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    <title>topic Re: Logistic regression - &amp;quot;unique profiles&amp;quot; in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Logistic-regression-quot-unique-profiles-quot/m-p/278906#M14726</link>
    <description>&lt;PRE&gt;
1)Maybe you missed some important independent variables .
2)Maybe the Scale for independent variable is too small . E.X. the dose of medication :  1ml v.s  100ml . 
   Check PROC LOGISTIC 's  UNIT statement.
3)Maybe there are some none-linear effect between  independent variable and dependent variables.
  Check PROC LOGISTIC 's  EFFECT statement.

4)Why not use Decision Tree or Random Forest in R ?
&lt;/PRE&gt;</description>
    <pubDate>Tue, 21 Jun 2016 02:52:00 GMT</pubDate>
    <dc:creator>Ksharp</dc:creator>
    <dc:date>2016-06-21T02:52:00Z</dc:date>
    <item>
      <title>Logistic regression - "unique profiles"</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Logistic-regression-quot-unique-profiles-quot/m-p/278662#M14709</link>
      <description>&lt;P&gt;Hello,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I am doing logistic regression in R on a binary dependent variable with only one independent variable. I found the odd ratio as 0.99 for an outcomes.&amp;nbsp;This can be shown in following. Odds ratio is defined as,&amp;nbsp;ratio_odds(H) = Probability(X=H) / (1-Probability(X=H)). As given earlier ratio_odds (H) = 0.99 which implies that the probability (X=H) = 0.497 which is close to 50% probability. This implies that the probability for having a H cases or non H cases 50% under the given condition of independent variable. This does not seem realistic from the data as only ~20% are found as H cases. Please give clarifications and proper explanations&amp;nbsp;of this kind of cases in logistic regression.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks all for your help!&lt;/P&gt;</description>
      <pubDate>Mon, 20 Jun 2016 13:16:17 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Logistic-regression-quot-unique-profiles-quot/m-p/278662#M14709</guid>
      <dc:creator>saurabh1</dc:creator>
      <dc:date>2016-06-20T13:16:17Z</dc:date>
    </item>
    <item>
      <title>Re: Logistic regression - "unique profiles"</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Logistic-regression-quot-unique-profiles-quot/m-p/278676#M14711</link>
      <description>&lt;P&gt;If you're using R, why are you posting to a SAS forum? Casting a wider net for an answer to your question?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;IMO a question like this should be posted on stats.stackexchange.com&lt;/P&gt;</description>
      <pubDate>Mon, 20 Jun 2016 13:47:09 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Logistic-regression-quot-unique-profiles-quot/m-p/278676#M14711</guid>
      <dc:creator>Reeza</dc:creator>
      <dc:date>2016-06-20T13:47:09Z</dc:date>
    </item>
    <item>
      <title>Re: Logistic regression - "unique profiles"</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Logistic-regression-quot-unique-profiles-quot/m-p/278906#M14726</link>
      <description>&lt;PRE&gt;
1)Maybe you missed some important independent variables .
2)Maybe the Scale for independent variable is too small . E.X. the dose of medication :  1ml v.s  100ml . 
   Check PROC LOGISTIC 's  UNIT statement.
3)Maybe there are some none-linear effect between  independent variable and dependent variables.
  Check PROC LOGISTIC 's  EFFECT statement.

4)Why not use Decision Tree or Random Forest in R ?
&lt;/PRE&gt;</description>
      <pubDate>Tue, 21 Jun 2016 02:52:00 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Logistic-regression-quot-unique-profiles-quot/m-p/278906#M14726</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2016-06-21T02:52:00Z</dc:date>
    </item>
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