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    <title>topic Log tranformed dependent: PROC Mixed / NLMIXED? in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Log-tranformed-dependent-PROC-Mixed-NLMIXED/m-p/410624#M21476</link>
    <description>&lt;P&gt;Hi everyone,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp; I'm sorry in advance if this is a dumb question. Say I'm using panel data to model log(Speed) as&amp;nbsp;the response and Turbo as a binary predictor (0= No, 1= Yes). My question:&lt;/P&gt;&lt;P&gt;1- Is Proc Mixed usable here, or do I have to use PROC NLMIXED?&lt;/P&gt;&lt;P&gt;2-&amp;nbsp; Would the results be valid and interpretable as they are in cross-sectional&amp;nbsp;data (i.e. we get x% in speed for Turbo)?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;SAS Version: 9.4&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you.&lt;/P&gt;</description>
    <pubDate>Sun, 05 Nov 2017 01:31:07 GMT</pubDate>
    <dc:creator>mragaa</dc:creator>
    <dc:date>2017-11-05T01:31:07Z</dc:date>
    <item>
      <title>Log tranformed dependent: PROC Mixed / NLMIXED?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Log-tranformed-dependent-PROC-Mixed-NLMIXED/m-p/410624#M21476</link>
      <description>&lt;P&gt;Hi everyone,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp; I'm sorry in advance if this is a dumb question. Say I'm using panel data to model log(Speed) as&amp;nbsp;the response and Turbo as a binary predictor (0= No, 1= Yes). My question:&lt;/P&gt;&lt;P&gt;1- Is Proc Mixed usable here, or do I have to use PROC NLMIXED?&lt;/P&gt;&lt;P&gt;2-&amp;nbsp; Would the results be valid and interpretable as they are in cross-sectional&amp;nbsp;data (i.e. we get x% in speed for Turbo)?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;SAS Version: 9.4&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you.&lt;/P&gt;</description>
      <pubDate>Sun, 05 Nov 2017 01:31:07 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Log-tranformed-dependent-PROC-Mixed-NLMIXED/m-p/410624#M21476</guid>
      <dc:creator>mragaa</dc:creator>
      <dc:date>2017-11-05T01:31:07Z</dc:date>
    </item>
    <item>
      <title>Re: Log tranformed dependent: PROC Mixed / NLMIXED?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Log-tranformed-dependent-PROC-Mixed-NLMIXED/m-p/410879#M21498</link>
      <description>&lt;P&gt;1. You can use PROC MIXED and other linear regression procedures if you first use the&amp;nbsp;DATA step&amp;nbsp;to define logSpeed&amp;nbsp;= log(speed).&amp;nbsp; Then use logSpeed&amp;nbsp;as the response variable.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;2. I am not sure what you are asking, but perhaps it has to do with the interpretation of the parameter estimates for Turbo. If you model&lt;/P&gt;
&lt;P&gt;log(Speed) = Intercept + A*Turbo then&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Speed = exp(Intercept)*exp(A*Turbo)&lt;/P&gt;
&lt;P&gt;Thus when Turbo=0,&amp;nbsp; the predicted speed is exp(Intercept).&lt;/P&gt;
&lt;P&gt;When Turbo=1,&amp;nbsp; the predicted speed is exp(Intercept)*exp(A).&lt;/P&gt;
&lt;P&gt;So the model predicts that using Turbo results in MULTIPLYING the&amp;nbsp;speed by exp(A).&lt;/P&gt;</description>
      <pubDate>Mon, 06 Nov 2017 15:00:43 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Log-tranformed-dependent-PROC-Mixed-NLMIXED/m-p/410879#M21498</guid>
      <dc:creator>Rick_SAS</dc:creator>
      <dc:date>2017-11-06T15:00:43Z</dc:date>
    </item>
    <item>
      <title>Re: Log tranformed dependent: PROC Mixed / NLMIXED?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Log-tranformed-dependent-PROC-Mixed-NLMIXED/m-p/412331#M21615</link>
      <description>Thanks a lot.</description>
      <pubDate>Fri, 10 Nov 2017 13:56:26 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Log-tranformed-dependent-PROC-Mixed-NLMIXED/m-p/412331#M21615</guid>
      <dc:creator>mragaa</dc:creator>
      <dc:date>2017-11-10T13:56:26Z</dc:date>
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