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dr. M.S. (Matthijs) Berends
2023-01-21 11:47:02 +01:00
parent ee38689172
commit 79c8415d3e
13 changed files with 22 additions and 22 deletions
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2
man/count.Rd
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@@ -67,7 +67,7 @@ The function \code{\link[=count_resistant]{count_resistant()}} is equal to the f
The function \code{\link[=n_sir]{n_sir()}} is an alias of \code{\link[=count_all]{count_all()}}. They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to \code{n_distinct()}. Their function is equal to \code{count_susceptible(...) + count_resistant(...)}.
The function \code{\link[=count_df]{count_df()}} takes any variable from \code{data} that has an \code{\link{sir}} class (created with \code{\link[=as.sir]{as.sir()}}) and counts the number of S's, I's and R's. It also supports grouped variables. The function \code{\link[=sir_sf]{sir_sf()}} works exactly like \code{\link[=count_df]{count_df()}}, but adds the percentage of S, I and R.
The function \code{\link[=count_df]{count_df()}} takes any variable from \code{data} that has an \code{\link{sir}} class (created with \code{\link[=as.sir]{as.sir()}}) and counts the number of S's, I's and R's. It also supports grouped variables. The function \code{\link[=sir_df]{sir_df()}} works exactly like \code{\link[=count_df]{count_df()}}, but adds the percentage of S, I and R.
}
\section{Interpretation of SIR}{

2
man/ggplot_sir.Rd
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@@ -120,7 +120,7 @@ Use these functions to create bar plots for AMR data analysis. All functions rel
At default, the names of antibiotics will be shown on the plots using \code{\link[=ab_name]{ab_name()}}. This can be set with the \code{translate_ab} argument. See \code{\link[=count_df]{count_df()}}.
\subsection{The Functions}{
\code{\link[=geom_sir]{geom_sir()}} will take any variable from the data that has an \code{\link{sir}} class (created with \code{\link[=as.sir]{as.sir()}}) using \code{\link[=sir_sf]{sir_sf()}} and will plot bars with the percentage S, I, and R. The default behaviour is to have the bars stacked and to have the different antibiotics on the x axis.
\code{\link[=geom_sir]{geom_sir()}} will take any variable from the data that has an \code{\link{sir}} class (created with \code{\link[=as.sir]{as.sir()}}) using \code{\link[=sir_df]{sir_df()}} and will plot bars with the percentage S, I, and R. The default behaviour is to have the bars stacked and to have the different antibiotics on the x axis.
\code{\link[=facet_sir]{facet_sir()}} creates 2d plots (at default based on S/I/R) using \code{\link[ggplot2:facet_wrap]{ggplot2::facet_wrap()}}.

10
man/proportion.Rd
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@@ -12,7 +12,7 @@
\alias{proportion_SI}
\alias{proportion_S}
\alias{proportion_df}
\alias{sir_sf}
\alias{sir_df}
\title{Calculate Microbial Resistance}
\source{
\strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 5th Edition}, 2022, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
@@ -52,7 +52,7 @@ proportion_df(
confidence_level = 0.95
)
sir_sf(
sir_df(
data,
translate_ab = "name",
language = get_AMR_locale(),
@@ -102,7 +102,7 @@ Use \code{\link[=sir_confidence_interval]{sir_confidence_interval()}} to calcula
These functions are not meant to count isolates, but to calculate the proportion of resistance/susceptibility. Use the \code{\link[=count]{count()}} functions to count isolates. The function \code{\link[=susceptibility]{susceptibility()}} is essentially equal to \code{count_susceptible() / count_all()}. \emph{Low counts can influence the outcome - the \code{proportion} functions may camouflage this, since they only return the proportion (albeit being dependent on the \code{minimum} argument).}
The function \code{\link[=proportion_df]{proportion_df()}} takes any variable from \code{data} that has an \code{\link{sir}} class (created with \code{\link[=as.sir]{as.sir()}}) and calculates the proportions S, I, and R. It also supports grouped variables. The function \code{\link[=sir_sf]{sir_sf()}} works exactly like \code{\link[=proportion_df]{proportion_df()}}, but adds the number of isolates.
The function \code{\link[=proportion_df]{proportion_df()}} takes any variable from \code{data} that has an \code{\link{sir}} class (created with \code{\link[=as.sir]{as.sir()}}) and calculates the proportions S, I, and R. It also supports grouped variables. The function \code{\link[=sir_df]{sir_df()}} works exactly like \code{\link[=proportion_df]{proportion_df()}}, but adds the number of isolates.
}
\section{Combination Therapy}{
@@ -270,11 +270,11 @@ if (require("dplyr")) {
proportion_df(translate = FALSE)
# It also supports grouping variables
# (use sir_sf to also include the count)
# (use sir_df to also include the count)
example_isolates \%>\%
select(ward, AMX, CIP) \%>\%
group_by(ward) \%>\%
sir_sf(translate = FALSE)
sir_df(translate = FALSE)
}
}
}