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    <title>topic Re: bayesian method in sas in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944835#M47211</link>
    <description>Yes. You can do Bayesian method of Mixed model by PROC BGLIMM.&lt;BR /&gt;I almost forgot this PROC when &lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/15363"&gt;@SteveDenham&lt;/a&gt; mentioned it before.&lt;BR /&gt;</description>
    <pubDate>Sun, 22 Sep 2024 00:40:13 GMT</pubDate>
    <dc:creator>Ksharp</dc:creator>
    <dc:date>2024-09-22T00:40:13Z</dc:date>
    <item>
      <title>bayesian method in sas</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944826#M47202</link>
      <description>&lt;P&gt;Hi everyone,&lt;/P&gt;
&lt;P&gt;I am working on a linear mixed model using&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;CODE&gt;PROC HPMIXED&lt;/CODE&gt;, but I have encountered an issue with my dependent variable, which is not normally distributed as it is a count trait. Since I am dealing with count data, I considered using a zero-inflated model with&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;CODE&gt;PROC NLMIXED&lt;/CODE&gt;. However, this is not feasible due to the large size of my dataset (over 100k observations).&lt;/P&gt;
&lt;P&gt;I am exploring other approaches, such as Gibbs sampling or Bayesian methods, for resampling. My question is: Does SAS have a procedure that can handle this approach, as I do not have time to explore R or other programs?&lt;/P&gt;
&lt;P&gt;Thank you for your suggestions.&lt;/P&gt;
&lt;P&gt;Best regards,&lt;/P&gt;</description>
      <pubDate>Sat, 21 Sep 2024 13:46:22 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944826#M47202</guid>
      <dc:creator>Ameurgen</dc:creator>
      <dc:date>2024-09-21T13:46:22Z</dc:date>
    </item>
    <item>
      <title>bayesian method in sas</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944814#M47206</link>
      <description>&lt;P&gt;Hi everyone,&lt;/P&gt;
&lt;P&gt;I am working on a linear mixed model using &lt;CODE&gt;PROC HPMIXED&lt;/CODE&gt;, but I have encountered an issue with my dependent variable, which is not normally distributed as it is a count trait. Since I am dealing with count data, I considered using a zero-inflated model with &lt;CODE&gt;PROC NLMIXED&lt;/CODE&gt;. However, this is not feasible due to the large size of my dataset (over 100k observations).&lt;/P&gt;
&lt;P&gt;I am exploring other approaches, such as Gibbs sampling or Bayesian methods, for resampling. My question is: Does SAS have a procedure that can handle this approach, as I do not have time to explore R or other programs?&lt;/P&gt;
&lt;P&gt;Thank you for your suggestions.&lt;/P&gt;
&lt;P&gt;Best regards,&lt;/P&gt;</description>
      <pubDate>Fri, 20 Sep 2024 22:01:29 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944814#M47206</guid>
      <dc:creator>Ameurgen</dc:creator>
      <dc:date>2024-09-20T22:01:29Z</dc:date>
    </item>
    <item>
      <title>Re: bayesian method in sas</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944816#M47207</link>
      <description>&lt;P&gt;Did you actually run the zero-inflated and encounter problems? If so what problems?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Fri, 20 Sep 2024 22:36:20 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944816#M47207</guid>
      <dc:creator>ballardw</dc:creator>
      <dc:date>2024-09-20T22:36:20Z</dc:date>
    </item>
    <item>
      <title>Re: bayesian method in sas</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944817#M47208</link>
      <description>&lt;P&gt;yes,&amp;nbsp; i used zero inflate, but as i mentioned i musing quiet large data so proc NLmixed can handle the large matrice x dimension, so now im looking for another method, so i said may be the bayesian method can do the job,&lt;/P&gt;
&lt;P&gt;My data is around 200 000 records&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Thank you for your response&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;regards&lt;/P&gt;</description>
      <pubDate>Fri, 20 Sep 2024 23:54:46 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944817#M47208</guid>
      <dc:creator>Ameurgen</dc:creator>
      <dc:date>2024-09-20T23:54:46Z</dc:date>
    </item>
    <item>
      <title>Re: bayesian method in sas</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944818#M47209</link>
      <description>1) You can use PROC GLIMMIX to fit Possion Distribution of Mixed model. But you have a very large table.&lt;BR /&gt;2)If you want use Bayesian method of Mixed model ,Check PROC MCMC .&lt;BR /&gt;&lt;BR /&gt;And better post your statistic question at Stat Forum:&lt;BR /&gt;&lt;A href="https://communities.sas.com/t5/Statistical-Procedures/bd-p/statistical_procedures" target="_blank"&gt;https://communities.sas.com/t5/Statistical-Procedures/bd-p/statistical_procedures&lt;/A&gt;</description>
      <pubDate>Sat, 21 Sep 2024 01:58:36 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944818#M47209</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2024-09-21T01:58:36Z</dc:date>
    </item>
    <item>
      <title>Re: bayesian method in sas</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944825#M47210</link>
      <description>&lt;P&gt;thank you for your response &lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;A title="A reply to Ksharp's message from 09-20-2024" href="https://communities.sas.com/t5/SAS-Programming/bayesian-method-in-sas/m-p/944818#M370177" target="_blank"&gt;Ksharp&lt;/A&gt;, ill ckeck mcmc procedure , its quiet complex&amp;nbsp;&lt;/P&gt;
&lt;P&gt;what do you think about&amp;nbsp;&lt;SPAN&gt;Proc BGLIMM (Bayesian Generalized Linear Mixed model, can do the job.? what is the differences?&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;regards&lt;/P&gt;</description>
      <pubDate>Sat, 21 Sep 2024 13:34:55 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944825#M47210</guid>
      <dc:creator>Ameurgen</dc:creator>
      <dc:date>2024-09-21T13:34:55Z</dc:date>
    </item>
    <item>
      <title>Re: bayesian method in sas</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944827#M47203</link>
      <description>&lt;P&gt;For a count response, you can fit appropriate models (Poisson, negative binomial, or zero-inflated versions of either) in PROC GENMOD. They can also be fit PROC HPGENSELECT as well as in PROC COUNTREG and PROC HPCOUNTREG in SAS/ETS. Zero-inflated models can also be fit using PROC FMM.&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Sat, 21 Sep 2024 15:51:36 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944827#M47203</guid>
      <dc:creator>StatDave</dc:creator>
      <dc:date>2024-09-21T15:51:36Z</dc:date>
    </item>
    <item>
      <title>Re: bayesian method in sas</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944835#M47211</link>
      <description>Yes. You can do Bayesian method of Mixed model by PROC BGLIMM.&lt;BR /&gt;I almost forgot this PROC when &lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/15363"&gt;@SteveDenham&lt;/a&gt; mentioned it before.&lt;BR /&gt;</description>
      <pubDate>Sun, 22 Sep 2024 00:40:13 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944835#M47211</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2024-09-22T00:40:13Z</dc:date>
    </item>
    <item>
      <title>Re: bayesian method in sas</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944836#M47212</link>
      <description>"what is the differences?"&lt;BR /&gt;No different. &lt;BR /&gt;PROC BGLIMM is for rookie of Bayesian method.&lt;BR /&gt;PROC MCMC is for Bayes expert to do some customize method.</description>
      <pubDate>Sun, 22 Sep 2024 00:44:51 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944836#M47212</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2024-09-22T00:44:51Z</dc:date>
    </item>
    <item>
      <title>Re: bayesian method in sas</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944837#M47205</link>
      <description>@SteveDave is right. &lt;BR /&gt;GEE model(PROC GEE or PROC GENMOD) is good(high efficient) for your BIG table.&lt;BR /&gt;But GEE model is a little different with Mixed model.You can use both of them.</description>
      <pubDate>Sun, 22 Sep 2024 01:12:23 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944837#M47205</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2024-09-22T01:12:23Z</dc:date>
    </item>
    <item>
      <title>Re: bayesian method in sas</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944853#M47213</link>
      <description>&lt;P&gt;Thank you Sir&amp;nbsp;&lt;A class="trigger-hovercard" href="https://communities.sas.com/t5/user/viewprofilepage/user-id/18408" target="_blank"&gt;Ksharp,&amp;nbsp;&lt;/A&gt; follow-up&amp;nbsp; my questions,&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I do like&amp;nbsp;proc bglimm, it is straight forward application for LMM using bayesian method, but in my case i asking if any one cant run it in sas because , i have &lt;STRONG&gt;error '&amp;nbsp;proc bglimm not found&lt;/STRONG&gt; ' im using 9.4 version of sas but this procedure is not available.&lt;/P&gt;
&lt;P&gt;Thank you&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Regards&lt;/P&gt;</description>
      <pubDate>Sun, 22 Sep 2024 17:14:59 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944853#M47213</guid>
      <dc:creator>Ameurgen</dc:creator>
      <dc:date>2024-09-22T17:14:59Z</dc:date>
    </item>
    <item>
      <title>Re: bayesian method in sas</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944856#M47214</link>
      <description>&lt;P&gt;I can ruing proc bglimm without problem.&lt;/P&gt;
&lt;PRE&gt;
49   data MultiCenter;
50   input Center Group$ N SideEffect @@;
51   datalines;

NOTE: INPUT 语句到达一行的末尾时，SAS 转到新的一行。
NOTE: 数据集 WORK.MULTICENTER 有 30 个观测和 4 个变量。
NOTE: “DATA 语句”所用时间（总处理时间）:
      实际时间          0.01 秒
      CPU 时间          0.00 秒


67   ;
68
69   proc bglimm data=MultiCenter nmc=10000 thin=2 seed=976352
NOTE: 正在写入 HTML Body（主体）文件: sashtml.htm
70   plots=all;
71   class Center Group;
72   model SideEffect/N = Group / noint;
73   random int / subject = Center;
74   run;

NOTE: Generating the burn-in samples.
NOTE: Beginning sample generation.
NOTE: Beginning calculation of summary and diagnostics statistics.
NOTE: Generating diagnostic plots.
NOTE: “PROCEDURE BGLIMM”所用时间（总处理时间）:
      实际时间          2.59 秒
      CPU 时间          0.31 秒

&lt;/PRE&gt;
&lt;P&gt;What version of sas are you using? Mine is SAS9.4M7 .&lt;/P&gt;
&lt;PRE&gt;78   %put &amp;amp;=sysvlong. ;
SYSVLONG=9.04.01M7P080520
&lt;/PRE&gt;
&lt;P&gt;If your sas version is too low to run the proc bglimm. you could try&amp;nbsp;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/13633"&gt;@StatDave&lt;/a&gt;&amp;nbsp; 's suggestion GEE model by PROC GEE or PROC GENMOD .&lt;/P&gt;</description>
      <pubDate>Mon, 23 Sep 2024 00:56:07 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944856#M47214</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2024-09-23T00:56:07Z</dc:date>
    </item>
    <item>
      <title>Re: bayesian method in sas</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944948#M47216</link>
      <description>&lt;P&gt;Hi;&lt;/P&gt;
&lt;P&gt;Thank for the response,&amp;nbsp;&lt;/P&gt;
&lt;P&gt;My version sas is : SYSVLONG=9.04.01M5P091317&lt;/P&gt;
&lt;P&gt;I think i am far way back from the recent one, do have any idea how can i upgrade mine,&amp;nbsp; i think this is the reason why i cant run the&amp;nbsp;proc bglimm&lt;/P&gt;
&lt;P&gt;Thank you so much&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;&amp;nbsp;&lt;/PRE&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 23 Sep 2024 20:06:59 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944948#M47216</guid>
      <dc:creator>Ameurgen</dc:creator>
      <dc:date>2024-09-23T20:06:59Z</dc:date>
    </item>
    <item>
      <title>Re: bayesian method in sas</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944970#M47219</link>
      <description>You could freely use SAS by SAS OnDemand for Academic :&lt;BR /&gt;&lt;BR /&gt;&lt;A href="https://welcome.oda.sas.com/login" target="_blank"&gt;https://welcome.oda.sas.com/login&lt;/A&gt;</description>
      <pubDate>Tue, 24 Sep 2024 00:47:17 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/bayesian-method-in-sas/m-p/944970#M47219</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2024-09-24T00:47:17Z</dc:date>
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