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    <title>topic Hierarchical multilevel bayes model (proc mcmc) in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Hierarchical-multilevel-bayes-model-proc-mcmc/m-p/190954#M10111</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Dear,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Does somebody has an example code of proc mcmc for a hierarchical random effects model of at least 3 levels? I want to fit such a bayesian model to data with proc MCMC but can't find really how to. My model looks like this:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Y_{ijk} | \mu_{jk} ~ N(\mu_{jk}, \sigma^2_w)&lt;/P&gt;&lt;P&gt;where \mu_{jk} | m_k ~ N(m_k, \sigma^2_{b2})&lt;/P&gt;&lt;P&gt;and m_k ~ N(\beta, \sigma^2_{b1})&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;One could, for instance, take m_k as a school effect, \mu_{jk} as a nested class effect (within the school k) and i=1,...,n_{jk} as the number of observations (students) in class j of school k. The eventual parameter of interest is mainly \beta. All help will be greatly appreciated!&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Thanks in advance,&lt;/P&gt;&lt;P&gt;Bert&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Wed, 23 Jul 2014 12:35:09 GMT</pubDate>
    <dc:creator>bert_db</dc:creator>
    <dc:date>2014-07-23T12:35:09Z</dc:date>
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      <title>Hierarchical multilevel bayes model (proc mcmc)</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Hierarchical-multilevel-bayes-model-proc-mcmc/m-p/190954#M10111</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Dear,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Does somebody has an example code of proc mcmc for a hierarchical random effects model of at least 3 levels? I want to fit such a bayesian model to data with proc MCMC but can't find really how to. My model looks like this:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Y_{ijk} | \mu_{jk} ~ N(\mu_{jk}, \sigma^2_w)&lt;/P&gt;&lt;P&gt;where \mu_{jk} | m_k ~ N(m_k, \sigma^2_{b2})&lt;/P&gt;&lt;P&gt;and m_k ~ N(\beta, \sigma^2_{b1})&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;One could, for instance, take m_k as a school effect, \mu_{jk} as a nested class effect (within the school k) and i=1,...,n_{jk} as the number of observations (students) in class j of school k. The eventual parameter of interest is mainly \beta. All help will be greatly appreciated!&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Thanks in advance,&lt;/P&gt;&lt;P&gt;Bert&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Wed, 23 Jul 2014 12:35:09 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Hierarchical-multilevel-bayes-model-proc-mcmc/m-p/190954#M10111</guid>
      <dc:creator>bert_db</dc:creator>
      <dc:date>2014-07-23T12:35:09Z</dc:date>
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