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    <title>topic proc logistic with only categorial var in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/proc-logistic-with-only-categorial-var/m-p/781178#M38351</link>
    <description>&lt;P&gt;How to model binary response with only categorial explanatory variables?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;The syntax wont let it happen after "model y = ", which doesn't make any sense at all.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;And where do I check weight of each categorial var value?&amp;nbsp; cant see any of them in proc logistic result, does that mean no var in class is selected? which doesn't make any sense twice at all.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;upset enough...&amp;nbsp;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Fri, 19 Nov 2021 03:22:18 GMT</pubDate>
    <dc:creator>kimmygzc</dc:creator>
    <dc:date>2021-11-19T03:22:18Z</dc:date>
    <item>
      <title>proc logistic with only categorial var</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/proc-logistic-with-only-categorial-var/m-p/781178#M38351</link>
      <description>&lt;P&gt;How to model binary response with only categorial explanatory variables?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;The syntax wont let it happen after "model y = ", which doesn't make any sense at all.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;And where do I check weight of each categorial var value?&amp;nbsp; cant see any of them in proc logistic result, does that mean no var in class is selected? which doesn't make any sense twice at all.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;upset enough...&amp;nbsp;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Fri, 19 Nov 2021 03:22:18 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/proc-logistic-with-only-categorial-var/m-p/781178#M38351</guid>
      <dc:creator>kimmygzc</dc:creator>
      <dc:date>2021-11-19T03:22:18Z</dc:date>
    </item>
    <item>
      <title>Re: proc logistic with only categorial var</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/proc-logistic-with-only-categorial-var/m-p/781180#M38352</link>
      <description>&lt;P&gt;You can use continuous and/or categorical predictor variables in the model. Categorical predictors should be specified in the CLASS statement as well as the MODEL statement. The CLASS statement tells the procedure to create a set of numerically-coded variables to represent the original variable in the model. See the &lt;A href="https://go.documentation.sas.com/doc/en/pgmsascdc/9.4_3.5/statug/statug_logistic_examples02.htm" target="_self"&gt;example&lt;/A&gt; titled "Logistic Modeling with Categorical Predictors" in the LOGISTIC documentation. By "weights", I assume you mean the parameter estimates of the model. Those are in the Estimate column of the&amp;nbsp;Analysis of Maximum Likelihood Estimates table in the LOGISTIC output.&lt;/P&gt;</description>
      <pubDate>Fri, 19 Nov 2021 03:31:54 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/proc-logistic-with-only-categorial-var/m-p/781180#M38352</guid>
      <dc:creator>StatDave</dc:creator>
      <dc:date>2021-11-19T03:31:54Z</dc:date>
    </item>
    <item>
      <title>Re: proc logistic with only categorial var</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/proc-logistic-with-only-categorial-var/m-p/781181#M38353</link>
      <description>Logistic regression in SAS works fine with all categorical predictors. If you're having issues with your code and getting error please include the code and log in your posts.</description>
      <pubDate>Fri, 19 Nov 2021 03:34:45 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/proc-logistic-with-only-categorial-var/m-p/781181#M38353</guid>
      <dc:creator>Reeza</dc:creator>
      <dc:date>2021-11-19T03:34:45Z</dc:date>
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    <item>
      <title>Re: proc logistic with only categorial var</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/proc-logistic-with-only-categorial-var/m-p/781182#M38354</link>
      <description>Thanks Sir! you saved my day!&lt;BR /&gt;I thought class and model are mutually exclusive...&lt;BR /&gt;try to put cats in model, error says should be numeric&lt;BR /&gt;try to put cats in class, didn't even calc them in model&lt;BR /&gt;&lt;BR /&gt;that make all the senses now. Thank you very much.</description>
      <pubDate>Fri, 19 Nov 2021 03:37:00 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/proc-logistic-with-only-categorial-var/m-p/781182#M38354</guid>
      <dc:creator>kimmygzc</dc:creator>
      <dc:date>2021-11-19T03:37:00Z</dc:date>
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    <item>
      <title>Re: proc logistic with only categorial var</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/proc-logistic-with-only-categorial-var/m-p/781184#M38355</link>
      <description>One more question Sir,&lt;BR /&gt;&lt;BR /&gt;I have a cat of hundreds values, and it makes the result too large to display, can I select the predictors of top-n significant estimators, and how?</description>
      <pubDate>Fri, 19 Nov 2021 03:47:04 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/proc-logistic-with-only-categorial-var/m-p/781184#M38355</guid>
      <dc:creator>kimmygzc</dc:creator>
      <dc:date>2021-11-19T03:47:04Z</dc:date>
    </item>
    <item>
      <title>Re: proc logistic with only categorial var</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/proc-logistic-with-only-categorial-var/m-p/781186#M38356</link>
      <description>or hide class level infomation would work, but I dont see any opt to turn it off..</description>
      <pubDate>Fri, 19 Nov 2021 04:04:46 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/proc-logistic-with-only-categorial-var/m-p/781186#M38356</guid>
      <dc:creator>kimmygzc</dc:creator>
      <dc:date>2021-11-19T04:04:46Z</dc:date>
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