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    <title>topic Re: %Beta_Regression Macro from &amp;quot;Inflated Beta Regression: Zero, One, and Everything in Between in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Beta-Regression-Macro-from-quot-Inflated-Beta-Regression-Zero/m-p/646302#M31017</link>
    <description>&lt;P&gt;So you could have the same variables predicting both the mean and precision?&lt;/P&gt;</description>
    <pubDate>Fri, 08 May 2020 19:15:12 GMT</pubDate>
    <dc:creator>markus24135</dc:creator>
    <dc:date>2020-05-08T19:15:12Z</dc:date>
    <item>
      <title>%Beta_Regression Macro from "Inflated Beta Regression: Zero, One, and Everything in Between"</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Beta-Regression-Macro-from-quot-Inflated-Beta-Regression-Zero/m-p/645954#M30990</link>
      <description>&lt;P&gt;Dear SAS Community,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I have recently run into a situation where my model requires a zero-one-inflated beta regression.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I have applied the macros created by&amp;nbsp;Christopher Swearingen,&amp;nbsp;Maria Melguizo Castro, and Zoran Bursac in their paper 325-2012 from the SAS Global Forum in 2012 (&lt;A href="https://support.sas.com/resources/papers/proceedings12/325-2012.pdf" target="_blank"&gt;https://support.sas.com/resources/papers/proceedings12/325-2012.pdf&lt;/A&gt;) but I have a question.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;The macro calls for:&lt;/P&gt;&lt;P&gt;%Macro Beta_Regression(Dataset,tech,details,mu_vars,phi_vars,zero_vars,one_vars,&lt;BR /&gt;depvar);&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;with -&amp;nbsp;&lt;/P&gt;&lt;P&gt;Dataset – the LIBNAME.DATA file&lt;BR /&gt;tech – allows for different optimization schemes to be used&lt;BR /&gt;details – allows for other options to be specified&lt;BR /&gt;mu_vars – variables modeling changes in mean&lt;BR /&gt;phi_vars – variables modeling changes in precision&lt;BR /&gt;zero_vars – variables predicting a response of zero&lt;BR /&gt;one_vars – variables predicting a response of one&lt;BR /&gt;depvar – the dependent variable scaled to a [0,1] interval&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I can't figure out what they are referring to with the "mu_vars" and "phi_vars" though. From what I can gather from the paper and from Ospina et. al this could be referring to continuous independent variables and categorical independent variables, respectively, in the model. Is this correct?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Please explain as much as possible without jargon, I am not a statistician. Thank you very much in advance!!&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Mark&lt;/P&gt;</description>
      <pubDate>Thu, 07 May 2020 17:22:09 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Beta-Regression-Macro-from-quot-Inflated-Beta-Regression-Zero/m-p/645954#M30990</guid>
      <dc:creator>markus24135</dc:creator>
      <dc:date>2020-05-07T17:22:09Z</dc:date>
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    <item>
      <title>Re: %Beta_Regression Macro from "Inflated Beta Regression: Zero, One, and Everything in Between</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Beta-Regression-Macro-from-quot-Inflated-Beta-Regression-Zero/m-p/646174#M31007</link>
      <description>&lt;P&gt;mu_vars refer to model effects, whether continuous or categorical. In other words, the independent variables that have an effect on the mean of the dependent variable.&amp;nbsp; phi_vars refer to the reciprocal of the variance/deviance of the model.&amp;nbsp; There are several ways of parameterizing a beta distribution, and one is the "mean and precision" method. Here is a good introductory level presentation on the beta distribution:&lt;/P&gt;
&lt;P&gt;&lt;A href="http://quantdevel.com/public/CSP2017/ModelingProportionsAndProbabilities.pdf" target="_self"&gt;http://quantdevel.com/public/CSP2017/ModelingProportionsAndProbabilities.pdf&lt;/A&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;SteveDenham&lt;/P&gt;</description>
      <pubDate>Fri, 08 May 2020 11:43:43 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Beta-Regression-Macro-from-quot-Inflated-Beta-Regression-Zero/m-p/646174#M31007</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2020-05-08T11:43:43Z</dc:date>
    </item>
    <item>
      <title>Re: %Beta_Regression Macro from "Inflated Beta Regression: Zero, One, and Everything in Between</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Beta-Regression-Macro-from-quot-Inflated-Beta-Regression-Zero/m-p/646302#M31017</link>
      <description>&lt;P&gt;So you could have the same variables predicting both the mean and precision?&lt;/P&gt;</description>
      <pubDate>Fri, 08 May 2020 19:15:12 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Beta-Regression-Macro-from-quot-Inflated-Beta-Regression-Zero/m-p/646302#M31017</guid>
      <dc:creator>markus24135</dc:creator>
      <dc:date>2020-05-08T19:15:12Z</dc:date>
    </item>
    <item>
      <title>Re: %Beta_Regression Macro from "Inflated Beta Regression: Zero, One, and Everything in Between</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Beta-Regression-Macro-from-quot-Inflated-Beta-Regression-Zero/m-p/646695#M31027</link>
      <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/276551"&gt;@markus24135&lt;/a&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I am not really familiar enough with the macro syntax to say for sure, but I would guess (and stress that it is only a guess) that the covariates associated with each of these could be identical, but may not be.&amp;nbsp; In the first example in the paper (Brazilian traffic accidents), they are identical. In the Barthel index examples where zero and one inflation are fit, it appears that they are not identical, with the phi_var as a subset of the mu_var.&amp;nbsp; I suppose if I tore into the coding I could give a better answer.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;SteveDenham.&lt;/P&gt;</description>
      <pubDate>Mon, 11 May 2020 14:08:56 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Beta-Regression-Macro-from-quot-Inflated-Beta-Regression-Zero/m-p/646695#M31027</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2020-05-11T14:08:56Z</dc:date>
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