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#variableselection

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Dr Mircea Zloteanu ☀️ 🌊🌴<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statstab</span></a> #380 Variable Importance Plots {vip} </p><p>Thoughts: Not sure how useful these are for researchers, but it's one way to plot the "importance" of your model.</p><p><a href="https://mastodon.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://mastodon.social/tags/lasso" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>lasso</span></a> <a href="https://mastodon.social/tags/ML" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ML</span></a> <a href="https://mastodon.social/tags/regression" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>regression</span></a> <a href="https://mastodon.social/tags/vip" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vip</span></a> <a href="https://mastodon.social/tags/variableselection" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>variableselection</span></a> <a href="https://mastodon.social/tags/r" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>r</span></a></p><p><a href="https://koalaverse.github.io/vip/articles/vip.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">koalaverse.github.io/vip/artic</span><span class="invisible">les/vip.html</span></a></p>
Jan R. Boehnke<p>Essay on "Principles of confounder selection":<br><a href="https://link.springer.com/article/10.1007/s10654-019-00494-6" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">link.springer.com/article/10.1</span><span class="invisible">007/s10654-019-00494-6</span></a></p><p>"[...] the following proposal is made for covariate control decisions: control for each covariate that is a cause of the exposure, or of the outcome, or of both; exclude from this set any variable known to be an instrumental variable; and include as a covariate any proxy for an unmeasured variable that is a common cause of both the exposure and the outcome."</p><p><a href="https://mastodon.social/tags/VariableSelection" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VariableSelection</span></a> <a href="https://mastodon.social/tags/Causality" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Causality</span></a></p>
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