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    <title>topic Re: How to interpret a continuous by continuous interaction in a logistic regression using survey we in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-interpret-a-continuous-by-continuous-interaction-in-a/m-p/923787#M45902</link>
    <description>&lt;P&gt;The default EFFECTPLOT, as noted earlier, gives a visual assessment of the variable effects and interaction via a surface plot. You can also use the &lt;A href="http://support.sas.com/kb/63038" target="_self"&gt;Margins macro&lt;/A&gt; to estimate the slope (instantaneous rate of change) of the response surface at specified points. For example, the following statements produce the surface plot and estimate slopes at points on the surface for the continuous variables in the neuralgia data in the example titled "Logistic Modeling with Categorical Predictors" in the PROC LOGISTIC documentation. The variable PAINNUM is a 0,1 coded numeric version of the character Pain variable in that data set. The macro requires a numeric response. See also &lt;A href="http://support.sas.com/kb/67024" target="_self"&gt;this note&lt;/A&gt; for more on assessing the effect of continuous variables in a model.&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;proc surveylogistic data=neuralgia;
   model Pain=Age|Duration;
   store log;
   run;
proc plm restore=log;
   effectplot; 
   run;
data atdat; 
   do duration=20,40;
   do age=60 to 80 by 5;
   output; end; end;
   run;
%margins(data=neuralgia, response=painnum, roptions=event='1',
   model=age|duration, dist=binomial,
   effect=age, at=duration age, atdata=atdat, options=cl)
&lt;/CODE&gt;&lt;/PRE&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Wed, 10 Apr 2024 13:42:42 GMT</pubDate>
    <dc:creator>StatDave</dc:creator>
    <dc:date>2024-04-10T13:42:42Z</dc:date>
    <item>
      <title>How to interpret a continuous by continuous interaction in a logistic regression using survey weigh?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-interpret-a-continuous-by-continuous-interaction-in-a/m-p/923678#M45898</link>
      <description>&lt;P&gt;Hello,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I am currently conducting a logistic regression where both of my predictors are continuous (i.e., X and M). The outcome is binary (Y). I have already tested the interaction term and found that it is significant, but I am struggling with the best approach for interpreting the types of interaction. Is there an easy way to plot this using PROC SURVEYLOGISTIC?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Any advice would be a great help.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks!&lt;/P&gt;</description>
      <pubDate>Tue, 09 Apr 2024 21:32:55 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/How-to-interpret-a-continuous-by-continuous-interaction-in-a/m-p/923678#M45898</guid>
      <dc:creator>djohn051</dc:creator>
      <dc:date>2024-04-09T21:32:55Z</dc:date>
    </item>
    <item>
      <title>Re: How to interpret a continuous by continuous interaction in a logistic regression using survey we</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-interpret-a-continuous-by-continuous-interaction-in-a/m-p/923680#M45899</link>
      <description>&lt;P&gt;I have never done this, but you can save the model using the STORE command in PROC SURVEYLOGISTIC. Then in PROC PLM, you can use the EFFECT PLOT command to create an interaction plot.&lt;/P&gt;</description>
      <pubDate>Tue, 09 Apr 2024 22:44:49 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/How-to-interpret-a-continuous-by-continuous-interaction-in-a/m-p/923680#M45899</guid>
      <dc:creator>PaigeMiller</dc:creator>
      <dc:date>2024-04-09T22:44:49Z</dc:date>
    </item>
    <item>
      <title>Re: How to interpret a continuous by continuous interaction in a logistic regression using survey we</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-interpret-a-continuous-by-continuous-interaction-in-a/m-p/923687#M45900</link>
      <description>&lt;P&gt;Is there anything I have to do to specify high versus low levels of the moderator? I'm used to categorical moderators where it is a lot easier to just stratify and plot, but I'm having trouble wrapping my head around how that's done with something continuous.&lt;/P&gt;</description>
      <pubDate>Wed, 10 Apr 2024 00:34:27 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/How-to-interpret-a-continuous-by-continuous-interaction-in-a/m-p/923687#M45900</guid>
      <dc:creator>djohn051</dc:creator>
      <dc:date>2024-04-10T00:34:27Z</dc:date>
    </item>
    <item>
      <title>Re: How to interpret a continuous by continuous interaction in a logistic regression using survey we</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-interpret-a-continuous-by-continuous-interaction-in-a/m-p/923765#M45901</link>
      <description>&lt;BLOCKQUOTE&gt;&lt;HR /&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/171133"&gt;@djohn051&lt;/a&gt;&amp;nbsp;wrote:&lt;BR /&gt;
&lt;P&gt;Is there anything I have to do to specify high versus low levels of the moderator?&lt;/P&gt;
&lt;HR /&gt;&lt;/BLOCKQUOTE&gt;
&lt;P&gt;No.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;BLOCKQUOTE&gt;
&lt;P&gt;I'm used to categorical moderators where it is a lot easier to just stratify and plot, but I'm having trouble wrapping my head around how that's done with something continuous.&lt;/P&gt;
&lt;/BLOCKQUOTE&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;A continuous * continuous interaction can be though of as different slope for variable X depending on value of variable M. Please use your favorite internet search engine and search for&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;interpret continuous * continuous interaction&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Plenty of explanations out there.&lt;/P&gt;</description>
      <pubDate>Wed, 10 Apr 2024 09:44:18 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/How-to-interpret-a-continuous-by-continuous-interaction-in-a/m-p/923765#M45901</guid>
      <dc:creator>PaigeMiller</dc:creator>
      <dc:date>2024-04-10T09:44:18Z</dc:date>
    </item>
    <item>
      <title>Re: How to interpret a continuous by continuous interaction in a logistic regression using survey we</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-interpret-a-continuous-by-continuous-interaction-in-a/m-p/923787#M45902</link>
      <description>&lt;P&gt;The default EFFECTPLOT, as noted earlier, gives a visual assessment of the variable effects and interaction via a surface plot. You can also use the &lt;A href="http://support.sas.com/kb/63038" target="_self"&gt;Margins macro&lt;/A&gt; to estimate the slope (instantaneous rate of change) of the response surface at specified points. For example, the following statements produce the surface plot and estimate slopes at points on the surface for the continuous variables in the neuralgia data in the example titled "Logistic Modeling with Categorical Predictors" in the PROC LOGISTIC documentation. The variable PAINNUM is a 0,1 coded numeric version of the character Pain variable in that data set. The macro requires a numeric response. See also &lt;A href="http://support.sas.com/kb/67024" target="_self"&gt;this note&lt;/A&gt; for more on assessing the effect of continuous variables in a model.&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;proc surveylogistic data=neuralgia;
   model Pain=Age|Duration;
   store log;
   run;
proc plm restore=log;
   effectplot; 
   run;
data atdat; 
   do duration=20,40;
   do age=60 to 80 by 5;
   output; end; end;
   run;
%margins(data=neuralgia, response=painnum, roptions=event='1',
   model=age|duration, dist=binomial,
   effect=age, at=duration age, atdata=atdat, options=cl)
&lt;/CODE&gt;&lt;/PRE&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 10 Apr 2024 13:42:42 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/How-to-interpret-a-continuous-by-continuous-interaction-in-a/m-p/923787#M45902</guid>
      <dc:creator>StatDave</dc:creator>
      <dc:date>2024-04-10T13:42:42Z</dc:date>
    </item>
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