \code{I} and \code{S})}
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\item{x}{a \code{data.frame} containing isolates.}
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\item{col_ab}{column name of \code{x} with antimicrobial interpretations (\code{R}, \code{I} and \code{S})}
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\item{col_date}{column name of the date, will be used to calculate years if this column doesn't consist of years already, defaults to the first column of with a date class}
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@ -38,18 +40,16 @@ ggplot_rsi_predict(x, main = paste("Resistance prediction of",
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\item{model}{the statistical model of choice. Defaults to a generalised linear regression model with binomial distribution, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See Details for valid options.}
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\item{I_as_R}{a logical to indicate whether values \code{I} should be treated as \code{R}}
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\item{I_as_S}{a logical to indicate whether values \code{I} should be treated as \code{S}}
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\item{preserve_measurements}{a 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}.}
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\item{info}{a logical to indicate whether textual analysis should be printed with the name and \code{\link{summary}} of the statistical model.}
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\item{x}{a \code{data.frame} containing isolates.}
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\item{...}{parameters passed on to functions}
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\item{main}{title of the plot}
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\item{...}{parameters passed on to the \code{first_isolate} function}
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\item{ribbon}{a logical to indicate whether a ribbon should be shown (default) or error bars}
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}
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\value{
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