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    <title>topic How to compare 2 mixed models with different Fixed Effects? in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-compare-2-mixed-models-with-different-Fixed-Effects/m-p/676900#M32446</link>
    <description>&lt;P&gt;How do I compare 2 mixed models with different fixed Effects (here "B"). I understand I cannot use REML but want to know if model B fits the data better than model A.&amp;nbsp; On the internet I saw something about using ANOVA for a Chi-square analysis in R, but don't know how to do it in SAS.&amp;nbsp; I'm a SAS newbie.&amp;nbsp; Thanks.&lt;/P&gt;&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;proc mixed data=ttnc_subsetsort PLOTS=RESIDUALPANEL(UNPACK) RATIO;
  class hyb ntrt pd loc pass rep;
  model tnc =hyb ntrt pd ntrt*hyb pd*hyb ntrt*pd / residual;
  random loc rep(loc) loc*ntrt loc*hyb ;
  lsmeans hyb ntrt pd hyb*ntrt / pdiff=all cl adjust=tukey alpha=0.10;
  title1 'Fit Model A with Factors';
  store modA;
  run;

proc mixed data=ttnc_subsetsort PLOTS=RESIDUALPANEL(UNPACK) RATIO;
  class hyb ntrt pd loc pass rep;
  model tnc =hyb ntrt pd ntrt*hyb pd*hyb ntrt*pd B / residual;
  random loc rep(loc) loc*ntrt loc*hyb ;
  lsmeans hyb ntrt pd hyb*ntrt / pdiff=all cl adjust=tukey alpha=0.10;
  title1 'Fit Model B with Factors';
  store modB;
  run;&lt;/CODE&gt;&lt;/PRE&gt;</description>
    <pubDate>Fri, 14 Aug 2020 21:41:51 GMT</pubDate>
    <dc:creator>Daisy2</dc:creator>
    <dc:date>2020-08-14T21:41:51Z</dc:date>
    <item>
      <title>How to compare 2 mixed models with different Fixed Effects?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-compare-2-mixed-models-with-different-Fixed-Effects/m-p/676900#M32446</link>
      <description>&lt;P&gt;How do I compare 2 mixed models with different fixed Effects (here "B"). I understand I cannot use REML but want to know if model B fits the data better than model A.&amp;nbsp; On the internet I saw something about using ANOVA for a Chi-square analysis in R, but don't know how to do it in SAS.&amp;nbsp; I'm a SAS newbie.&amp;nbsp; Thanks.&lt;/P&gt;&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;proc mixed data=ttnc_subsetsort PLOTS=RESIDUALPANEL(UNPACK) RATIO;
  class hyb ntrt pd loc pass rep;
  model tnc =hyb ntrt pd ntrt*hyb pd*hyb ntrt*pd / residual;
  random loc rep(loc) loc*ntrt loc*hyb ;
  lsmeans hyb ntrt pd hyb*ntrt / pdiff=all cl adjust=tukey alpha=0.10;
  title1 'Fit Model A with Factors';
  store modA;
  run;

proc mixed data=ttnc_subsetsort PLOTS=RESIDUALPANEL(UNPACK) RATIO;
  class hyb ntrt pd loc pass rep;
  model tnc =hyb ntrt pd ntrt*hyb pd*hyb ntrt*pd B / residual;
  random loc rep(loc) loc*ntrt loc*hyb ;
  lsmeans hyb ntrt pd hyb*ntrt / pdiff=all cl adjust=tukey alpha=0.10;
  title1 'Fit Model B with Factors';
  store modB;
  run;&lt;/CODE&gt;&lt;/PRE&gt;</description>
      <pubDate>Fri, 14 Aug 2020 21:41:51 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/How-to-compare-2-mixed-models-with-different-Fixed-Effects/m-p/676900#M32446</guid>
      <dc:creator>Daisy2</dc:creator>
      <dc:date>2020-08-14T21:41:51Z</dc:date>
    </item>
    <item>
      <title>Re: How to compare 2 mixed models with different Fixed Effects?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-compare-2-mixed-models-with-different-Fixed-Effects/m-p/677178#M32494</link>
      <description>&lt;P&gt;Since the base model is nested within model B, you can get a likelihood ratio test for the significance of adding the B parameter by subtracting the -2 log likelihood for the base model from the same factor of model B.&amp;nbsp; This should give the same probability as the F test for B in the B model.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;But somehow, I don't think this is quite what you are looking for.&amp;nbsp; I suspect you want to know something about the adequacy of the full models.&amp;nbsp; This is where information criteria are helpful.&amp;nbsp; In this case, as there are a fairly substantial number of parameters, I would suggest looking at the corrected AIC values for the two models, and selecting the one with the smaller value.&amp;nbsp; See&amp;nbsp;&lt;CITE id="CITEREFBurnhamAnderson2002" class="citation cs2"&gt;Burnham, K. P.; Anderson, D. R. (2002),&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;Model Selection and Multimodel Inference: A practical information-theoretic approach&lt;/I&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;(2nd ed.),&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;A class="mw-redirect" title="Springer-Verlag" href="https://en.wikipedia.org/wiki/Springer-Verlag" target="_blank"&gt;Springer-Verlag&lt;/A&gt;&lt;/CITE&gt;&lt;SPAN&gt;., or for a quick overview, look at the Wikipedia article&amp;nbsp;&lt;A href="https://en.wikipedia.org/wiki/Akaike_information_criterion" target="_self"&gt;here.&lt;/A&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;SteveDenham&lt;/SPAN&gt;&lt;/P&gt;</description>
      <pubDate>Mon, 17 Aug 2020 12:02:09 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/How-to-compare-2-mixed-models-with-different-Fixed-Effects/m-p/677178#M32494</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2020-08-17T12:02:09Z</dc:date>
    </item>
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