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<h1 class="title toc-ignore">Description of a categorical or continuous variable with qualitative and quantitative data</h1>
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<p>The first method of the <strong>Automatic Univariate Description</strong> submenu is the description of either continuous or categorical variable by both continuous and categorical variables. <img src="images/catdes1.png" width="80%" style="display: block; margin: auto auto auto 0;" /> <br><br /></p>
<div id="the-interface" class="section level2">
<h2><strong>The interface</strong></h2>
<p>As it can be seen in the figure above, the interface is very simple and only has 3 fields you need to worry about. <br><br /> <img src="images/catdes2.png" width="60%" style="display: block; margin: auto auto auto 0;" /> Firstly, the <strong><em>Variable to Characterize</em></strong> take either a continuous or categorical variable that you wish to describe. Then, you put the continuous and categorical variables you want to use for the characterization of the variable. Lastly, the <strong><em>Significance threshold</em></strong> option set the threshold under which a variable is significantly describing the variable to characterize. <br><br /></p>
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<h2><strong>Examples</strong></h2>
<p>There are two ways of using this methods. You can either use it to see what variables are significantly describing the variable to characterize or you can set the <strong><em>Significance threshold</em></strong> to 100 so that you have the indicators (R², correlation, etc.) for all the variables.<br />
For the following examples, we will be using the bugs data set (available with Jamovi): <img src="images/catdesbugs.png" width="80%" style="display: block; margin: auto auto auto 0;" /> <br><br /></p>
<div id="description-of-a-continuous-variable" class="section level3">
<h3>Description of a continuous variable</h3>
<p>For this example we are going to describe the LDLF variable using all the other variables (except Subject) and let the default value for the <strong><em>Significance threshold</em></strong>: <img src="images/catdesex1.png" width="50%" style="display: block; margin: auto auto auto 0;" /> <img src="images/catdesexres1.png" width="50%" style="display: block; margin: auto auto auto 0;" /> <br><br /></p>
<p>We can see that for a threshold of 0.05, none of the categorical variable significantly describe the LDFL variable. However, the 3 continuous variables are significantly correlated (for a threshold of 0.05) to LDLF with correlations between 0.5 and 0.6. <br><br /></p>
<p>Now, let’s set the <strong><em>Significance threshold</em></strong> to 100 to get a complete description of the variable. <img src="images/catdesexres2.png" width="60%" style="display: block; margin: auto auto auto 0;" /><img src="images/catdesexres3.png" width="60%" style="display: block; margin: auto auto auto 0;" /> <br><br /></p>
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<h3>Description of a categorical variable</h3>
<p>Let’s describe the gender variable and set the threshold to 100 to see all the output.</p>
<p><img src="images/catdesexres4.png" width="60%" style="display: block; margin: auto auto auto 0;" /><img src="images/catdesexres5.png" width="60%" style="display: block; margin: auto auto auto 0;" /><img src="images/catdesexres6.png" width="60%" style="display: block; margin: auto auto auto 0;" /> <br><br /></p>
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