<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Re: Regression_Plots in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Regression-Plots/m-p/270348#M14224</link>
    <description>&lt;P&gt;Yes, use PROC LOGISTIC. Since LOGISTIC supports the CLASS statement you can skip the call to GLMMOD and just put the categorical variables on the CLASS statement.&amp;nbsp; Add the INFLUENCE option to the MODEL statement. If you turn on ODS graphics (ODS GRAPHICS ON) and request PLOTS=ALL, you will get many &lt;A href="http://support.sas.com/documentation/cdl/en/statug/68162/HTML/default/viewer.htm#statug_logistic_details38.htm" target="_self"&gt;diagnostic plots.&lt;/A&gt;&amp;nbsp;The PROC LOGISTIC doc has &lt;A href="http://support.sas.com/documentation/cdl/en/statug/68162/HTML/default/viewer.htm#statug_logistic_examples06.htm" target="_self"&gt;an example that explains the diagnostic plots.&lt;/A&gt;&lt;/P&gt;</description>
    <pubDate>Fri, 13 May 2016 14:11:39 GMT</pubDate>
    <dc:creator>Rick_SAS</dc:creator>
    <dc:date>2016-05-13T14:11:39Z</dc:date>
    <item>
      <title>Regression_Plots</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Regression-Plots/m-p/270277#M14218</link>
      <description>&lt;P&gt;I have produced a regression model where the dependent variable is binary type (0,1) and the independent variables are categorical for which i have used dummy variables.What kind of plots can i use for the model?&lt;/P&gt;&lt;P&gt;following codes were used:&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;proc glmmod data = traindata outdesign=GLMDesign1 outparm=GLMParm1;&lt;BR /&gt;class v24 v30 v31 v47 v56 v62 v66 v72 v79 v112 v113 ;&lt;BR /&gt;model target = v24 v30 v31 v47 v56 v62 v66 v72 v79 v112 v113;&lt;BR /&gt;run;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;proc glm data = traindata;&lt;BR /&gt;class v24 v30 v31 v47 v56 v62 v66 v72 v79 v112 v113 ;&lt;BR /&gt;model target = v24 v30 v31 v47 v56 v62 v66 v72 v79 v112 v113 / solution clparm;&lt;BR /&gt;ods select ParameterEstimates;&lt;BR /&gt;quit;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;proc reg data = GLMDesign1 outest = regout plots(MAXPOINTS = NONE) = all;&lt;BR /&gt;DummyVars:model target = col2 col3 col7 col12 col14 col18 col22 col24 col32 col36 col45 col81&lt;BR /&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; col86 col90 col94 col97 col102 col105 col112 col116 col120 col126 col133 col152 col157 col159 col164 / P R;&lt;BR /&gt;ods select ParameterEstimates;&lt;BR /&gt;OUTPUT OUT = stat&lt;BR /&gt;P=pred R=Residual RSTUDENT=r1 DFFITS=dffits&lt;BR /&gt;COOKD=cookd H=hatvalue PRESS=res_del ;&lt;BR /&gt;quit;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;proc reg data = GLMDesign1 outest = regout1 plots = all;&lt;BR /&gt;DummyVars:model target = col9 col11 col19-col21 col25 col30 col34 col38-col40 col56 col59 col61 col62&lt;BR /&gt;col72 col74 col75 col82 col85 col96 col97 col112 ;&lt;BR /&gt;ods select ParameterEstimates;&lt;BR /&gt;quit;&lt;/P&gt;</description>
      <pubDate>Fri, 13 May 2016 07:23:50 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Regression-Plots/m-p/270277#M14218</guid>
      <dc:creator>DineshK1493</dc:creator>
      <dc:date>2016-05-13T07:23:50Z</dc:date>
    </item>
    <item>
      <title>Re: Regression_Plots</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Regression-Plots/m-p/270288#M14219</link>
      <description>&lt;P&gt;If your dependent variable is 0/1 why aren't you using logistic regression?&lt;/P&gt;
&lt;P&gt;I may be missing something though.&lt;/P&gt;</description>
      <pubDate>Fri, 13 May 2016 08:24:51 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Regression-Plots/m-p/270288#M14219</guid>
      <dc:creator>Reeza</dc:creator>
      <dc:date>2016-05-13T08:24:51Z</dc:date>
    </item>
    <item>
      <title>Re: Regression_Plots</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Regression-Plots/m-p/270326#M14221</link>
      <description>Do I need to mention in the above glm procedure that the model is logit (like family = "binomial" in R)? How do I see the regression curve?</description>
      <pubDate>Fri, 13 May 2016 12:37:09 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Regression-Plots/m-p/270326#M14221</guid>
      <dc:creator>DineshK1493</dc:creator>
      <dc:date>2016-05-13T12:37:09Z</dc:date>
    </item>
    <item>
      <title>Re: Regression_Plots</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Regression-Plots/m-p/270327#M14222</link>
      <description>Or should I use the proc logistic feature?&lt;BR /&gt;</description>
      <pubDate>Fri, 13 May 2016 12:38:33 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Regression-Plots/m-p/270327#M14222</guid>
      <dc:creator>DineshK1493</dc:creator>
      <dc:date>2016-05-13T12:38:33Z</dc:date>
    </item>
    <item>
      <title>Re: Regression_Plots</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Regression-Plots/m-p/270348#M14224</link>
      <description>&lt;P&gt;Yes, use PROC LOGISTIC. Since LOGISTIC supports the CLASS statement you can skip the call to GLMMOD and just put the categorical variables on the CLASS statement.&amp;nbsp; Add the INFLUENCE option to the MODEL statement. If you turn on ODS graphics (ODS GRAPHICS ON) and request PLOTS=ALL, you will get many &lt;A href="http://support.sas.com/documentation/cdl/en/statug/68162/HTML/default/viewer.htm#statug_logistic_details38.htm" target="_self"&gt;diagnostic plots.&lt;/A&gt;&amp;nbsp;The PROC LOGISTIC doc has &lt;A href="http://support.sas.com/documentation/cdl/en/statug/68162/HTML/default/viewer.htm#statug_logistic_examples06.htm" target="_self"&gt;an example that explains the diagnostic plots.&lt;/A&gt;&lt;/P&gt;</description>
      <pubDate>Fri, 13 May 2016 14:11:39 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Regression-Plots/m-p/270348#M14224</guid>
      <dc:creator>Rick_SAS</dc:creator>
      <dc:date>2016-05-13T14:11:39Z</dc:date>
    </item>
  </channel>
</rss>

