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    <title>topic Re: determining which model to use in SAS Procedures</title>
    <link>https://communities.sas.com/t5/SAS-Procedures/determining-which-model-to-use/m-p/317970#M61824</link>
    <description>&lt;P&gt;Ok, now I'm looking for the part of the output (odds ratios?) so that I can conclude something like "males are 1.5 times more likely to be retained than females."&lt;/P&gt;</description>
    <pubDate>Fri, 09 Dec 2016 19:16:42 GMT</pubDate>
    <dc:creator>GreggB</dc:creator>
    <dc:date>2016-12-09T19:16:42Z</dc:date>
    <item>
      <title>determining which model to use</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/determining-which-model-to-use/m-p/317948#M61821</link>
      <description>&lt;P&gt;I want to create a model to examine the relationship between 7 independent variables and 1 dependent variable.&lt;/P&gt;
&lt;P&gt;The dep var is EverRetained. Values are Y/N.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;The &amp;nbsp;independent vars are &amp;nbsp;gender (M/F), lunchstatus (F,R,P), GTstatus (Y/N), IEPstatus (Y/N), 504status (Y/N), LEPstatus (Y/N) and RR (Y/N).&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I know the type of variables determine how I should proceed but I'm sure if a regression model is appropriate. I conducted a chi square comparing the dependent var to each indep var separately. 5 of the 7 tests returned a p-value less than 0.05&lt;/P&gt;</description>
      <pubDate>Fri, 09 Dec 2016 17:38:16 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/determining-which-model-to-use/m-p/317948#M61821</guid>
      <dc:creator>GreggB</dc:creator>
      <dc:date>2016-12-09T17:38:16Z</dc:date>
    </item>
    <item>
      <title>Re: determining which model to use</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/determining-which-model-to-use/m-p/317953#M61823</link>
      <description>&lt;P&gt;A first approach that ignores any interactions would look like:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;proc logistic data=yourdata;
class gender lunchstatus gtstatus iepstatus 504status rr;
model everretained(event='y') = gender lunchstatus gtstatus iepstatus 504status rr/clodds=both;
run;&lt;/CODE&gt;&lt;/PRE&gt;
&lt;P&gt;However, I am sure that interactions between the independent variables exist, and should be modeled. &amp;nbsp;Use your prior knowledge about which interactions are of interest.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Steve Denham&lt;/P&gt;</description>
      <pubDate>Fri, 09 Dec 2016 17:47:10 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/determining-which-model-to-use/m-p/317953#M61823</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2016-12-09T17:47:10Z</dc:date>
    </item>
    <item>
      <title>Re: determining which model to use</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/determining-which-model-to-use/m-p/317970#M61824</link>
      <description>&lt;P&gt;Ok, now I'm looking for the part of the output (odds ratios?) so that I can conclude something like "males are 1.5 times more likely to be retained than females."&lt;/P&gt;</description>
      <pubDate>Fri, 09 Dec 2016 19:16:42 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/determining-which-model-to-use/m-p/317970#M61824</guid>
      <dc:creator>GreggB</dc:creator>
      <dc:date>2016-12-09T19:16:42Z</dc:date>
    </item>
    <item>
      <title>Re: determining which model to use</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/determining-which-model-to-use/m-p/318300#M61855</link>
      <description>&lt;P&gt;That would come from the odds ratios, yes.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Steve Denham&lt;/P&gt;</description>
      <pubDate>Mon, 12 Dec 2016 15:55:40 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/determining-which-model-to-use/m-p/318300#M61855</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2016-12-12T15:55:40Z</dc:date>
    </item>
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