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    <title>topic Re: Classification table proc logistic in SAS Procedures</title>
    <link>https://communities.sas.com/t5/SAS-Procedures/Classification-table-proc-logistic/m-p/238637#M55441</link>
    <description>&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks,&amp;nbsp;&lt;SPAN class="login-bold"&gt;&lt;A href="https://communities.sas.com/t5/user/viewprofilepage/user-id/13884" target="_self"&gt;ballardw&lt;/A&gt;!&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;U&gt;&lt;SPAN&gt;You don't indicate what your variables represent&lt;/SPAN&gt;&lt;/U&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;The variables are numeric with 1 for 'Yes' and 0 for 'No'.&lt;/P&gt;&lt;P&gt;Also t&lt;SPAN&gt;he removing of parameters that are not statistically significant is performed by&lt;/SPAN&gt;&lt;STRONG&gt; SELECTION=stepwise.&lt;/STRONG&gt;&lt;/P&gt;</description>
    <pubDate>Thu, 10 Dec 2015 07:52:48 GMT</pubDate>
    <dc:creator>Ektchup</dc:creator>
    <dc:date>2015-12-10T07:52:48Z</dc:date>
    <item>
      <title>Classification table proc logistic</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/Classification-table-proc-logistic/m-p/238517#M55437</link>
      <description>&lt;P&gt;Hi all,&lt;/P&gt;&lt;P&gt;I&amp;nbsp;use PROC LOGISTIC to to find the most predictive combination of parameters(model) for diagnosis. The code is below:&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;%let list_param = AP01 AP02 AP03 AP04 AP05 AP06 AP07 AP08 AP09 AP10 AP11 AP12 AP13 AP14 AP15 AP16 AP17 AP18 AP19 AP20&lt;BR /&gt;AP21 AP22 AP23 AP24 AP25 AP26 AP27 AP28 AI01 AI02 AI03 AI04 AI05 AI06 AI07 AI08 AI09 AI10 AI11 AI12&lt;BR /&gt;AI13 AI14 AI15 AI16 AI17 AI18 AI19 AI20 AI21;&lt;/P&gt;&lt;P&gt;&lt;BR /&gt;&lt;STRONG&gt;proc logistic data= Source plots(only)= roc; &lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;class reasvis;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;model acrstat = &amp;amp;list_param. age sexn reasvis/ CTABLE pprob=0.5 SELECTION=stepwise;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;output out=probs6 PREDPROBS= i;&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;run;&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;acrstat -&amp;nbsp;&lt;/STRONG&gt;is dependent variable with values if the diagnosis is or no.&lt;/P&gt;&lt;P&gt;Predictors - list of parameters - &amp;amp;list_param, age, sex&lt;STRONG&gt; -&amp;nbsp;&lt;/STRONG&gt;all n umeric variables,&amp;nbsp;&lt;STRONG&gt;reasvis -&amp;nbsp;&lt;/STRONG&gt;character variable.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;And there are only 9 patients with diagnosis and 320 without it (Total number of subjects - 329) in Source dataset.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;And&amp;nbsp;I have some problems with it - actually&amp;nbsp;procedure&amp;nbsp;predicts that no diagnosis will occur. I think it is becouse of small amount of subjects with diagnosis.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;BR /&gt;&lt;SPAN style="line-height: 20px;"&gt;But is it possible to find the model which will predict the occurance of diagnosis?&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;Thanks.&lt;/P&gt;</description>
      <pubDate>Wed, 09 Dec 2015 15:45:55 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/Classification-table-proc-logistic/m-p/238517#M55437</guid>
      <dc:creator>Ektchup</dc:creator>
      <dc:date>2015-12-09T15:45:55Z</dc:date>
    </item>
    <item>
      <title>Re: Classification table proc logistic</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/Classification-table-proc-logistic/m-p/238527#M55438</link>
      <description>&lt;P&gt;The large number of variables is perhaps a factor as well. When you look at the 9 diagnosis and all of the variables in the model to any 2 have the same factors? You don't indicate what your variables represent but if they are all of a "yes/no" or "Present/not present" it should be easy to check. If none of them have any in common then I wouldn't be surprised.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You could examine using Selection=Score see if any of the subsets do very well.&lt;/P&gt;</description>
      <pubDate>Wed, 09 Dec 2015 16:17:52 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/Classification-table-proc-logistic/m-p/238527#M55438</guid>
      <dc:creator>ballardw</dc:creator>
      <dc:date>2015-12-09T16:17:52Z</dc:date>
    </item>
    <item>
      <title>Re: Classification table proc logistic</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/Classification-table-proc-logistic/m-p/238546#M55439</link>
      <description>&lt;P&gt;This is a logistic regression model with a small event rate. There are some known ways to deal with this, including assiging prior probabiliites via a Bayesian methodology.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;A href="http://stats.stackexchange.com/questions/10236/applying-logistic-regression-with-low-event-rate" target="_blank"&gt;http://stats.stackexchange.com/questions/10236/applying-logistic-regression-with-low-event-rate&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You can find a better model by removing some variables that don't add value to the regression.&lt;/P&gt;</description>
      <pubDate>Wed, 09 Dec 2015 18:03:16 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/Classification-table-proc-logistic/m-p/238546#M55439</guid>
      <dc:creator>Reeza</dc:creator>
      <dc:date>2015-12-09T18:03:16Z</dc:date>
    </item>
    <item>
      <title>Re: Classification table proc logistic</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/Classification-table-proc-logistic/m-p/238636#M55440</link>
      <description>&lt;P&gt;HI,&amp;nbsp;&lt;A href="https://communities.sas.com/t5/user/viewprofilepage/user-id/13879" target="_self"&gt;&lt;SPAN class="login-bold"&gt;Reeza&lt;/SPAN&gt;&lt;/A&gt;&lt;/P&gt;&lt;P&gt;Thanks.&lt;/P&gt;&lt;P&gt;The removing of parameters that are not statistically significant is performed by&lt;STRONG&gt; SELECTION=stepwise &lt;/STRONG&gt;option&lt;STRONG&gt;.&amp;nbsp;&lt;/STRONG&gt;But despite on this I get the classification table without predicted diagnosis.&lt;/P&gt;</description>
      <pubDate>Thu, 10 Dec 2015 07:41:49 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/Classification-table-proc-logistic/m-p/238636#M55440</guid>
      <dc:creator>Ektchup</dc:creator>
      <dc:date>2015-12-10T07:41:49Z</dc:date>
    </item>
    <item>
      <title>Re: Classification table proc logistic</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/Classification-table-proc-logistic/m-p/238637#M55441</link>
      <description>&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks,&amp;nbsp;&lt;SPAN class="login-bold"&gt;&lt;A href="https://communities.sas.com/t5/user/viewprofilepage/user-id/13884" target="_self"&gt;ballardw&lt;/A&gt;!&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;U&gt;&lt;SPAN&gt;You don't indicate what your variables represent&lt;/SPAN&gt;&lt;/U&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;The variables are numeric with 1 for 'Yes' and 0 for 'No'.&lt;/P&gt;&lt;P&gt;Also t&lt;SPAN&gt;he removing of parameters that are not statistically significant is performed by&lt;/SPAN&gt;&lt;STRONG&gt; SELECTION=stepwise.&lt;/STRONG&gt;&lt;/P&gt;</description>
      <pubDate>Thu, 10 Dec 2015 07:52:48 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/Classification-table-proc-logistic/m-p/238637#M55441</guid>
      <dc:creator>Ektchup</dc:creator>
      <dc:date>2015-12-10T07:52:48Z</dc:date>
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