<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Re: Confidence Interval in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Confidence-Interval/m-p/416181#M21853</link>
    <description>&lt;P&gt;You can't, because the model selection process itself&amp;nbsp;biasses the model fit and estimates&amp;nbsp;statistics.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;From the documentation:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;The QUANTSELECT procedure is intended primarily as an effect selection
 procedure and does not include regression diagnostics and hypothesis
 testing. The intention is that you use the QUANTSELECT procedure to select
 a model or a set of models, where each model contains a set of selected
 effects, and then you can further investigate these models by using PROC
 QUANTREG or other analytic tools.&lt;/PRE&gt;
&lt;P&gt;Use proc quantreg with your selected model(s) to get confidence intervals.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Sun, 26 Nov 2017 06:33:39 GMT</pubDate>
    <dc:creator>PGStats</dc:creator>
    <dc:date>2017-11-26T06:33:39Z</dc:date>
    <item>
      <title>Confidence Interval</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Confidence-Interval/m-p/416167#M21852</link>
      <description>&lt;P&gt;How do&amp;nbsp;I calculate confidence intervals in Quantselect?&lt;/P&gt;</description>
      <pubDate>Sat, 25 Nov 2017 21:04:06 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Confidence-Interval/m-p/416167#M21852</guid>
      <dc:creator>cricesd</dc:creator>
      <dc:date>2017-11-25T21:04:06Z</dc:date>
    </item>
    <item>
      <title>Re: Confidence Interval</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Confidence-Interval/m-p/416181#M21853</link>
      <description>&lt;P&gt;You can't, because the model selection process itself&amp;nbsp;biasses the model fit and estimates&amp;nbsp;statistics.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;From the documentation:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;The QUANTSELECT procedure is intended primarily as an effect selection
 procedure and does not include regression diagnostics and hypothesis
 testing. The intention is that you use the QUANTSELECT procedure to select
 a model or a set of models, where each model contains a set of selected
 effects, and then you can further investigate these models by using PROC
 QUANTREG or other analytic tools.&lt;/PRE&gt;
&lt;P&gt;Use proc quantreg with your selected model(s) to get confidence intervals.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Sun, 26 Nov 2017 06:33:39 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Confidence-Interval/m-p/416181#M21853</guid>
      <dc:creator>PGStats</dc:creator>
      <dc:date>2017-11-26T06:33:39Z</dc:date>
    </item>
    <item>
      <title>Re: Confidence Interval</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Confidence-Interval/m-p/416198#M21854</link>
      <description>&lt;P&gt;Thank you for your reply. So, if I want to use L1-norm (LASSO) regularized quantile regression for my data analysis, is there another SAS program that I shoud be using? I need to get shrinkage on the estimates. Apparently QUANTSELECT only uses LASSO for the model selection and&amp;nbsp;then refits the model 'without penalty'.&lt;/P&gt;</description>
      <pubDate>Sun, 26 Nov 2017 14:50:06 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Confidence-Interval/m-p/416198#M21854</guid>
      <dc:creator>cricesd</dc:creator>
      <dc:date>2017-11-26T14:50:06Z</dc:date>
    </item>
  </channel>
</rss>

