<p><strong>This reply illustrates a search <em>strategy</em> by means of an example.</strong>  The strategy consists of an iterative procedure whose objectives are, in order,</p>
<ol>
<li><strong>Discover appropriate key words</strong> and search terms to include.</li>
<li><strong>Find questions and answers related to these terms</strong>.  Mine them for related terms (which might be new or unfamiliar: that's ok).</li>
<li><strong>Refine the search</strong> by including and excluding related terms, as appropriate.
<ul>
<li>Examine top hits by relevance and, separately, by voting.</li>
<li>When there are still too many hits, limit them by asking for posts with positive upvotes (using the keyword <code>score:1</code>).</li>
</ul>
</li>
<li><strong>Repeat</strong> as necessary.</li>
</ol>
<p>If you are the original proposer of the question, this activity--which usually takes less than a minute--often will answer your question.  But if it does not, it likely will help you <em>ask</em> your question in a clearer and more focused way, which will help us <em>answer</em> the question you came to the site with.</p>
<p>If you are a reviewer, this activity often identifies interpretations you might not have considered upon a first reading, enabling you to guide the OP to clarify their question.  Sometimes it will turn up existing answers and you can vote to close the current post as a duplicate.</p>
<hr />
<h3>Searching comments (optional)</h3>
<p>To construct this example, I needed to find threads on our site where I, user &quot;whuber,&quot; had recommended or mentioned searches.  Because such recommendations would occur primarily in comments, and comments are not targeted by the site search engine, I started with <a href="https://www.google.com/search" rel="nofollow noreferrer">Google</a>.  As you likely know, you can focus any Google search on a specified site using <code>site:</code> syntax, as in</p>
<pre><code>site:stats.stackexchange.com whuber search
</code></pre>
<p>This input requested a search of all pages served at our site that include both &quot;whuber&quot; and &quot;search.&quot;</p>
<h3>Carrying out the site search strategy</h3>
<p>The first hit in this Google search is a closed thread at <a href="https://stats.stackexchange.com/questions/351443">https://stats.stackexchange.com/questions/351443</a> about &quot;MLR.&quot;  The sequence of interactions with the original poster (OP) went like this:</p>
<ol>
<li><p><strong>Discover key words.</strong> I posted a comment asking for an explanation of what &quot;MLR&quot; was intended to mean, along with a suggestion about one possible interpretation.</p>
<ul>
<li>It's often a good idea to ask posters for clarification rather than assuming you know what they intended (unless you are very good at asynchronous long-distance mind reading).</li>
<li>However, sometimes unclear acronyms can be resolved by searching the web for the acronym along with the term &quot;statistics&quot; or &quot;mathematics.&quot;  In this case, the hits make it clear that <a href="https://www.google.com/search?q=mlr+statistics" rel="nofollow noreferrer">MLR really does mean multiple regression</a>.  It looks like I didn't take the time to do this search before I commented, <em>mea culpa.</em></li>
<li>The OP patiently confirmed this interpretation in a comment.</li>
</ul>
</li>
<li><p><strong>Conduct a broad site search.</strong>  I recommended searching on the<code>multiple-regression</code> tag along with keywords like &quot;rank,&quot; which was suggested by <em>terms used by the OP in their original question formulation.</em>  I couldn't do much more than this because grammatical distortions in the question statement made it unclear what the specific question might be.  <a href="https://stats.stackexchange.com/search?q=multiple-regression+rank">The search returned hundreds of results.</a></p>
</li>
<li><p><strong>Use initial results to refine the search.</strong> This involves several tactics:</p>
<ul>
<li><strong>Sort the results by relevance and then by votes</strong>: both have their advantages.</li>
<li><strong>Skim through the first few hits to identify related keywords</strong> or other technical terms that are relevant to the question.</li>
<li>When there are many results, <strong>skim through the first page or two of hits to identify <em>unrelated</em> keywords</strong> that can be used to exclude irrelevant hits.  A common example is to exclude &quot;logistic&quot; when the focus is on ordinary regression, by including <code>-logistic</code> in the search term.</li>
<li>In this case, <a href="https://stats.stackexchange.com/questions/35071">one highly voted thread</a> refers to &quot;rank deficiency&quot; and several highly-voted threads refer to &quot;multicollinearity.&quot;</li>
</ul>
</li>
</ol>
<p>This already is progress: a tiny bit of searching will have revealed useful keywords <em>that even a novice can use to find an answer,</em> whether or not they are familiar with those terms.</p>
<hr />
<p>Today these initial results, along with a review of the original question, suggest simply adding the keyword &quot;unique&quot; to the search and focusing on upvoted posts.  The search expression becomes <code>multiple-regression rank unique score:1</code>.</p>
<ul>
<li><p>Top hits (by relevance) indicate that &quot;regularization&quot; and &quot;identifiability&quot; might be useful keywords for subsequent searches.  An <a href="https://stats.stackexchange.com/questions/142314/identifiability-of-the-linear-regression-model-necessary-and-sufficient-conditi/142341#142341">identifiability post</a> might contain an answer, or at least provide useful information to help the OP formulate and refine their question.</p>
</li>
<li><p>A top hit by votes turned up a <a href="https://stats.stackexchange.com/questions/21022/does-the-order-of-explanatory-variables-matter-when-calculating-their-regression/21136#21136">nice mathematical analysis of least squares solutions</a> which, if the OP is of a mathematical bent, might also answer their question.</p>
</li>
</ul>
