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+4
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@@ -91,7 +91,7 @@
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website update since they are based on randomly created values and the
|
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page was written in <a href="https://rmarkdown.rstudio.com/" class="external-link">R
|
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Markdown</a>. However, the methodology remains unchanged. This page was
|
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generated on 13 June 2025.</p>
|
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generated on 22 June 2025.</p>
|
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<div class="section level2">
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<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
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</h2>
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@@ -147,21 +147,21 @@ make the structure of your data generally look like this:</p>
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</tr></thead>
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<tbody>
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<tr class="odd">
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<td align="center">2025-06-13</td>
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<td align="center">2025-06-22</td>
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<td align="center">abcd</td>
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<td align="center">Escherichia coli</td>
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<td align="center">S</td>
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<td align="center">S</td>
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</tr>
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<tr class="even">
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<td align="center">2025-06-13</td>
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<td align="center">2025-06-22</td>
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<td align="center">abcd</td>
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<td align="center">Escherichia coli</td>
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<td align="center">S</td>
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<td align="center">R</td>
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</tr>
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<tr class="odd">
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<td align="center">2025-06-13</td>
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<td align="center">2025-06-22</td>
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<td align="center">efgh</td>
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<td align="center">Escherichia coli</td>
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<td align="center">R</td>
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@@ -80,7 +80,7 @@
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<main id="main" class="col-md-9"><div class="page-header">
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<img src="../logo.svg" class="logo" alt=""><h1>Download data sets for download / own use</h1>
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<h4 data-toc-skip class="date">13 June 2025</h4>
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<h4 data-toc-skip class="date">22 June 2025</h4>
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<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small>
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<div class="d-none name"><code>datasets.Rmd</code></div>
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+1
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@@ -503,7 +503,7 @@
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<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"AMR"</span>, repos <span class="op">=</span> <span class="st">"beta.amr-for-r.org"</span><span class="op">)</span></span>
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<span></span>
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<span><span class="co"># if this does not work, try to install directly from GitHub using the 'remotes' package:</span></span>
|
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<span><span class="fu">remotes</span><span class="fu">::</span><span class="fu"><a href="https://remotes.r-lib.org/reference/install_github.html" class="external-link">install_github</a></span><span class="op">(</span><span class="st">"msberends/AMR"</span><span class="op">)</span></span></code></pre></div>
|
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<span><span class="fu">remotes</span><span class="fu">::</span><span class="fu">install_github</span><span class="op">(</span><span class="st">"msberends/AMR"</span><span class="op">)</span></span></code></pre></div>
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</div>
|
||||
</div>
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<div class="section level2">
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+1
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@@ -10,7 +10,7 @@ articles:
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PCA: PCA.html
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WHONET: WHONET.html
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WISCA: WISCA.html
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last_built: 2025-06-13T15:09Z
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last_built: 2025-06-22T18:50Z
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urls:
|
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reference: https://amr-for-r.org/reference
|
||||
article: https://amr-for-r.org/articles
|
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+10
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@@ -112,16 +112,16 @@
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||||
<span class="r-in"><span></span></span>
|
||||
<span class="r-in"><span><span class="va">df</span></span></span>
|
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<span class="r-out co"><span class="r-pr">#></span> birth_date age age_exact age_at_y2k</span>
|
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<span class="r-out co"><span class="r-pr">#></span> 1 1999-06-30 25 25.95342 0</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 2 1968-01-29 57 57.36986 31</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 3 1965-12-05 59 59.52055 34</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 4 1980-03-01 45 45.28493 19</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 5 1949-11-01 75 75.61370 50</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 6 1947-02-14 78 78.32603 52</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 7 1940-02-19 85 85.31233 59</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 8 1988-01-10 37 37.42192 11</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 9 1997-08-27 27 27.79452 2</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 10 1978-01-26 47 47.37808 21</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 1 1980-02-27 45 45.31507 19</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 2 1953-07-26 71 71.90685 46</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 3 1949-09-02 75 75.80274 50</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 4 1986-08-03 38 38.88493 13</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 5 1932-11-19 92 92.58904 67</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 6 1949-03-30 76 76.23014 50</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 7 1996-06-23 28 28.99726 3</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 8 1963-09-16 61 61.76438 36</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 9 1952-05-16 73 73.10137 47</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 10 1952-11-14 72 72.60274 47</span>
|
||||
</code></pre></div>
|
||||
</div>
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||||
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
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@@ -218,10 +218,10 @@ may affect the computations for subsequent operations.</p></dd>
|
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 4 × 3</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> .metric .estimator .estimate</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><dbl></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> accuracy binary 0.912</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> kap binary 0.824</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">3</span> ppv binary 0.917</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">4</span> npv binary 0.908</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> accuracy binary 0.936</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> kap binary 0.872</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">3</span> ppv binary 0.925</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">4</span> npv binary 0.948</span>
|
||||
</code></pre></div>
|
||||
</div>
|
||||
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
|
||||
|
||||
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@@ -587,9 +587,9 @@ Adhering to previously described approaches (see Source) and especially the Baye
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Type: WISCA with 95% CI</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> `Syndromic Group` `Piperacillin/tazobactam` Piperacillin/tazobactam + Gentam…¹</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> Clinical 73.4% (68.3-78.6%) 92.3% (90.7-93.7%) </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> ICU 57.4% (49.7-65.4%) 84.9% (82.1-87.6%) </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">3</span> Outpatient 57% (47.4-66.7%) 74.6% (68.8-79.8%) </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> Clinical 73.6% (68.3-78.8%) 92.3% (90.8-93.8%) </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> ICU 57.2% (49.8-65.1%) 84.9% (81.8-87.8%) </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">3</span> Outpatient 57.1% (47.2-66.8%) 74.4% (69-79.6%) </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># ℹ abbreviated name: ¹`Piperacillin/tazobactam + Gentamicin`</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># ℹ 1 more variable: `Piperacillin/tazobactam + Tobramycin` <chr></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,</span></span>
|
||||
@@ -614,9 +614,9 @@ Adhering to previously described approaches (see Source) and especially the Baye
|
||||
<span class="r-out co"><span class="r-pr">#></span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> |Syndromic Group |Piperacillin/tazobactam |</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> |:---------------|:-----------------------|</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> |Clinical |73.5% (68-79%) |</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> |ICU |57.7% (49.9-65.3%) |</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> |Outpatient |56.9% (46.5-66.8%) |</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> |Clinical |73.4% (67.8-78.8%) |</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> |ICU |57.2% (49.6-65.3%) |</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> |Outpatient |56.9% (47.1-66.9%) |</span>
|
||||
<span class="r-in"><span></span></span>
|
||||
<span class="r-in"><span></span></span>
|
||||
<span class="r-in"><span><span class="co"># Generate plots with ggplot2 or base R --------------------------------</span></span></span>
|
||||
|
||||
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@@ -414,10 +414,10 @@ Breakpoints are currently implemented from EUCAST 2011-2025 and CLSI 2011-2025,
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 4 × 18</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> datetime index method ab_given mo_given host_given input_given</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><dttm></span> <span style="color: #949494; font-style: italic;"><int></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> 2025-06-13 <span style="color: #949494;">15:10:25</span> 1 MIC amoxicillin Escherich… human 8 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> 2025-06-13 <span style="color: #949494;">15:10:25</span> 1 MIC cipro Escherich… human 0.256 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">3</span> 2025-06-13 <span style="color: #949494;">15:10:26</span> 1 DISK tobra Escherich… human 16 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">4</span> 2025-06-13 <span style="color: #949494;">15:10:26</span> 1 DISK genta Escherich… human 18 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> 2025-06-22 <span style="color: #949494;">18:51:08</span> 1 MIC amoxicillin Escherich… human 8 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> 2025-06-22 <span style="color: #949494;">18:51:08</span> 1 MIC cipro Escherich… human 0.256 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">3</span> 2025-06-22 <span style="color: #949494;">18:51:08</span> 1 DISK tobra Escherich… human 16 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">4</span> 2025-06-22 <span style="color: #949494;">18:51:08</span> 1 DISK genta Escherich… human 18 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># ℹ 11 more variables: ab <ab>, mo <mo>, host <chr>, input <chr>,</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># outcome <sir>, notes <chr>, guideline <chr>, ref_table <chr>, uti <lgl>,</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># breakpoint_S_R <chr>, site <chr></span></span>
|
||||
|
||||
+55
-54
@@ -154,27 +154,28 @@
|
||||
<span class="r-in"><span><span class="va">df</span> <span class="op"><-</span> <span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq_len</a></span><span class="op">(</span><span class="fl">2000</span><span class="op">)</span>, size <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>, <span class="op">]</span></span></span>
|
||||
<span class="r-in"><span></span></span>
|
||||
<span class="r-in"><span><span class="fu">get_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span> <span class="co"># indices</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 7 4 45 15 6 11 26 43 24 20 8 29 24 42 32 13 45 2 43 39 15 32 45 2 31</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [26] 4 19 21 44 22 44 9 43 38 16 7 45 10 33 36 44 4 20 11 14 5 19 7 39 6</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [51] 46 30 4 30 41 7 13 28 37 30 18 27 9 42 17 22 40 12 8 34 13 2 44 4 3</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [76] 33 35 15 22 23 15 9 40 12 1 43 17 18 36 31 22 34 37 43 36 37 10 23 25 36</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 43 9 7 14 28 40 49 29 19 27 10 44 18 22 42 12 8 36 13 3 46 5 4 35 38</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [26] 16 22 23 16 10 42 13 2 45 18 19 39 32 22 36 40 45 39 40 11 23 25 39 26 23</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [51] 25 12 17 23 30 30 34 16 21 37 40 26 11 7 4 16 43 22 47 37 39 31 25 41 1</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [76] 45 39 23 32 45 20 22 15 14 13 43 9 38 29 6 48 24 21 23 44 19 31 1 3 33</span>
|
||||
<span class="r-in"><span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span> <span class="co"># TRUE/FALSE</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [13] FALSE TRUE TRUE TRUE FALSE TRUE FALSE TRUE FALSE FALSE FALSE FALSE</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [25] TRUE FALSE TRUE TRUE TRUE TRUE FALSE TRUE FALSE TRUE TRUE FALSE</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [37] FALSE TRUE TRUE TRUE FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [49] FALSE FALSE TRUE TRUE FALSE FALSE TRUE FALSE FALSE TRUE TRUE FALSE</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [61] TRUE TRUE FALSE FALSE TRUE FALSE TRUE TRUE FALSE TRUE FALSE FALSE</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [73] FALSE FALSE TRUE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [85] TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [97] FALSE FALSE TRUE FALSE</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [13] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [25] TRUE TRUE FALSE TRUE FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [37] TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE TRUE FALSE</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [49] TRUE FALSE FALSE FALSE TRUE FALSE TRUE FALSE TRUE FALSE TRUE TRUE</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [73] FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE TRUE FALSE</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [85] FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE FALSE FALSE FALSE</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [97] FALSE FALSE FALSE TRUE</span>
|
||||
<span class="r-in"><span></span></span>
|
||||
<span class="r-in"><span><span class="co"># filter on results from the third 60-day episode only, using base R</span></span></span>
|
||||
<span class="r-in"><span><span class="va">df</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html" class="external-link">which</a></span><span class="op">(</span><span class="fu">get_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, <span class="fl">60</span><span class="op">)</span> <span class="op">==</span> <span class="fl">3</span><span class="op">)</span>, <span class="op">]</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 1 × 46</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> date patient age gender ward mo PEN OXA FLC AMX </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><date></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><dbl></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><mo></span> <span style="color: #949494; font-style: italic;"><sir></span> <span style="color: #949494; font-style: italic;"><sir></span> <span style="color: #949494; font-style: italic;"><sir></span> <span style="color: #949494; font-style: italic;"><sir></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> 2003-01-06 894506 83 M ICU <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN <span style="color: #080808; background-color: #5FD7AF;"> S </span> <span style="color: #B2B2B2;"> NA</span> <span style="color: #B2B2B2;"> NA</span> <span style="color: #080808; background-color: #5FD7AF;"> S </span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 2 × 46</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> date patient age gender ward mo PEN OXA FLC AMX </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><date></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><dbl></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><mo></span> <span style="color: #949494; font-style: italic;"><sir></span> <span style="color: #949494; font-style: italic;"><sir></span> <span style="color: #949494; font-style: italic;"><sir></span> <span style="color: #949494; font-style: italic;"><sir></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> 2002-11-04 304347 62 M Clinical <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN <span style="color: #080808; background-color: #5FD7AF;"> S </span> <span style="color: #B2B2B2;"> NA</span> <span style="color: #B2B2B2;"> NA</span> <span style="color: #080808; background-color: #5FD7AF;"> S </span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> 2002-10-18 E55128 57 F ICU <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS <span style="color: #080808; background-color: #FFAFAF;"> R </span> <span style="color: #B2B2B2;"> NA</span> <span style="color: #080808; background-color: #5FD7AF;"> S </span> <span style="color: #080808; background-color: #FFAFAF;"> R </span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>,</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>,</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>,</span></span>
|
||||
@@ -208,19 +209,19 @@
|
||||
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange</a></span><span class="op">(</span><span class="va">patient</span>, <span class="va">condition</span>, <span class="va">date</span><span class="op">)</span></span></span>
|
||||
<span class="r-in"><span><span class="op">}</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 100 × 4</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Groups: patient, condition [93]</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Groups: patient, condition [96]</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> patient date condition new_episode</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><date></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><lgl></span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> 060287 2007-03-11 A TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 2</span> 101305 2006-12-13 A TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> 141061 2014-10-22 A TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 4</span> 151041 2006-02-10 A TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 5</span> 15D386 2004-08-01 B TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 6</span> 187841 2008-04-22 A TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 7</span> 189363 2004-06-22 C TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> 208305 2015-09-14 A TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> 257844 2011-05-22 A TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> 284FFF 2010-03-31 A TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> 022060 2004-05-04 A TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 2</span> 060287 2007-03-11 A TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> 0E2483 2007-04-06 C TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 4</span> 101305 2006-12-13 A TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 5</span> 141061 2014-10-22 A TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 6</span> 146F70 2009-08-14 A TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 7</span> 15D386 2004-08-01 B TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> 187841 2008-04-22 C TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> 195736 2008-08-29 C TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> 195736 2008-08-29 C FALSE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># ℹ 90 more rows</span></span>
|
||||
<span class="r-in"><span></span></span>
|
||||
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
|
||||
@@ -234,19 +235,19 @@
|
||||
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange</a></span><span class="op">(</span><span class="va">patient</span>, <span class="va">ward</span>, <span class="va">date</span><span class="op">)</span></span></span>
|
||||
<span class="r-in"><span><span class="op">}</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 100 × 5</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Groups: ward, patient [88]</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Groups: ward, patient [91]</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> ward date patient new_index new_logical</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><date></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><int></span> <span style="color: #949494; font-style: italic;"><lgl></span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> Clinical 2007-03-11 060287 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 2</span> Clinical 2006-12-13 101305 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> Clinical 2014-10-22 141061 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 4</span> Clinical 2006-02-10 151041 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 5</span> ICU 2004-08-01 15D386 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 6</span> Clinical 2008-04-22 187841 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 7</span> Clinical 2004-06-22 189363 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> Clinical 2015-09-14 208305 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> Clinical 2011-05-22 257844 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> Clinical 2010-03-31 284FFF 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> ICU 2004-05-04 022060 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 2</span> Clinical 2007-03-11 060287 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> Clinical 2007-04-06 0E2483 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 4</span> Clinical 2006-12-13 101305 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 5</span> Clinical 2014-10-22 141061 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 6</span> Clinical 2009-08-14 146F70 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 7</span> ICU 2004-08-01 15D386 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> Clinical 2008-04-22 187841 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> Clinical 2008-08-29 195736 1 TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> Clinical 2008-08-29 195736 1 FALSE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># ℹ 90 more rows</span></span>
|
||||
<span class="r-in"><span></span></span>
|
||||
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
|
||||
@@ -262,9 +263,9 @@
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 3 × 5</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> ward n_patients n_episodes_365 n_episodes_60 n_episodes_30</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><int></span> <span style="color: #949494; font-style: italic;"><int></span> <span style="color: #949494; font-style: italic;"><int></span> <span style="color: #949494; font-style: italic;"><int></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> Clinical 55 12 34 39</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> ICU 27 10 24 25</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">3</span> Outpatient 6 5 6 6</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> Clinical 58 14 38 44</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> ICU 26 7 20 23</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">3</span> Outpatient 7 4 6 7</span>
|
||||
<span class="r-in"><span></span></span>
|
||||
<span class="r-in"><span><span class="co"># grouping on patients and microorganisms leads to the same</span></span></span>
|
||||
<span class="r-in"><span><span class="co"># results as first_isolate() when using 'episode-based':</span></span></span>
|
||||
@@ -293,19 +294,19 @@
|
||||
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_data.html" class="external-link">group_vars</a></span><span class="op">(</span><span class="va">.</span><span class="op">)</span>, <span class="va">flag_episode</span><span class="op">)</span></span></span>
|
||||
<span class="r-in"><span><span class="op">}</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 100 × 4</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Groups: patient, mo, ward [92]</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> patient mo ward flag_episode</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><mo></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><lgl></span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> F24801 <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>AGLC ICU TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 2</span> A26548 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>CONS ICU TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> 422833 <span style="color: #949494;">B_</span>ENTRC<span style="color: #949494;">_</span>FCLS Clinical TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 4</span> AFD3B1 <span style="color: #BB0000;"> UNKNOWN</span> Clinical TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 5</span> F35553 <span style="color: #949494;">B_</span>ENTRBC<span style="color: #949494;">_</span>CLOC ICU TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 6</span> 316893 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>CONS Clinical TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 7</span> B54813 <span style="color: #949494;">B_</span>ENTRC ICU TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> E06844 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS Outpatient TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> B65162 <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN Clinical TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> 43F266 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS ICU TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Groups: patient, mo, ward [96]</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> patient mo ward flag_episode</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><mo></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><lgl></span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> 917895 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>CPTS ICU TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 2</span> 022060 <span style="color: #949494;">B_</span>ENTRBC<span style="color: #949494;">_</span>CLOC ICU TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> C36883 <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI Clinical TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 4</span> 5DF436 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS ICU TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 5</span> 971739 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>CONS Clinical TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 6</span> 488175 <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI Clinical TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 7</span> 5DB1C8 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>CPTS Clinical TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> BC9909 <span style="color: #949494;">B_</span>ENTRBC<span style="color: #949494;">_</span>CLOC Clinical TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> 5B78D5 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS Clinical TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> 284FFF <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR Clinical TRUE </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># ℹ 90 more rows</span></span>
|
||||
<span class="r-in"><span><span class="co"># }</span></span></span>
|
||||
</code></pre></div>
|
||||
|
||||
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@@ -91,9 +91,9 @@
|
||||
<div class="section level2">
|
||||
<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
|
||||
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu">kurtosis</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">10000</span><span class="op">)</span><span class="op">)</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 3.072546</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 3.069947</span>
|
||||
<span class="r-in"><span><span class="fu">kurtosis</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">10000</span><span class="op">)</span>, excess <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] -0.024332</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] -0.02599697</span>
|
||||
</code></pre></div>
|
||||
</div>
|
||||
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
|
||||
|
||||
@@ -110,31 +110,30 @@
|
||||
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">sir</span> <span class="op"><-</span> <span class="fu"><a href="random.html">random_sir</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span></span></span>
|
||||
<span class="r-in"><span><span class="va">sir</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> Class 'sir'</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] R S R I I R R R S R</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] R R I R I I S R S I</span>
|
||||
<span class="r-in"><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">sir</span><span class="op">)</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 0.7745967 -1.1618950 0.7745967 -1.1618950 -1.1618950 0.7745967</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [7] 0.7745967 0.7745967 -1.1618950 0.7745967</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 1.1618950 1.1618950 -0.7745967 1.1618950 -0.7745967 -0.7745967</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [7] -0.7745967 1.1618950 -0.7745967 -0.7745967</span>
|
||||
<span class="r-in"><span></span></span>
|
||||
<span class="r-in"><span><span class="va">mic</span> <span class="op"><-</span> <span class="fu"><a href="random.html">random_mic</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span></span></span>
|
||||
<span class="r-in"><span><span class="va">mic</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> Class 'mic'</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 0.25 0.0005 0.001 0.0002 8 <=0.0001 <=0.0001 0.004 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [9] 0.016 0.002 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 0.032 0.5 1 >=8 4 0.016 >=8 1 0.004 0.008</span>
|
||||
<span class="r-in"><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">mic</span><span class="op">)</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 1.17346160 -0.53194487 -0.34173212 -0.78339244 2.12452534 -0.97360519</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [7] -0.97360519 0.03869338 0.41911887 -0.15151937</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] -0.7311752 0.2104422 0.4478776 1.1601837 0.9227483 -0.9686106</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [7] 1.1601837 0.4478776 -1.4434813 -1.2060459</span>
|
||||
<span class="r-in"><span><span class="co"># equal to the Z-score of their log2:</span></span></span>
|
||||
<span class="r-in"><span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log2</a></span><span class="op">(</span><span class="va">mic</span><span class="op">)</span> <span class="op">-</span> <span class="fu"><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log2</a></span><span class="op">(</span><span class="va">mic</span><span class="op">)</span><span class="op">)</span><span class="op">)</span> <span class="op">/</span> <span class="fu"><a href="https://rdrr.io/r/stats/sd.html" class="external-link">sd</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log2</a></span><span class="op">(</span><span class="va">mic</span><span class="op">)</span><span class="op">)</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 1.17346160 -0.53194487 -0.34173212 -0.78339244 2.12452534 -0.97360519</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [7] -0.97360519 0.03869338 0.41911887 -0.15151937</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] -0.7311752 0.2104422 0.4478776 1.1601837 0.9227483 -0.9686106</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [7] 1.1601837 0.4478776 -1.4434813 -1.2060459</span>
|
||||
<span class="r-in"><span></span></span>
|
||||
<span class="r-in"><span><span class="va">disk</span> <span class="op"><-</span> <span class="fu"><a href="random.html">random_disk</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span></span></span>
|
||||
<span class="r-in"><span><span class="va">disk</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> Class 'disk'</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 31 26 23 38 44 41 20 49 32 16</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 50 49 38 33 31 17 42 43 46 37</span>
|
||||
<span class="r-in"><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">disk</span><span class="op">)</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] -0.09179851 -0.55079106 -0.82618658 0.55079106 1.10158211 0.82618658</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [7] -1.10158211 1.56057466 0.00000000 -1.46877615</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 1.15131286 1.05032051 -0.06059541 -0.56555720 -0.76754191 -2.18143490</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [7] 0.34337401 0.44436637 0.74734344 -0.16158777</span>
|
||||
<span class="r-in"><span></span></span>
|
||||
<span class="r-in"><span><span class="va">y</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span></span></span>
|
||||
<span class="r-in"><span> id <span class="op">=</span> <span class="va">LETTERS</span><span class="op">[</span><span class="fl">1</span><span class="op">:</span><span class="fl">10</span><span class="op">]</span>,</span></span>
|
||||
@@ -145,35 +144,35 @@
|
||||
<span class="r-in"><span><span class="op">)</span></span></span>
|
||||
<span class="r-in"><span><span class="va">y</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> id amox cipr gent tobr</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 1 A S 27 8 32</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 2 B I 33 2 16</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 3 C I 22 1 <=4</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 4 D R 32 0.25 8</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 5 E S 31 8 16</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 6 F I 31 2 <=4</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 7 G R 28 2 <=4</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 8 H S 22 16 8</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 9 I I 22 8 16</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 10 J I 24 0.25 32</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 1 A I 27 >=2 8</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 2 B S 28 1 8</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 3 C R 33 1 8</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 4 D R 32 1 16</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 5 E I 25 0.5 16</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 6 F I 19 0.5 8</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 7 G S 23 0.5 16</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 8 H R 27 0.5 8</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 9 I S 29 1 8</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 10 J R 32 0.5 16</span>
|
||||
<span class="r-in"><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">y</span><span class="op">)</span></span></span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #0000BB;">ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent",</span></span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #0000BB;"> and "tobr"</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 0.42546514 0.31178268 -0.85243112 0.27789744 0.43759204 -0.22674498</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [7] 0.19734764 -0.16271414 -0.06891128 -0.33928341</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 0.08471751 -0.21572693 0.55391610 0.98093500 -0.26046456 -1.08721162</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [7] -0.37467261 -0.14625651 -0.15862291 0.62338653</span>
|
||||
<span class="r-in"><span><span class="va">y</span><span class="op">$</span><span class="va">amr_distance</span> <span class="op"><-</span> <span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">y</span>, <span class="fu"><a href="as.mic.html">is.mic</a></span><span class="op">(</span><span class="va">y</span><span class="op">)</span><span class="op">)</span></span></span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #0000BB;">ℹ Calculating mean AMR distance based on columns "gent" and "tobr"</span></span>
|
||||
<span class="r-in"><span><span class="va">y</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/order.html" class="external-link">order</a></span><span class="op">(</span><span class="va">y</span><span class="op">$</span><span class="va">amr_distance</span><span class="op">)</span>, <span class="op">]</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> id amox cipr gent tobr amr_distance</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 4 D R 32 0.25 8 -0.93315862</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 3 C I 22 1 <=4 -0.88239870</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 6 F I 31 2 <=4 -0.64403306</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 7 G R 28 2 <=4 -0.64403306</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 10 J I 24 0.25 32 -0.08121587</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 2 B I 33 2 16 0.20790970</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 8 H S 22 16 8 0.49703526</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 5 E S 31 8 16 0.68464099</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 9 I I 22 8 16 0.68464099</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 1 A S 27 8 32 1.11061237</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 6 F I 19 0.5 8 -0.8163565</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 8 H R 27 0.5 8 -0.8163565</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 2 B S 28 1 8 -0.1012596</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 3 C R 33 1 8 -0.1012596</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 9 I S 29 1 8 -0.1012596</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 5 E I 25 0.5 16 0.1518893</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 7 G S 23 0.5 16 0.1518893</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 10 J R 32 0.5 16 0.1518893</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 1 A I 27 >=2 8 0.6138374</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 4 D R 32 1 16 0.8669863</span>
|
||||
<span class="r-in"><span></span></span>
|
||||
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
|
||||
<span class="r-in"><span> <span class="va">y</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||||
@@ -186,16 +185,16 @@
|
||||
<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #0000BB;">ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent",</span></span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #0000BB;"> and "tobr"</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> id amox cipr gent tobr amr_distance check_id_C</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 1 C I 22 1 <=4 -0.85243112 0.0000000</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 2 J I 24 0.25 32 -0.33928341 0.5131477</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 3 F I 31 2 <=4 -0.22674498 0.6256861</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 4 H S 22 16 8 -0.16271414 0.6897170</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 5 I I 22 8 16 -0.06891128 0.7835198</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 6 G R 28 2 <=4 0.19734764 1.0497788</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 7 D R 32 0.25 8 0.27789744 1.1303286</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 8 B I 33 2 16 0.31178268 1.1642138</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 9 A S 27 8 32 0.42546514 1.2778963</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 10 E S 31 8 16 0.43759204 1.2900232</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 1 C R 33 1 8 0.55391610 0.00000000</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 2 J R 32 0.5 16 0.62338653 0.06947042</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 3 D R 32 1 16 0.98093500 0.42701889</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 4 A I 27 >=2 8 0.08471751 0.46919859</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 5 H R 27 0.5 8 -0.14625651 0.70017262</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 6 I S 29 1 8 -0.15862291 0.71253901</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 7 B S 28 1 8 -0.21572693 0.76964304</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 8 E I 25 0.5 16 -0.26046456 0.81438066</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 9 G S 23 0.5 16 -0.37467261 0.92858871</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 10 F I 19 0.5 8 -1.08721162 1.64112773</span>
|
||||
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
|
||||
<span class="r-in"><span> <span class="co"># support for groups</span></span></span>
|
||||
<span class="r-in"><span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||||
|
||||
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+16
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@@ -111,16 +111,15 @@
|
||||
<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
|
||||
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu">random_mic</span><span class="op">(</span><span class="fl">25</span><span class="op">)</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> Class 'mic'</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 0.125 2 16 1 0.004 0.008 0.0005 0.125 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [9] 2 0.008 0.008 0.016 0.064 0.064 <=0.0002 0.001 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [17] 0.0005 0.5 0.002 0.002 0.125 8 <=0.0002 0.002 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [25] 0.064 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 1 0.064 2 0.016 128 0.001 0.004 0.008 64 0.064 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [11] 0.002 0.001 0.016 0.004 0.0005 0.0005 0.125 0.032 0.032 8 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [21] 2 8 0.008 0.0005 8 </span>
|
||||
<span class="r-in"><span><span class="fu">random_disk</span><span class="op">(</span><span class="fl">25</span><span class="op">)</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> Class 'disk'</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 47 24 47 38 28 36 33 31 50 41 29 40 31 44 45 37 40 44 49 9 48 20 37 47 28</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 46 38 45 47 24 28 45 43 19 23 44 19 31 22 40 39 39 36 35 14 34 45 21 19 39</span>
|
||||
<span class="r-in"><span><span class="fu">random_sir</span><span class="op">(</span><span class="fl">25</span><span class="op">)</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> Class 'sir'</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] S R R S S I S I S S I S R I I I I S I R I I I I R</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] I S R I R I S S S R R R I I R R I S R R S I S R I</span>
|
||||
<span class="r-in"><span></span></span>
|
||||
<span class="r-in"><span><span class="co"># add more skewedness, make more realistic by setting a bug and/or drug:</span></span></span>
|
||||
<span class="r-in"><span><span class="va">disks</span> <span class="op"><-</span> <span class="fu">random_disk</span><span class="op">(</span><span class="fl">100</span>, severity <span class="op">=</span> <span class="fl">2</span>, mo <span class="op">=</span> <span class="st">"Escherichia coli"</span>, ab <span class="op">=</span> <span class="st">"CIP"</span><span class="op">)</span></span></span>
|
||||
@@ -133,30 +132,28 @@
|
||||
<span class="r-in"><span><span class="co"># \donttest{</span></span></span>
|
||||
<span class="r-in"><span><span class="fu">random_mic</span><span class="op">(</span><span class="fl">25</span>, <span class="st">"Klebsiella pneumoniae"</span><span class="op">)</span> <span class="co"># range 0.0625-64</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> Class 'mic'</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 0.0005 8 0.008 0.0002 0.0002 0.0002 0.0002 <=0.0001</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [9] 64 <=0.0001 1 0.5 0.001 0.5 0.001 0.0005 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [17] 0.016 0.008 0.002 0.032 <=0.0001 0.0002 0.001 0.0005 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [25] 0.001 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 2 0.032 32 0.5 0.001 0.008 0.002 4 0.0005 1 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [11] 0.001 1 8 0.002 0.25 2 0.016 0.004 0.25 0.125 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [21] 0.002 0.5 0.004 >=256 0.0005</span>
|
||||
<span class="r-in"><span><span class="fu">random_mic</span><span class="op">(</span><span class="fl">25</span>, <span class="st">"Klebsiella pneumoniae"</span>, <span class="st">"meropenem"</span><span class="op">)</span> <span class="co"># range 0.0625-16</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> Class 'mic'</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] <=0.5 <=0.5 2 <=0.5 1 <=0.5 <=0.5 <=0.5 <=0.5 1 <=0.5 <=0.5</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [13] <=0.5 1 <=0.5 1 <=0.5 <=0.5 <=0.5 <=0.5 <=0.5 <=0.5 2 1 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [25] 2 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 4 >=8 4 >=8 4 >=8 4 4 4 4 4 4 >=8 >=8 4 >=8 4 4 4 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [20] 4 4 4 4 4 4 </span>
|
||||
<span class="r-in"><span><span class="fu">random_mic</span><span class="op">(</span><span class="fl">25</span>, <span class="st">"Streptococcus pneumoniae"</span>, <span class="st">"meropenem"</span><span class="op">)</span> <span class="co"># range 0.0625-4</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> Class 'mic'</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 0.125 0.125 1 0.25 0.5 0.125 0.125 0.125 0.125 0.125 0.125 0.125</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [13] 1 0.125 0.5 1 0.125 0.25 0.5 0.25 0.5 0.5 0.5 0.125</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [25] 0.25 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] <=0.25 0.5 <=0.25 <=0.25 <=0.25 0.5 <=0.25 <=0.25 <=0.25 <=0.25</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [11] <=0.25 <=0.25 0.5 <=0.25 <=0.25 <=0.25 0.5 <=0.25 0.5 <=0.25</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [21] <=0.25 0.5 <=0.25 0.5 0.5 </span>
|
||||
<span class="r-in"><span></span></span>
|
||||
<span class="r-in"><span><span class="fu">random_disk</span><span class="op">(</span><span class="fl">25</span>, <span class="st">"Klebsiella pneumoniae"</span><span class="op">)</span> <span class="co"># range 8-50</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> Class 'disk'</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 32 21 23 21 14 22 25 29 29 28 34 34 34 33 13 28 33 34 32 25 18 26 13 21 33</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 33 26 16 27 29 33 24 17 17 15 16 26 26 14 17 29 25 25 24 32 32 34 18 31 10</span>
|
||||
<span class="r-in"><span><span class="fu">random_disk</span><span class="op">(</span><span class="fl">25</span>, <span class="st">"Klebsiella pneumoniae"</span>, <span class="st">"ampicillin"</span><span class="op">)</span> <span class="co"># range 11-17</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> Class 'disk'</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 20 21 15 22 16 22 16 14 21 17 15 19 20 17 18 21 16 20 11 22 19 18 19 11 21</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 19 20 11 14 12 12 17 16 12 10 15 22 19 21 19 17 18 19 21 17 21 15 17 12 19</span>
|
||||
<span class="r-in"><span><span class="fu">random_disk</span><span class="op">(</span><span class="fl">25</span>, <span class="st">"Streptococcus pneumoniae"</span>, <span class="st">"ampicillin"</span><span class="op">)</span> <span class="co"># range 12-27</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> Class 'disk'</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 29 25 31 17 29 21 31 34 33 31 29 30 23 20 33 20 34 32 35 26 26 26 34 30 33</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] 27 24 31 22 35 28 26 32 24 18 35 33 24 28 33 25 35 25 32 24 26 20 23 22 33</span>
|
||||
<span class="r-in"><span><span class="co"># }</span></span></span>
|
||||
</code></pre></div>
|
||||
</div>
|
||||
|
||||
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@@ -90,7 +90,7 @@ When negative ('left-skewed'): the left tail is longer; the mass of the distribu
|
||||
<div class="section level2">
|
||||
<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
|
||||
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu">skewness</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Uniform.html" class="external-link">runif</a></span><span class="op">(</span><span class="fl">1000</span><span class="op">)</span><span class="op">)</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] -0.08600633</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> [1] -0.03886098</span>
|
||||
</code></pre></div>
|
||||
</div>
|
||||
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
|
||||
|
||||
+1
-1
@@ -1 +1 @@
|
||||
[{"path":"https://amr-for-r.org/articles/AMR.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"Conduct AMR data analysis","text":"Conducting AMR data analysis unfortunately requires -depth knowledge different scientific fields, makes hard right. least, requires: Good questions (always start !) reliable data thorough understanding (clinical) epidemiology, understand clinical epidemiological relevance possible bias results thorough understanding (clinical) microbiology/infectious diseases, understand microorganisms causal infections implications pharmaceutical treatment, well understanding intrinsic acquired microbial resistance Experience data analysis microbiological tests results, understand determination limitations MIC values interpretations SIR values Availability biological taxonomy microorganisms probably normalisation factors pharmaceuticals, defined daily doses (DDD) Available (inter-)national guidelines, profound methods apply course, instantly provide knowledge experience. AMR package, aimed providing (1) tools simplify antimicrobial resistance data cleaning, transformation analysis, (2) methods easily incorporate international guidelines (3) scientifically reliable reference data, including requirements mentioned . AMR package enables standardised reproducible AMR data analysis, application evidence-based rules, determination first isolates, translation various codes microorganisms antimicrobial agents, determination (multi-drug) resistant microorganisms, calculation antimicrobial resistance, prevalence future trends.","code":""},{"path":"https://amr-for-r.org/articles/AMR.html","id":"preparation","dir":"Articles","previous_headings":"","what":"Preparation","title":"Conduct AMR data analysis","text":"tutorial, create fake demonstration data work . can skip Cleaning data already data ready. start analysis, try make structure data generally look like :","code":""},{"path":"https://amr-for-r.org/articles/AMR.html","id":"needed-r-packages","dir":"Articles","previous_headings":"Preparation","what":"Needed R packages","title":"Conduct AMR data analysis","text":"many uses R, need additional packages AMR data analysis. package works closely together tidyverse packages dplyr ggplot2 RStudio. tidyverse tremendously improves way conduct data science - allows natural way writing syntaxes creating beautiful plots R. also use cleaner package, can used cleaning data creating frequency tables. AMR package contains data set example_isolates_unclean, might look data users extracted laboratory systems: AMR data analysis, like microorganism column contain valid, --date taxonomy, antibiotic columns cleaned SIR values well.","code":"library(dplyr) library(ggplot2) library(AMR) # (if not yet installed, install with:) # install.packages(c(\"dplyr\", \"ggplot2\", \"AMR\")) example_isolates_unclean #> # A tibble: 3,000 × 8 #> patient_id hospital date bacteria AMX AMC CIP GEN #> <chr> <chr> <date> <chr> <chr> <chr> <chr> <chr> #> 1 J3 A 2012-11-21 E. coli R I S S #> 2 R7 A 2018-04-03 K. pneumoniae R I S S #> 3 P3 A 2014-09-19 E. coli R S S S #> 4 P10 A 2015-12-10 E. coli S I S S #> 5 B7 A 2015-03-02 E. coli S S S S #> 6 W3 A 2018-03-31 S. aureus R S R S #> 7 J8 A 2016-06-14 E. coli R S S S #> 8 M3 A 2015-10-25 E. coli R S S S #> 9 J3 A 2019-06-19 E. coli S S S S #> 10 G6 A 2015-04-27 S. aureus S S S S #> # ℹ 2,990 more rows # we will use 'our_data' as the data set name for this tutorial our_data <- example_isolates_unclean"},{"path":"https://amr-for-r.org/articles/AMR.html","id":"taxonomy-of-microorganisms","dir":"Articles","previous_headings":"Preparation","what":"Taxonomy of microorganisms","title":"Conduct AMR data analysis","text":".mo(), users can transform arbitrary microorganism names codes current taxonomy. AMR package contains --date taxonomic data. specific, currently included data retrieved 24 Jun 2024. codes AMR packages come .mo() short, still human readable. importantly, .mo() supports kinds input: first character codes denote taxonomic kingdom, Bacteria (B), Fungi (F), Protozoa (P). AMR package also contain functions directly retrieve taxonomic properties, name, genus, species, family, order, even Gram-stain. start mo_ use .mo() internally, still arbitrary user input can used: Now can thus clean data: Apparently, uncertainty translation taxonomic codes. Let’s check : ’s good.","code":"as.mo(\"Klebsiella pneumoniae\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"K. pneumoniae\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"KLEPNE\") #> Class 'mo' #> [1] Line truncated
|
||||
[{"path":"https://amr-for-r.org/articles/AMR.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"Conduct AMR data analysis","text":"Conducting AMR data analysis unfortunately requires -depth knowledge different scientific fields, makes hard right. least, requires: Good questions (always start !) reliable data thorough understanding (clinical) epidemiology, understand clinical epidemiological relevance possible bias results thorough understanding (clinical) microbiology/infectious diseases, understand microorganisms causal infections implications pharmaceutical treatment, well understanding intrinsic acquired microbial resistance Experience data analysis microbiological tests results, understand determination limitations MIC values interpretations SIR values Availability biological taxonomy microorganisms probably normalisation factors pharmaceuticals, defined daily doses (DDD) Available (inter-)national guidelines, profound methods apply course, instantly provide knowledge experience. AMR package, aimed providing (1) tools simplify antimicrobial resistance data cleaning, transformation analysis, (2) methods easily incorporate international guidelines (3) scientifically reliable reference data, including requirements mentioned . AMR package enables standardised reproducible AMR data analysis, application evidence-based rules, determination first isolates, translation various codes microorganisms antimicrobial agents, determination (multi-drug) resistant microorganisms, calculation antimicrobial resistance, prevalence future trends.","code":""},{"path":"https://amr-for-r.org/articles/AMR.html","id":"preparation","dir":"Articles","previous_headings":"","what":"Preparation","title":"Conduct AMR data analysis","text":"tutorial, create fake demonstration data work . can skip Cleaning data already data ready. start analysis, try make structure data generally look like :","code":""},{"path":"https://amr-for-r.org/articles/AMR.html","id":"needed-r-packages","dir":"Articles","previous_headings":"Preparation","what":"Needed R packages","title":"Conduct AMR data analysis","text":"many uses R, need additional packages AMR data analysis. package works closely together tidyverse packages dplyr ggplot2 RStudio. tidyverse tremendously improves way conduct data science - allows natural way writing syntaxes creating beautiful plots R. also use cleaner package, can used cleaning data creating frequency tables. AMR package contains data set example_isolates_unclean, might look data users extracted laboratory systems: AMR data analysis, like microorganism column contain valid, --date taxonomy, antibiotic columns cleaned SIR values well.","code":"library(dplyr) library(ggplot2) library(AMR) # (if not yet installed, install with:) # install.packages(c(\"dplyr\", \"ggplot2\", \"AMR\")) example_isolates_unclean #> # A tibble: 3,000 × 8 #> patient_id hospital date bacteria AMX AMC CIP GEN #> <chr> <chr> <date> <chr> <chr> <chr> <chr> <chr> #> 1 J3 A 2012-11-21 E. coli R I S S #> 2 R7 A 2018-04-03 K. pneumoniae R I S S #> 3 P3 A 2014-09-19 E. coli R S S S #> 4 P10 A 2015-12-10 E. coli S I S S #> 5 B7 A 2015-03-02 E. coli S S S S #> 6 W3 A 2018-03-31 S. aureus R S R S #> 7 J8 A 2016-06-14 E. coli R S S S #> 8 M3 A 2015-10-25 E. coli R S S S #> 9 J3 A 2019-06-19 E. coli S S S S #> 10 G6 A 2015-04-27 S. aureus S S S S #> # ℹ 2,990 more rows # we will use 'our_data' as the data set name for this tutorial our_data <- example_isolates_unclean"},{"path":"https://amr-for-r.org/articles/AMR.html","id":"taxonomy-of-microorganisms","dir":"Articles","previous_headings":"Preparation","what":"Taxonomy of microorganisms","title":"Conduct AMR data analysis","text":".mo(), users can transform arbitrary microorganism names codes current taxonomy. AMR package contains --date taxonomic data. specific, currently included data retrieved 24 Jun 2024. codes AMR packages come .mo() short, still human readable. importantly, .mo() supports kinds input: first character codes denote taxonomic kingdom, Bacteria (B), Fungi (F), Protozoa (P). AMR package also contain functions directly retrieve taxonomic properties, name, genus, species, family, order, even Gram-stain. start mo_ use .mo() internally, still arbitrary user input can used: Now can thus clean data: Apparently, uncertainty translation taxonomic codes. Let’s check : ’s good.","code":"as.mo(\"Klebsiella pneumoniae\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"K. pneumoniae\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"KLEPNE\") #> Class 'mo' #> [1] Line truncated
|
||||
Reference in new issue
Block a user