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    <title>topic how to analyze logistic regression with low sample size in SAS Procedures</title>
    <link>https://communities.sas.com/t5/SAS-Procedures/how-to-analyze-logistic-regression-with-low-sample-size/m-p/554342#M74665</link>
    <description>&lt;P&gt;Hi all,&lt;/P&gt;&lt;P&gt;I have a data set with 423 pts but have only 10 pts with required outcome (Visit = 1 for Hospital visit and Visit = 0 for no hospital visit). I am trying to evaluate independent predictors for Hospital visit&amp;nbsp; (Visit = 1). When I ran the logistic regression, some of the variables of interest have 95% CI values &amp;gt;999.999. How to handle such situations? And whether to include such variables in the logistic regression model or not?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you in advance!&lt;/P&gt;&lt;DIV class="branch"&gt;&lt;DIV align="center"&gt;&amp;nbsp;&lt;/DIV&gt;&lt;/DIV&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Fri, 26 Apr 2019 16:58:11 GMT</pubDate>
    <dc:creator>sms1891</dc:creator>
    <dc:date>2019-04-26T16:58:11Z</dc:date>
    <item>
      <title>how to analyze logistic regression with low sample size</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/how-to-analyze-logistic-regression-with-low-sample-size/m-p/554342#M74665</link>
      <description>&lt;P&gt;Hi all,&lt;/P&gt;&lt;P&gt;I have a data set with 423 pts but have only 10 pts with required outcome (Visit = 1 for Hospital visit and Visit = 0 for no hospital visit). I am trying to evaluate independent predictors for Hospital visit&amp;nbsp; (Visit = 1). When I ran the logistic regression, some of the variables of interest have 95% CI values &amp;gt;999.999. How to handle such situations? And whether to include such variables in the logistic regression model or not?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you in advance!&lt;/P&gt;&lt;DIV class="branch"&gt;&lt;DIV align="center"&gt;&amp;nbsp;&lt;/DIV&gt;&lt;/DIV&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Fri, 26 Apr 2019 16:58:11 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/how-to-analyze-logistic-regression-with-low-sample-size/m-p/554342#M74665</guid>
      <dc:creator>sms1891</dc:creator>
      <dc:date>2019-04-26T16:58:11Z</dc:date>
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    <item>
      <title>Re: how to analyze logistic regression with low sample size</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/how-to-analyze-logistic-regression-with-low-sample-size/m-p/554346#M74668</link>
      <description>&lt;P&gt;When you have a response variable which is a rare event, often the solution is to oversample the data, and then run PROC LOGISTIC, and then transform the results back to the non-oversampled space. Here's a tutorial: &lt;A href="http://support.sas.com/kb/22/601.html" target="_blank"&gt;http://support.sas.com/kb/22/601.html&lt;/A&gt;&lt;/P&gt;</description>
      <pubDate>Fri, 26 Apr 2019 17:04:27 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/how-to-analyze-logistic-regression-with-low-sample-size/m-p/554346#M74668</guid>
      <dc:creator>PaigeMiller</dc:creator>
      <dc:date>2019-04-26T17:04:27Z</dc:date>
    </item>
    <item>
      <title>Re: how to analyze logistic regression with low sample size</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/how-to-analyze-logistic-regression-with-low-sample-size/m-p/554587#M74681</link>
      <description>&lt;P&gt;Try Exact Logistic Model or Penalty Logistic Model.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;There are some examples in documentation.&lt;/P&gt;</description>
      <pubDate>Sun, 28 Apr 2019 14:49:58 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/how-to-analyze-logistic-regression-with-low-sample-size/m-p/554587#M74681</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2019-04-28T14:49:58Z</dc:date>
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