<?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 Regression analysis with Cost as outcome variable in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Regression-analysis-with-Cost-as-outcome-variable/m-p/314372#M16553</link>
    <description>&lt;P&gt;I am trying to predict the impact of readmission events (continuous) and type of readmission (medical, surgical, other) on total hospital costs. Because costs are skewed by nature, I am applying gamma distribution with log link function. Below is the model&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;PROC GENMOD data = abc;
class type (ref='medical') gender (ref='F')/param=ref;
model cost = event type age gender /dist=gamma link=log type3;
run;&lt;/CODE&gt;&lt;/PRE&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;1) Is the model correct?&lt;/P&gt;
&lt;P&gt;2) How can I get marginal effects from the coefficients for different variables. i.e. is there a SAS option that will give me hospital cost within each level of type of readmission and for male and female?&lt;/P&gt;
&lt;P&gt;3) I know modified park test will help us determine whether to use gamma distribution or not, but I can't seem to find that option in SAS.&lt;/P&gt;</description>
    <pubDate>Fri, 25 Nov 2016 21:53:12 GMT</pubDate>
    <dc:creator>samraty81</dc:creator>
    <dc:date>2016-11-25T21:53:12Z</dc:date>
    <item>
      <title>Regression analysis with Cost as outcome variable</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Regression-analysis-with-Cost-as-outcome-variable/m-p/314372#M16553</link>
      <description>&lt;P&gt;I am trying to predict the impact of readmission events (continuous) and type of readmission (medical, surgical, other) on total hospital costs. Because costs are skewed by nature, I am applying gamma distribution with log link function. Below is the model&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;PROC GENMOD data = abc;
class type (ref='medical') gender (ref='F')/param=ref;
model cost = event type age gender /dist=gamma link=log type3;
run;&lt;/CODE&gt;&lt;/PRE&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;1) Is the model correct?&lt;/P&gt;
&lt;P&gt;2) How can I get marginal effects from the coefficients for different variables. i.e. is there a SAS option that will give me hospital cost within each level of type of readmission and for male and female?&lt;/P&gt;
&lt;P&gt;3) I know modified park test will help us determine whether to use gamma distribution or not, but I can't seem to find that option in SAS.&lt;/P&gt;</description>
      <pubDate>Fri, 25 Nov 2016 21:53:12 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Regression-analysis-with-Cost-as-outcome-variable/m-p/314372#M16553</guid>
      <dc:creator>samraty81</dc:creator>
      <dc:date>2016-11-25T21:53:12Z</dc:date>
    </item>
    <item>
      <title>Re: Regression analysis with Cost as outcome variable</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Regression-analysis-with-Cost-as-outcome-variable/m-p/314414#M16558</link>
      <description>&lt;PRE&gt;
1) check EFFECTPLOT statement
2)

http://blogs.sas.com/content/iml/2015/09/10/plot-distrib-reg-model.html

http://blogs.sas.com/content/iml/2015/09/16/plot-distrib-exp.html&lt;/PRE&gt;</description>
      <pubDate>Sat, 26 Nov 2016 04:08:34 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Regression-analysis-with-Cost-as-outcome-variable/m-p/314414#M16558</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2016-11-26T04:08:34Z</dc:date>
    </item>
  </channel>
</rss>

