* Additional way to calculate co-resistance, i.e. when using multiple antibiotics as input for `portion_*` functions or `count_*` functions. This can be used to determine the empiric susceptibily of a combination therapy. A new parameter `only_all_tested` replaces the old `also_single_tested` and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the `portion` and `count` help pages), where the %SI is being determined:
* Additional way to calculate co-resistance, i.e. when using multiple antibiotics as input for `portion_*` functions or `count_*` functions. This can be used to determine the empiric susceptibily of a combination therapy. A new parameter `only_all_tested`(**which defaults to `FALSE`**) replaces the old `also_single_tested` and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the `portion` and `count` help pages), where the %SI is being determined:
#' @inheritSection as.rsi Interpretation of S, I and R
#' @details \strong{Remember that you should filter your table to let it contain only first isolates!} This is needed to exclude duplicates and to reduce selection bias. Use \code{\link{first_isolate}} to determine them in your data set.
#'
#' These functions are not meant to count isolates, but to calculate the portion of resistance/susceptibility. Use the \code{\link[AMR]{count}} functions to count isolates. \emph{Low counts can infuence the outcome - these \code{portion} functions may camouflage this, since they only return the portion albeit being dependent on the \code{minimum} parameter.}
#' These functions are not meant to count isolates, but to calculate the portion of resistance/susceptibility. Use the \code{\link[AMR]{count}} functions to count isolates. The function \code{portion_SI()} is essentially equal to \code{count_SI() / count_all()}. \emph{Low counts can infuence the outcome - the \code{portion} functions may camouflage this, since they only return the portion (albeit being dependent on the \code{minimum} parameter).}
#'
#' The function \code{portion_df} takes any variable from \code{data} that has an \code{"rsi"} class (created with \code{\link{as.rsi}}) and calculates the portions R, I and S. The resulting \emph{tidy data} (see Source) \code{data.frame} will have three rows (S/I/R) and a column for each group and each variable with class \code{"rsi"}.
<p>Additional way to calculate co-resistance, i.e.when using multiple antibiotics as input for <code>portion_*</code> functions or <code>count_*</code> functions. This can be used to determine the empiric susceptibily of a combination therapy. A new parameter <code>only_all_tested</code> replaces the old <code>also_single_tested</code> and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the <code>portion</code> and <code>count</code> help pages), where the %SI is being determined:</p>
<p>Additional way to calculate co-resistance, i.e.when using multiple antibiotics as input for <code>portion_*</code> functions or <code>count_*</code> functions. This can be used to determine the empiric susceptibily of a combination therapy. A new parameter <code>only_all_tested</code>(<strong>which defaults to <code>FALSE</code></strong>) replaces the old <code>also_single_tested</code> and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the <code>portion</code> and <code>count</code> help pages), where the %SI is being determined:</p>
@ -81,7 +81,7 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
@@ -81,7 +81,7 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
@ -81,7 +81,7 @@ portion_R and portion_IR can be used to calculate resistance, portion_S and port
@@ -81,7 +81,7 @@ portion_R and portion_IR can be used to calculate resistance, portion_S and port
<spanclass="version label label-default"data-toggle="tooltip"data-placement="bottom"title="Latest development version">0.7.1.9005</span>
<spanclass="version label label-default"data-toggle="tooltip"data-placement="bottom"title="Latest development version">0.7.1.9006</span>
</span>
</div>
@ -319,7 +319,7 @@ portion_R and portion_IR can be used to calculate resistance, portion_S and port
@@ -319,7 +319,7 @@ portion_R and portion_IR can be used to calculate resistance, portion_S and port
<p><strong>Remember that you should filter your table to let it contain only first isolates!</strong> This is needed to exclude duplicates and to reduce selection bias. Use <code><ahref='first_isolate.html'>first_isolate</a></code> to determine them in your data set.</p>
<p>These functions are not meant to count isolates, but to calculate the portion of resistance/susceptibility. Use the <code><ahref='count.html'>count</a></code> functions to count isolates. <em>Low counts can infuence the outcome - these<code>portion</code> functions may camouflage this, since they only return the portion albeit being dependent on the <code>minimum</code> parameter.</em></p>
<p>These functions are not meant to count isolates, but to calculate the portion of resistance/susceptibility. Use the <code><ahref='count.html'>count</a></code> functions to count isolates. The function <code>portion_SI()</code> is essentially equal to <code>count_SI() / count_all()</code>. <em>Low counts can infuence the outcome - the <code>portion</code> functions may camouflage this, since they only return the portion (albeit being dependent on the <code>minimum</code> parameter).</em></p>
<p>The function <code>portion_df</code> takes any variable from <code>data</code> that has an <code>"rsi"</code> class (created with <code><ahref='as.rsi.html'>as.rsi</a></code>) and calculates the portions R, I and S. The resulting <em>tidy data</em> (see Source) <code>data.frame</code> will have three rows (S/I/R) and a column for each group and each variable with class <code>"rsi"</code>.</p>
<p>The function <code>rsi_df</code> works exactly like <code>portion_df</code>, but adds the number of isolates.</p>
@ -352,10 +352,10 @@ not tested R - - - -
@@ -352,10 +352,10 @@ not tested R - - - -
@ -145,6 +145,7 @@ On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://
@@ -145,6 +145,7 @@ On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://
}
\examples{
\donttest{
# These examples all return "B_STPHY_AUR", the ID of S. aureus:
as.mo("sau") # WHONET code
as.mo("stau")
@ -179,7 +180,7 @@ as.mo("S. pyogenes", Lancefield = TRUE) # will not remain species: B_STRPT_GRA
@@ -179,7 +180,7 @@ as.mo("S. pyogenes", Lancefield = TRUE) # will not remain species: B_STRPT_GRA
# All mo_* functions use as.mo() internally too (see ?mo_property):
@ -69,7 +69,7 @@ These functions can be used to calculate the (co-)resistance of microbial isolat
@@ -69,7 +69,7 @@ These functions can be used to calculate the (co-)resistance of microbial isolat
\details{
\strong{Remember that you should filter your table to let it contain only first isolates!} This is needed to exclude duplicates and to reduce selection bias. Use \code{\link{first_isolate}} to determine them in your data set.
These functions are not meant to count isolates, but to calculate the portion of resistance/susceptibility. Use the \code{\link[AMR]{count}} functions to count isolates. \emph{Low counts can infuence the outcome - these \code{portion} functions may camouflage this, since they only return the portion albeit being dependent on the \code{minimum} parameter.}
These functions are not meant to count isolates, but to calculate the portion of resistance/susceptibility. Use the \code{\link[AMR]{count}} functions to count isolates. The function \code{portion_SI()} is essentially equal to \code{count_SI() / count_all()}. \emph{Low counts can infuence the outcome - the \code{portion} functions may camouflage this, since they only return the portion (albeit being dependent on the \code{minimum} parameter).}
The function \code{portion_df} takes any variable from \code{data} that has an \code{"rsi"} class (created with \code{\link{as.rsi}}) and calculates the portions R, I and S. The resulting \emph{tidy data} (see Source) \code{data.frame} will have three rows (S/I/R) and a column for each group and each variable with class \code{"rsi"}.
@ -105,12 +105,12 @@ not tested not tested - - - -
@@ -105,12 +105,12 @@ not tested not tested - - - -
