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<title>How to conduct AMR data analysis • AMR (for R)</title>
<title>Conduct AMR data analysis • AMR (for R)</title>
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<img src="../logo.svg" class="logo" alt=""><h1>How to conduct AMR data analysis</h1>
<img src="../logo.svg" class="logo" alt=""><h1>Conduct AMR data analysis</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/AMR.Rmd" class="external-link"><code>vignettes/AMR.Rmd</code></a></small>
@ -1147,8 +1147,8 @@ incidence and antimicrobial susceptibility patterns.</p>
</tr></thead>
<tbody><tr class="odd">
<td align="left">69.4% (64.3-74.3%)</td>
<td align="left">92.6% (91.2-93.8%)</td>
<td align="left">88.7% (85.9-91.2%)</td>
<td align="left">92.6% (91.1-93.9%)</td>
<td align="left">88.7% (85.8-91.2%)</td>
</tr></tbody>
</table>
<p>WISCA uses a <strong>Bayesian decision model</strong> to integrate
@ -1190,57 +1190,57 @@ function on a grouped <code>tibble</code>, i.e., using
<td align="left">0-24</td>
<td align="left">F</td>
<td align="left">56.6% (25.2-83.9%)</td>
<td align="left">74% (50.5-91.9%)</td>
<td align="left">68% (39.7-88.9%)</td>
<td align="left">73.6% (48-91.6%)</td>
<td align="left">68.6% (42.9-89.5%)</td>
</tr>
<tr class="even">
<td align="left">0-24</td>
<td align="left">M</td>
<td align="left">60.3% (28.4-87.1%)</td>
<td align="left">79.3% (59.5-94.2%)</td>
<td align="left">60.1% (29.3-87.5%)</td>
<td align="left">79.7% (57.6-94.2%)</td>
<td align="left">60.1% (29.5-87.7%)</td>
</tr>
<tr class="odd">
<td align="left">25-49</td>
<td align="left">F</td>
<td align="left">66.6% (45.6-85.5%)</td>
<td align="left">91.8% (85.1-96.5%)</td>
<td align="left">82.6% (66.7-93.9%)</td>
<td align="left">91.7% (84.6-96.7%)</td>
<td align="left">83% (67.9-94%)</td>
</tr>
<tr class="even">
<td align="left">25-49</td>
<td align="left">M</td>
<td align="left">56.4% (29.1-81.7%)</td>
<td align="left">89.5% (80-95.6%)</td>
<td align="left">72.2% (47.1-90%)</td>
<td align="left">89.2% (80.3-95.7%)</td>
<td align="left">72.4% (49.7-90%)</td>
</tr>
<tr class="odd">
<td align="left">50-74</td>
<td align="left">F</td>
<td align="left">67.8% (55.8-80.1%)</td>
<td align="left">95.6% (93.2-97.7%)</td>
<td align="left">88% (80.2-94.2%)</td>
<td align="left">95.6% (93.2-97.5%)</td>
<td align="left">88.1% (80.4-94.6%)</td>
</tr>
<tr class="even">
<td align="left">50-74</td>
<td align="left">M</td>
<td align="left">66.2% (54.8-75.8%)</td>
<td align="left">95.3% (92.5-97.4%)</td>
<td align="left">84.2% (75.2-92.4%)</td>
<td align="left">95.2% (92.4-97.4%)</td>
<td align="left">84.4% (74.4-92.5%)</td>
</tr>
<tr class="odd">
<td align="left">75+</td>
<td align="left">F</td>
<td align="left">71.7% (61-81.7%)</td>
<td align="left">96.5% (94.4-98.2%)</td>
<td align="left">90.7% (84.4-95.7%)</td>
<td align="left">96.6% (94.4-98.2%)</td>
<td align="left">90.6% (84.6-95.3%)</td>
</tr>
<tr class="even">
<td align="left">75+</td>
<td align="left">M</td>
<td align="left">72.9% (63.8-82%)</td>
<td align="left">96.6% (94.5-98.1%)</td>
<td align="left">92.8% (87.6-96.3%)</td>
<td align="left">96.6% (94.6-98.1%)</td>
<td align="left">92.8% (87.8-96.5%)</td>
</tr>
</tbody>
</table>