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    <title>topic Re: Hausman Test in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Hausman-Test/m-p/933718#M46559</link>
    <description>&lt;P&gt;If possible, it's better to choose your modeling approach based on the goals of the study/analysis, rather than a statistical test. Can you give more information about your data and the question you are trying to answer?&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Tue, 25 Jun 2024 20:10:13 GMT</pubDate>
    <dc:creator>Mike_N</dc:creator>
    <dc:date>2024-06-25T20:10:13Z</dc:date>
    <item>
      <title>Hausman Test</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Hausman-Test/m-p/933543#M46552</link>
      <description>&lt;P&gt;Hi,&lt;/P&gt;&lt;P&gt;In my data, i have repeated measures from two waves and I used both fixed effects and random effects. I am getting risk estimates in opposite directions. I want to test which method is suitable for my data and I saw on internet and ChatGpt also suggested to use Hausman test but unfortunately I couldn't get much help on how to run/code it.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Below is my code, and if anyone can see how to use Husman's test to decide which method to use.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Fixed effects:&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;PRE&gt;&lt;CODE class=""&gt;proc logistic data=analysis1;
class newid sex(ref='1') age_dik region(ref='North') / param=ref;
model anxiety (event='1') = temperature sex age_dik region rain / selection=none;
strata newid;
run;&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;Random effects:&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;PRE&gt;&lt;CODE class=""&gt;proc genmod data=analysis1 descending;
class sex(ref='1') age_dik region(ref='North') newid;
model anxiety (ref='0') = temperature sex age_dik region rain/ dist=bin link=logit type3;
estimate 'temperature' temperature 1 / exp;
repeated subject=newid / type=exch ;
run;&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;Thank you for help!&lt;/P&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;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 24 Jun 2024 12:21:23 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Hausman-Test/m-p/933543#M46552</guid>
      <dc:creator>Ms_Raza</dc:creator>
      <dc:date>2024-06-24T12:21:23Z</dc:date>
    </item>
    <item>
      <title>Re: Hausman Test</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Hausman-Test/m-p/933625#M46556</link>
      <description>&lt;P&gt;You need module SAS/ETS.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Ksharp_0-1719282299787.png" style="width: 400px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/97873i077B5EEC38B1E9AB/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Ksharp_0-1719282299787.png" alt="Ksharp_0-1719282299787.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 25 Jun 2024 02:25:07 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Hausman-Test/m-p/933625#M46556</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2024-06-25T02:25:07Z</dc:date>
    </item>
    <item>
      <title>Re: Hausman Test</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Hausman-Test/m-p/933718#M46559</link>
      <description>&lt;P&gt;If possible, it's better to choose your modeling approach based on the goals of the study/analysis, rather than a statistical test. Can you give more information about your data and the question you are trying to answer?&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 25 Jun 2024 20:10:13 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Hausman-Test/m-p/933718#M46559</guid>
      <dc:creator>Mike_N</dc:creator>
      <dc:date>2024-06-25T20:10:13Z</dc:date>
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