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    <title>topic Re: nlmixed - random effect covariate calculation and contrast help in SAS Procedures</title>
    <link>https://communities.sas.com/t5/SAS-Procedures/nlmixed-random-effect-covariate-calculation-and-contrast-help/m-p/165488#M42888</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;1.&amp;nbsp; It looks like these should work, but it may be worthwhile to consider using ESTIMATE statement due to the additional info it gives.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;2.&amp;nbsp; Coming up with initial values, especially for covariances, is hard.&amp;nbsp; I would try the default values and see where that leads.&amp;nbsp; Then I would go back and refit with different values, roughly based on the results, and see if I got comparable convergence to the same values.&amp;nbsp; If you have a lot of time, you could try the grid searching option.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Another method would be to semi-linearize, and use PROC MIXED to get approximate starting values.&amp;nbsp; Subtract your best common estimate of c from performance, take the logs of both sides, and fit a regression model that accomodates the random effects and the values from the V matrix.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Steve Denham&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Thu, 03 Apr 2014 12:31:44 GMT</pubDate>
    <dc:creator>SteveDenham</dc:creator>
    <dc:date>2014-04-03T12:31:44Z</dc:date>
    <item>
      <title>nlmixed - random effect covariate calculation and contrast help</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/nlmixed-random-effect-covariate-calculation-and-contrast-help/m-p/165487#M42887</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I have a similar problem as one of the earlier post(with 3 random variables), &lt;A __default_attr="39131" __jive_macro_name="message" class="jive_macro jive_macro_message" href="https://communities.sas.com/"&gt;&lt;/A&gt;, repeated measure of performance over 4-5 trials.&amp;nbsp; I have a group variable (ordinal - 3 groups).&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I'd like to test the differences between the groups (1 vs 2, 1 vs 3, and 2 vs 3).&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Here is my attempt to the code,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;proc nlmixed data=long;&lt;/P&gt;&lt;P&gt;&amp;nbsp; parms a1=1 b1=.5 c1=.5 u1=.1 u2=.1 u3=.1 s2e=?? g11=?? g21=?? ...&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; a2=0 a3=0 b2=0 b3=0 c2=0 c3=0;&lt;/P&gt;&lt;P&gt;&amp;nbsp; a=a1+a2*(group=2)+a3*(group=3)+u1;&lt;/P&gt;&lt;P&gt;&amp;nbsp; b=b1+b2*(group=2)+b3*(group=3)+u2;&lt;/P&gt;&lt;P&gt;&amp;nbsp; c=c1+c2*(group=2)+c3*(group=3)+u3;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp; eqn=a/time**b+c;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp; model performance ~ normal(eqn,s2e);&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp; random u1 u2 u3 ~ normal([0,0,0],[g11,g21,g11,g31,g32,g33]) subject=id;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;run;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;2 things I am having trouble with are:&lt;/P&gt;&lt;P&gt;1.&amp;nbsp; how to code "CONTRAST" to test the proper groups.&amp;nbsp; is it just &lt;/P&gt;&lt;P&gt;contrast "b1 vs b2" b1 - b2;&lt;/P&gt;&lt;P&gt;contrast "b1 vs b3" b1 - b3;&lt;/P&gt;&lt;P&gt;contrast "b2 vs b3" b2 - b3;&lt;/P&gt;&lt;P&gt;contrast "a1 vs a2" a1 - a2;&lt;/P&gt;&lt;P&gt;....&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;2.&amp;nbsp; how do I calculate the values to s2e, g11, g21....?&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;thanks in advance for your help.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;ming&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Wed, 02 Apr 2014 19:55:39 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/nlmixed-random-effect-covariate-calculation-and-contrast-help/m-p/165487#M42887</guid>
      <dc:creator>Ming</dc:creator>
      <dc:date>2014-04-02T19:55:39Z</dc:date>
    </item>
    <item>
      <title>Re: nlmixed - random effect covariate calculation and contrast help</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/nlmixed-random-effect-covariate-calculation-and-contrast-help/m-p/165488#M42888</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;1.&amp;nbsp; It looks like these should work, but it may be worthwhile to consider using ESTIMATE statement due to the additional info it gives.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;2.&amp;nbsp; Coming up with initial values, especially for covariances, is hard.&amp;nbsp; I would try the default values and see where that leads.&amp;nbsp; Then I would go back and refit with different values, roughly based on the results, and see if I got comparable convergence to the same values.&amp;nbsp; If you have a lot of time, you could try the grid searching option.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Another method would be to semi-linearize, and use PROC MIXED to get approximate starting values.&amp;nbsp; Subtract your best common estimate of c from performance, take the logs of both sides, and fit a regression model that accomodates the random effects and the values from the V matrix.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Steve Denham&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 03 Apr 2014 12:31:44 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/nlmixed-random-effect-covariate-calculation-and-contrast-help/m-p/165488#M42888</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2014-04-03T12:31:44Z</dc:date>
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