* Function `freq()` has moved to a new package, [`clean`](https://github.com/msberends/clean) ([CRAN link](https://cran.r-project.org/package=clean)). The `freq()` function still works, since it is re-exported from the `clean` package to this `AMR` package. Creating frequency tables is actually not the scope of this package (never was) and this function has matured a lot over the last two years. Therefore, a new package was created for data cleaning and checking and it perfectly fits the `freq()` function. The [`clean`](https://github.com/msberends/clean) package is available on CRAN and will be installed automatically when updating the `AMR` package, that now imports it. In a later stage, the `skewness()` and `kurtosis()` functions will be moved to the `clean` package too.
* Determination of first isolates now **excludes** all 'unknown' microorganisms at default, i.e. microbial code `"UNKNOWN"`. They can be included with the new parameter `include_unknown`:
```r
first_isolate(..., include_unknown = TRUE)
```
For WHONET users, this means that all records with organism code `"con"` (*contamination*) will be excluded at default, since `as.mo("con") = "UNKNOWN"`. The function always shows a note with the number of 'unknown' microorganisms that were included or excluded.
For WHONET users, this means that all records/isolates with organism code `"con"` (*contamination*) will be excluded at default, since `as.mo("con") = "UNKNOWN"`. The function always shows a note with the number of 'unknown' microorganisms that were included or excluded.
* For code consistency, classes `ab` and `mo` will now be preserved in any subsetting or assignment. For the sake of data integrity, this means that invalid assignments will now result in `NA`:
```r
# how it works in base R:
x <-factor("A")
x[1] <-"B"
#> Warning message:
#> invalid factor level, NA generated
# how it now works similarly for classes 'mo' and 'ab':
x <-as.mo("E.coli")
x[1] <-"testvalue"
#> Warning message:
#> invalid microbial code, NA generated
```
This is important, because a value like `"testvalue"` could never be understood by e.g. `mo_name()`, although the class would suggest a valid microbial code.
* Function `freq()` has moved to a new package, [`clean`](https://github.com/msberends/clean) ([CRAN link](https://cran.r-project.org/package=clean)), since creating frequency tables actually does not fit the scope of this package. The `freq()` function still works, since it is re-exported from the `clean` package (which will be installed automatically upon updating this `AMR` package).
### New
* Function `bug_drug_combinations()` to quickly get a `data.frame` with the antimicrobial resistance of any bug-drug combination in a data set:
@ -24,35 +39,36 @@
```r
format(x)
```
* 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:
* Additional way to calculate co-resistance, i.e. when using multiple antimicrobials 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:
Since this is a major change, usage of the old `also_single_tested` will throw an informative error that it has been replaced by `only_all_tested`.
* `tibble` printing support for classes `rsi`, `mic`, `disk`, `ab``mo`. When using `tibble`s containing antimicrobial columns, values `S` will print in green, values `I` will print in yellow and values `R` will print in red. Microbial IDs (class `mo`) will emphasise on the genus and species, not on the kingdom.
```r
# (run this on your own console, as this page does not support colour printing)
library(dplyr)
septic_patients %>%
select(mo:AMC) %>%
as_tibble()
```
### Changed
* Function: `eucast_rules()`
@ -62,14 +78,6 @@
* Using Verbose mode (i.e. `eucast_rules(..., verbose = TRUE)`) returns more informative and readable output
* Using factors as input now adds missing factors levels when the function changes antibiotic results
* Improved the internal auto-guessing function for determining antibiotics in your data set (`AMR:::get_column_abx()`)
* Added tibble printing support for classes `rsi`, `mic`, `disk`, `ab``mo`. When using tibbles containing antibiotic columns, values `S` will print in green, values `I` will print in yellow and values `R` will print in red. Microbial IDs (class `mo`) will emphasise on the genus and species, not on the kingdom.
```r
# (run this on your own console, as this page does not support colour printing)
library(dplyr)
septic_patients %>%
select(mo:AMC) %>%
as_tibble()
```
* Removed class `atc` - using `as.atc()` is now deprecated in favour of `ab_atc()` and this will return a character, not the `atc` class anymore
#' When using more than one variable for \code{...} (= combination therapy)), use \code{only_all_tested} to only count isolates that are tested for all antibiotics/variables that you test them for. See this example for two antibiotics, Antibiotic A and Antibiotic B, about how \code{portion_SI} works to calculate the \%SI:
<li>Function <code><ahref="https://www.rdocumentation.org/packages/clean/topics/freq">freq()</a></code> has moved to a new package, <ahref="https://github.com/msberends/clean"><code>clean</code></a> (<ahref="https://cran.r-project.org/package=clean">CRAN link</a>). The <code><ahref="https://www.rdocumentation.org/packages/clean/topics/freq">freq()</a></code> function still works, since it is re-exported from the <code>clean</code> package to this <code>AMR</code> package. Creating frequency tables is actually not the scope of this package (never was) and this function has matured a lot over the last two years. Therefore, a new package was created for data cleaning and checking and it perfectly fits the <code><ahref="https://www.rdocumentation.org/packages/clean/topics/freq">freq()</a></code> function. The <ahref="https://github.com/msberends/clean"><code>clean</code></a> package is available on CRAN and will be installed automatically when updating the <code>AMR</code> package, that now imports it. In a later stage, the <code><ahref="../reference/skewness.html">skewness()</a></code> and <code><ahref="../reference/kurtosis.html">kurtosis()</a></code> functions will be moved to the <code>clean</code> package too.</li>
<li>
<p>Determination of first isolates now <strong>excludes</strong> all ‘unknown’ microorganisms at default, i.e.microbial code <code>"UNKNOWN"</code>. They can be included with the new parameter <code>include_unknown</code>:</p>
<p>For WHONET users, this means that all records with organism code <code>"con"</code> (<em>contamination</em>) will be excluded at default, since <code>as.mo("con") = "UNKNOWN"</code>. The function always shows a note with the number of ‘unknown’ microorganisms that were included or excluded.</p>
</li>
For WHONET users, this means that all records/isolates with organism code <code>"con"</code> (<em>contamination</em>) will be excluded at default, since <code>as.mo("con") = "UNKNOWN"</code>. The function always shows a note with the number of ‘unknown’ microorganisms that were included or excluded.</li>
<li>
<p>For code consistency, classes <code>ab</code> and <code>mo</code> will now be preserved in any subsetting or assignment. For the sake of data integrity, this means that invalid assignments will now result in <code>NA</code>:</p>
<divclass="sourceCode"id="cb2"><preclass="sourceCode r"><codeclass="sourceCode r"><aclass="sourceLine"id="cb2-1"data-line-number="1"><spanclass="co"># how it works in base R:</span></a>
<aclass="sourceLine"id="cb2-11"data-line-number="11"><spanclass="co">#> invalid microbial code, NA generated</span></a></code></pre></div>
This is important, because a value like <code>"testvalue"</code> could never be understood by e.g. <code><ahref="../reference/mo_property.html">mo_name()</a></code>, although the class would suggest a valid microbial code.</li>
<li><p>Function <code><ahref="https://www.rdocumentation.org/packages/clean/topics/freq">freq()</a></code> has moved to a new package, <ahref="https://github.com/msberends/clean"><code>clean</code></a> (<ahref="https://cran.r-project.org/package=clean">CRAN link</a>), since creating frequency tables actually does not fit the scope of this package. The <code><ahref="https://www.rdocumentation.org/packages/clean/topics/freq">freq()</a></code> function still works, since it is re-exported from the <code>clean</code> package (which will be installed automatically upon updating this <code>AMR</code> package).</p></li>
</ul>
</div>
<divid="new"class="section level3">
@ -247,43 +260,43 @@
<ul>
<li>
<p>Function <code><ahref="../reference/bug_drug_combinations.html">bug_drug_combinations()</a></code> to quickly get a <code>data.frame</code> with the antimicrobial resistance of any bug-drug combination in a data set:</p>
<p>You can format this to a printable format, ready for reporting or exporting to e.g.Excel with the base R <code><ahref="https://www.rdocumentation.org/packages/base/topics/format">format()</a></code> function:</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>
<p>Since this is a major change, usage of the old <code>also_single_tested</code> will throw an informative error that it has been replaced by <code>only_all_tested</code>.</p>
<p>Additional way to calculate co-resistance, i.e.when using multiple antimicrobials 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>
Since this is a major change, usage of the old <code>also_single_tested</code> will throw an informative error that it has been replaced by <code>only_all_tested</code>.</li>
<li>
<p><code>tibble</code> printing support for classes <code>rsi</code>, <code>mic</code>, <code>disk</code>, <code>ab</code><code>mo</code>. When using <code>tibble</code>s containing antimicrobial columns, values <code>S</code> will print in green, values <code>I</code> will print in yellow and values <code>R</code> will print in red. Microbial IDs (class <code>mo</code>) will emphasise on the genus and species, not on the kingdom.</p>
<divclass="sourceCode"id="cb6"><preclass="sourceCode r"><codeclass="sourceCode r"><aclass="sourceLine"id="cb6-1" data-line-number="1"><spanclass="co"># (run this on your own console, as this page does not support colour printing)</span></a>
<li>Improved the internal auto-guessing function for determining antibiotics in your data set (<code>AMR:::get_column_abx()</code>)</li>
<li>
<p>Added tibble printing support for classes <code>rsi</code>, <code>mic</code>, <code>disk</code>, <code>ab</code><code>mo</code>. When using tibbles containing antibiotic columns, values <code>S</code> will print in green, values <code>I</code> will print in yellow and values <code>R</code> will print in red. Microbial IDs (class <code>mo</code>) will emphasise on the genus and species, not on the kingdom.</p>
<divclass="sourceCode"id="cb5"><preclass="sourceCode r"><codeclass="sourceCode r"><aclass="sourceLine"id="cb5-1"data-line-number="1"><spanclass="co"># (run this on your own console, as this page does not support colour printing)</span></a>
<li>Removed class <code>atc</code> - using <code><ahref="../reference/AMR-deprecated.html">as.atc()</a></code> is now deprecated in favour of <code><ahref="../reference/ab_property.html">ab_atc()</a></code> and this will return a character, not the <code>atc</code> class anymore</li>
<li>The <code>antibiotics</code> data set is now sorted by name and all cephalosporins now have their generation between brackets</li>
<li>Speed improvement for <code><ahref="../reference/guess_ab_col.html">guess_ab_col()</a></code> which is now 30 times faster for antibiotic abbreviations</li>
<li>Improved <code><ahref="../reference/filter_ab_class.html">filter_ab_class()</a></code> to be more reliable and to support 5th generation cephalosporins</li>
<li>Classes <code>ab</code> and <code>mo</code> will now be preserved in any subsetting</li>
<li><p>Function <code><ahref="../reference/availability.html">availability()</a></code> now uses <code><ahref="../reference/portion.html">portion_R()</a></code> instead of <code><ahref="../reference/portion.html">portion_IR()</a></code>, to comply with EUCAST insights</p></li>
<li>Function <code><ahref="../reference/availability.html">availability()</a></code> now uses <code><ahref="../reference/portion.html">portion_R()</a></code> instead of <code><ahref="../reference/portion.html">portion_IR()</a></code>, to comply with EUCAST insights</li>
</ul>
<divid="other"class="section level4">
<h4class="hasAnchor">
@ -353,14 +357,14 @@
<ul>
<li>
<p>Function <code><ahref="../reference/portion.html">rsi_df()</a></code> to transform a <code>data.frame</code> to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions <code><ahref="../reference/count.html">count_df()</a></code> and <code><ahref="../reference/portion.html">portion_df()</a></code> to immediately show resistance percentages and number of available isolates:</p>
<li>Function <code><ahref="../reference/mo_property.html">mo_info()</a></code> as an analogy to <code><ahref="../reference/ab_property.html">ab_info()</a></code>. The <code><ahref="../reference/mo_property.html">mo_info()</a></code> prints a list with the full taxonomy, authors, and the URL to the online database of a microorganism</li>
<li><p>Function <code><ahref="../reference/mo_property.html">mo_synonyms()</a></code> to get all previously accepted taxonomic names of a microorganism</p></li>
<p>The <code>antibiotics</code> data set will be searched, after which the input data will be checked for column names with a value in any abbreviations, codes or official names found in the <code>antibiotics</code> data set. For example:</p>
<aclass="sourceLine"id="cb10-2" data-line-number="2"><spanclass="co"># Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R</span></a>
<aclass="sourceLine"id="cb10-4" data-line-number="4"><spanclass="co"># Filtering on glycopeptide antibacterials: all of `vanc` and `teic` is R</span></a></code></pre></div>
<aclass="sourceLine"id="cb11-2" data-line-number="2"><spanclass="co"># Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R</span></a>
<aclass="sourceLine"id="cb11-4" data-line-number="4"><spanclass="co"># Filtering on glycopeptide antibacterials: all of `vanc` and `teic` is R</span></a></code></pre></div>
</li>
<li>
<p>All <code>ab_*</code> functions are deprecated and replaced by <code>atc_*</code> functions:</p>
These functions use <code><ahref="../reference/AMR-deprecated.html">as.atc()</a></code> internally. The old <code>atc_property</code> has been renamed <code><ahref="../reference/atc_online.html">atc_online_property()</a></code>. This is done for two reasons: firstly, not all ATC codes are of antibiotics (ab) but can also be of antivirals or antifungals. Secondly, the input must have class <code>atc</code> or must be coerable to this class. Properties of these classes should start with the same class name, analogous to <code><ahref="../reference/as.mo.html">as.mo()</a></code> and e.g. <code>mo_genus</code>.</li>
<li>New functions <code><ahref="../reference/mo_source.html">set_mo_source()</a></code> and <code><ahref="../reference/mo_source.html">get_mo_source()</a></code> to use your own predefined MO codes as input for <code><ahref="../reference/as.mo.html">as.mo()</a></code> and consequently all <code>mo_*</code> functions</li>
<li>Support for the upcoming <ahref="https://dplyr.tidyverse.org"><code>dplyr</code></a> version 0.8.0</li>
@ -611,20 +615,20 @@ These functions use <code><a href="../reference/AMR-deprecated.html">as.atc()</a
<li>New function <code><ahref="../reference/age_groups.html">age_groups()</a></code> to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.</li>
<li>
<p>New function <code><ahref="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> as well as the base R <code><ahref="https://www.rdocumentation.org/packages/graphics/topics/plot">plot()</a></code> function can now be used for resistance prediction calculated with <code><ahref="../reference/resistance_predict.html">resistance_predict()</a></code>:</p>
<p>Functions <code><ahref="../reference/first_isolate.html">filter_first_isolate()</a></code> and <code><ahref="../reference/first_isolate.html">filter_first_weighted_isolate()</a></code> to shorten and fasten filtering on data sets with antimicrobial results, e.g.:</p>
<li>New function <code><ahref="../reference/availability.html">availability()</a></code> to check the number of available (non-empty) results in a <code>data.frame</code>
</li>
@ -653,33 +657,33 @@ These functions use <code><a href="../reference/AMR-deprecated.html">as.atc()</a
<ul>
<li>
<p>Now handles incorrect spelling, like <code>i</code> instead of <code>y</code> and <code>f</code> instead of <code>ph</code>:</p>
<p>Uncertainty of the algorithm is now divided into four levels, 0 to 3, where the default <code>allow_uncertain = TRUE</code> is equal to uncertainty level 2. Run <code><ahref="../reference/as.mo.html">?as.mo</a></code> for more info about these levels.</p>
Using <code><ahref="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a></code> could lead to very unreliable results.</li>
<li>Implemented the latest publication of Becker <em>et al.</em> (2019), for categorising coagulase-negative <em>Staphylococci</em>
</li>
<li>All microbial IDs that found are now saved to a local file <code>~/.Rhistory_mo</code>. Use the new function <code>clean_mo_history()</code> to delete this file, which resets the algorithms.</li>
<li>
<p>Incoercible results will now be considered ‘unknown’, MO code <code>UNKNOWN</code>. On foreign systems, properties of these will be translated to all languages already previously supported: German, Dutch, French, Italian, Spanish and Portuguese:</p>
<aclass="sourceLine"id="cb17-3" data-line-number="3"><spanclass="co"># one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.</span></a>
<aclass="sourceLine"id="cb18-3" data-line-number="3"><spanclass="co"># one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.</span></a>
<li>Fix for vector containing only empty values</li>
<li>Finds better results when input is in other languages</li>
@ -725,19 +729,19 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<ul>
<li>
<p>Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:</p>
<divclass="sourceCode"id="cb18"><preclass="sourceCode r"><codeclass="sourceCode r"><aclass="sourceLine"id="cb18-1" data-line-number="1"><spanclass="co"># Determine genus of microorganisms (mo) in `septic_patients` data set:</span></a>
<aclass="sourceLine"id="cb18-2" data-line-number="2"><spanclass="co"># OLD WAY</span></a>
<divclass="sourceCode"id="cb19"><preclass="sourceCode r"><codeclass="sourceCode r"><aclass="sourceLine"id="cb19-1" data-line-number="1"><spanclass="co"># Determine genus of microorganisms (mo) in `septic_patients` data set:</span></a>
<aclass="sourceLine"id="cb19-2" data-line-number="2"><spanclass="co"># OLD WAY</span></a>
<li>Added parameter <code>combine_IR</code> (TRUE/FALSE) to functions <code>portion_df</code> and <code>count_df</code>, to indicate that all values of I and R must be merged into one, so the output only consists of S vs.IR (susceptible vs.non-susceptible)</li>
<li>Fix for <code>portion_*(..., as_percent = TRUE)</code> when minimal number of isolates would not be met</li>
@ -828,15 +832,15 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<aclass="sourceLine"id="cb21-3" data-line-number="3"><spanclass="st"></span><spanclass="kw"><ahref="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<spanclass="op">-</span>count, <spanclass="op">-</span>cum_count) <spanclass="co"># only get item, percent, cum_percent</span></a></code></pre></div>
<aclass="sourceLine"id="cb22-3" data-line-number="3"><spanclass="st"></span><spanclass="kw"><ahref="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<spanclass="op">-</span>count, <spanclass="op">-</span>cum_count) <spanclass="co"># only get item, percent, cum_percent</span></a></code></pre></div>
</li>
<li>Check for <code><ahref="https://www.rdocumentation.org/packages/hms/topics/Deprecated">hms::is.hms</a></code>
</li>
@ -916,18 +920,18 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
</li>
</ul>
<p>They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:</p>
<li>Functions <code>count_R</code>, <code>count_IR</code>, <code>count_I</code>, <code>count_SI</code> and <code>count_S</code> to selectively count resistant or susceptible isolates
<ul>
@ -938,18 +942,18 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
</li>
<li>
<p>Functions <code>as.mo</code> and <code>is.mo</code> as replacements for <code>as.bactid</code> and <code>is.bactid</code> (since the <code>microoganisms</code> data set not only contains bacteria). These last two functions are deprecated and will be removed in a future release. The <code>as.mo</code> function determines microbial IDs using intelligent rules:</p>
<aclass="sourceLine"id="cb24-5" data-line-number="5"><spanclass="kw"><ahref="../reference/as.mo.html">as.mo</a></span>(<spanclass="st">"S group A"</span>)</a>
<aclass="sourceLine"id="cb25-5" data-line-number="5"><spanclass="kw"><ahref="../reference/as.mo.html">as.mo</a></span>(<spanclass="st">"S group A"</span>)</a>
<li>Added parameter <code>reference_df</code> for <code>as.mo</code>, so users can supply their own microbial IDs, name or codes as a reference table</li>
<li>Renamed all previous references to <code>bactid</code> to <code>mo</code>, like:
@ -977,12 +981,12 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<li>Added three antimicrobial agents to the <code>antibiotics</code> data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)</li>
<li>
<p>Added 163 trade names to the <code>antibiotics</code> data set, it now contains 298 different trade names in total, e.g.:</p>
<li>For <code>first_isolate</code>, rows will be ignored when there’s no species available</li>
<li>Function <code>ratio</code> is now deprecated and will be removed in a future release, as it is not really the scope of this package</li>
@ -993,13 +997,13 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
</li>
<li>
<p>Support for quasiquotation in the functions series <code>count_*</code> and <code>portions_*</code>, and <code>n_rsi</code>. This allows to check for more than 2 vectors or columns.</p>
<li>Edited <code>ggplot_rsi</code> and <code>geom_rsi</code> so they can cope with <code>count_df</code>. The new <code>fun</code> parameter has value <code>portion_df</code> at default, but can be set to <code>count_df</code>.</li>
<li>Fix for <code>ggplot_rsi</code> when the <code>ggplot2</code> package was not loaded</li>
@ -1013,12 +1017,12 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
</li>
<li>
<p>Support for types (classes) list and matrix for <code>freq</code></p>
<spanclass="version label label-default"data-toggle="tooltip"data-placement="bottom"title="Latest development version">0.7.1.9055</span>
<spanclass="version label label-default"data-toggle="tooltip"data-placement="bottom"title="Latest development version">0.7.1.9062</span>
</span>
</div>
@ -318,29 +318,22 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
<p>When using more than one variable for <code>...</code> (= combination therapy)), use <code>only_all_tested</code> to only count isolates that are tested for all antibiotics/variables that you test them for. See this example for two antibiotics, Antibiotic A and Antibiotic B, about how <code>portion_SI</code> works to calculate the %SI:</p>
<p>Please note that, in combination therapies, for <code>only_all_tested = TRUE</code> applies that:</p><pre>
count_S() + count_I() + count_R() == count_all()
@ -448,7 +441,7 @@ not tested not tested - - - -
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<divclass="copyright">
<p>Developed by <ahref='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <ahref='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <ahref='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <ahref='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <ahref='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
<p>Developed by <ahref='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <ahref='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <ahref='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <ahref='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <ahref='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <ahref='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
<spanclass="version label label-default"data-toggle="tooltip"data-placement="bottom"title="Latest development version">0.7.1.9055</span>
<spanclass="version label label-default"data-toggle="tooltip"data-placement="bottom"title="Latest development version">0.7.1.9062</span>
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@ -321,29 +321,22 @@ portion_R and portion_IR can be used to calculate resistance, portion_S and port
<p>When using more than one variable for <code>...</code> (= combination therapy)), use <code>only_all_tested</code> to only count isolates that are tested for all antibiotics/variables that you test them for. See this example for two antibiotics, Antibiotic A and Antibiotic B, about how <code>portion_SI</code> works to calculate the %SI:</p>
<p>Please note that, in combination therapies, for <code>only_all_tested = TRUE</code> applies that:</p><pre>
count_S() + count_I() + count_R() == count_all()
@ -494,7 +487,7 @@ not tested not tested - - - -
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<divclass="copyright">
<p>Developed by <ahref='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <ahref='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <ahref='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <ahref='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <ahref='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
<p>Developed by <ahref='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <ahref='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <ahref='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <ahref='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <ahref='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <ahref='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
@ -84,29 +84,22 @@ This AMR package honours this new insight. Use \code{\link{portion_SI}} to deter
When using more than one variable for \code{...} (= combination therapy)), use \code{only_all_tested} to only count isolates that are tested for all antibiotics/variables that you test them for. See this example for two antibiotics, Antibiotic A and Antibiotic B, about how \code{portion_SI} works to calculate the \%SI:
@ -80,29 +80,22 @@ The function \code{rsi_df} works exactly like \code{portion_df}, but adds the nu
When using more than one variable for \code{...} (= combination therapy)), use \code{only_all_tested} to only count isolates that are tested for all antibiotics/variables that you test them for. See this example for two antibiotics, Antibiotic A and Antibiotic B, about how \code{portion_SI} works to calculate the \%SI:
