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@@ -532,7 +532,7 @@ <h1 class="title">Hierarchical Linear Regression (Radon Contamination dataset)</
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-<p>In this notebook we want to revisit the classical hierarchical linear regression model based on the dataset of the <em>Radon Contamination</em> by Gelman and Hill. In particular, we want to show how easy is to port the <a href="https://docs.pymc.io/en/v3/">PyMC</a> models, presented in the very complete article <a href="https://docs.pymc.io/projects/examples/en/latest/case_studies/multilevel_modeling.html">A Primer on Bayesian Methods for Multilevel Modeling</a>, to <a href="https://bambinos.github.io/bambi/main/index.html">Bambi</a> using the more concise formula specification for the models.</p>
+<p>In this notebook we want to revisit the classical hierarchical linear regression model based on the dataset of the <em>Radon Contamination</em> by Gelman and Hill. In particular, we want to show how easy is to port the <a href="https://docs.pymc.io/en/v3/">PyMC</a> models, presented in the very complete article <a href="https://docs.pymc.io/projects/examples/en/latest/case_studies/multilevel_modeling.html">A Primer on Bayesian Methods for Multilevel Modeling</a>, to <a href="https://bambinos.github.io/bambi/notebooks/">Bambi</a> using the more concise formula specification for the models.</p>
 <p>This example has been ported from PyMC by Juan Orduz (<a href="https://github.com/juanitorduz">@juanitorduz</a>) and Bambi developers.</p>
 <section id="prepare-notebook" class="level2">
 <h2 class="anchored" data-anchor-id="prepare-notebook">Prepare Notebook</h2>