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    <title>topic Joint test in PROC FMM? in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Joint-test-in-PROC-FMM/m-p/959547#M48059</link>
    <description>&lt;P&gt;Since PROC FMM does not have an ESTIMATE or CONTRAST statement, the %NLEST macro can be used for hypothesis testing. However, the %NLEST macro does not support joint testing (according to this SAS note:&amp;nbsp;&lt;A href="https://support.sas.com/kb/24/094.html" target="_blank"&gt;https://support.sas.com/kb/24/094.html&lt;/A&gt;).&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Is there a procedure or alternative SAS macro that facilitates a joint hypothesis test of the PROBMODEL parameters in PROC FMM?&lt;/P&gt;</description>
    <pubDate>Tue, 18 Feb 2025 21:03:32 GMT</pubDate>
    <dc:creator>jl4443</dc:creator>
    <dc:date>2025-02-18T21:03:32Z</dc:date>
    <item>
      <title>Joint test in PROC FMM?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Joint-test-in-PROC-FMM/m-p/959547#M48059</link>
      <description>&lt;P&gt;Since PROC FMM does not have an ESTIMATE or CONTRAST statement, the %NLEST macro can be used for hypothesis testing. However, the %NLEST macro does not support joint testing (according to this SAS note:&amp;nbsp;&lt;A href="https://support.sas.com/kb/24/094.html" target="_blank"&gt;https://support.sas.com/kb/24/094.html&lt;/A&gt;).&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Is there a procedure or alternative SAS macro that facilitates a joint hypothesis test of the PROBMODEL parameters in PROC FMM?&lt;/P&gt;</description>
      <pubDate>Tue, 18 Feb 2025 21:03:32 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Joint-test-in-PROC-FMM/m-p/959547#M48059</guid>
      <dc:creator>jl4443</dc:creator>
      <dc:date>2025-02-18T21:03:32Z</dc:date>
    </item>
    <item>
      <title>Re: Joint test in PROC FMM?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Joint-test-in-PROC-FMM/m-p/959625#M48061</link>
      <description>&lt;P&gt;The problem is the FMM does not report a covariance matrix for the estimates of the PROBMODEL.&amp;nbsp; This would make performing a joint test impossible.&lt;/P&gt;</description>
      <pubDate>Wed, 19 Feb 2025 16:10:48 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Joint-test-in-PROC-FMM/m-p/959625#M48061</guid>
      <dc:creator>SAS_Rob</dc:creator>
      <dc:date>2025-02-19T16:10:48Z</dc:date>
    </item>
    <item>
      <title>Re: Joint test in PROC FMM?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Joint-test-in-PROC-FMM/m-p/959628#M48063</link>
      <description>&lt;P&gt;Thank you for taking a look at this question. When I run PROC FMM with the COV option on the PROC FMM statement and use ODS OUTPUT COV = COV_OUTPUT,&lt;/P&gt;&lt;P&gt;The resulting COV_OUTPUT dataset includes a variable 'ModelNo' with a value of 1 and corresponding variable 'Label' = "Weibull" (since I have distribution=Weibull for my FMM outcome model) as well as data corresponding to a 'ModelNo' = 2 and 'Label' = "Probability Model". I interpreted this&amp;nbsp;as the covariance matrix from the component membership model from the PROBMODEL statement, is that not the correct interpretation of that output?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 19 Feb 2025 16:26:33 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Joint-test-in-PROC-FMM/m-p/959628#M48063</guid>
      <dc:creator>jl4443</dc:creator>
      <dc:date>2025-02-19T16:26:33Z</dc:date>
    </item>
    <item>
      <title>Re: Joint test in PROC FMM?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Joint-test-in-PROC-FMM/m-p/959631#M48065</link>
      <description>&lt;P&gt;No, you are interpreting it correctly.&amp;nbsp; I was wrong about what was contained in that data set.&lt;/P&gt;
&lt;P&gt;In any regard, hypothesis testing in finite mixture models is not very well defined because it is difficult if not impossible to derive the asymptotic distribution for the mixture likelihood.&amp;nbsp; There is a paper that discusses the problem and makes a few suggestions related to goodness of fit tests that might work.&amp;nbsp; Anything that they propose would not be available in SAS, but you might be able to program it yourself.&lt;/P&gt;
&lt;P&gt;&lt;A href="https://www.sciencedirect.com/science/article/abs/pii/S0167947318301142" target="_blank"&gt;Hypothesis testing for finite mixture models - ScienceDirect&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 19 Feb 2025 16:41:40 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Joint-test-in-PROC-FMM/m-p/959631#M48065</guid>
      <dc:creator>SAS_Rob</dc:creator>
      <dc:date>2025-02-19T16:41:40Z</dc:date>
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