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    <title>topic Significance test of intercepts difference_more details in SAS Programming</title>
    <link>https://communities.sas.com/t5/SAS-Programming/Significance-test-of-intercepts-difference-more-details/m-p/620554#M182358</link>
    <description>&lt;P&gt;Hello everyone,&lt;/P&gt;&lt;P&gt;I'm a beginner in sas and I'm wondering a question.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I have 10 models to estimate in order to say which is the correct one to predict returns (rp). Consequently, I decided to make 12 main comparisons (2 by 2) of my regression models by statistically comparing each time only my 2 intercepts (not the other betas coefficients) with tests. The trouble is I do not want to do this only with one returns serie but ultimately with around 2,000 (returns series). However, for now, I would like to make it as easy as I can. If I can do this on 1 serie, I can do it on 2,000.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;So ultimately, I would like firstly to save on a distinct database all the parameters of my 10 regressions models (intercepts, bêtas coefficients, p-value, F-test, etc.). Secondly, I would like, for each model,to&amp;nbsp;compute intercepts mean,&amp;nbsp;intercepts percentiles,&amp;nbsp;intercepts distribution, etc. Secondly, to know which model is correct to predict returns, I would like to compare 2 by 2 all of my 10 models by testing each time whether the 2 intercepts are statistically the same or not.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Please find below my 12 comparisons:&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;proc reg data=modelization outest=est; /*1*/
      M1: model rp=rm / selection=rsquare b best=1;
	  MFS1: model rp=rm rm_zdy rm_ztbl rm_ztms rm_zdfy / selection=rsquare b best=1;
   proc print data=est;
   run;

proc reg data=modelization outest=est; /*2*/
      M2: model rp=rm rmrsq / selection=rsquare b best=1;
      MFS2: model rp=rm rm_zdy rm_ztbl rm_ztms rm_zdfy rmrsq / selection=rsquare b best=1;
   proc print data=est;
   run;

proc reg data=modelization outest=est; /*3*/
	  M1: model rp=rm / selection=rsquare b best=1;
	  MPM10: model rp=rm rm_pred_mean / selection=rsquare b best=1;
proc print data=est;
   run;

proc reg data=modelization outest=est; /*4*/
	  M2: model rp=rm rmrsq / selection=rsquare b best=1;
	  MPM11: model rp=rm rm_pred_mean rmrsq / selection=rsquare b best=1;
proc print data=est;
   run;

proc reg data=modelization outest=est; /*5*/
	  M1: model rp=rm / selection=rsquare b best=1;
	  MCFG1: model rp=rm zdy ztbl ztms zdfy rm_zdy rm_ztbl rm_ztms rm_zdfy / selection=rsquare b best=1;
proc print data=est;
   run;

proc reg data=modelization outest=est; /*6*/
	  M2: model rp=rm rmrsq / selection=rsquare b best=1;
      MCFG2: model rp=rm zdy ztbl ztms zdfy rm_zdy rm_ztbl rm_ztms rm_zdfy rmrsq / selection=rsquare b best=1;
proc print data=est;
   run;

proc reg data=modelization outest=est; /*7*/
      M1: model rp=rm / selection=rsquare b best=1;
	  MPM20: model rp=pred_mean rm rm_pred_mean / selection=rsquare b best=1;
proc print data=est;
   run;

proc reg data=modelization outest=est; /*8*/
      M2: model rp=rm rmrsq / selection=rsquare b best=1;
      MPM21: model rp=pred_mean rm rm_pred_mean rmrsq / selection=rsquare b best=1;
proc print data=est;
   run;

proc reg data=modelization outest=est; /*9*/
	  MFS1: model rp=rm rm_zdy rm_ztbl rm_ztms rm_zdfy / selection=rsquare b best=1;
      MPM10: model rp=rm rm_pred_mean / selection=rsquare b best=1;
proc print data=est;
   run;

proc reg data=modelization outest=est; /*10*/
      MFS2: model rp=rm rm_zdy rm_ztbl rm_ztms rm_zdfy rmrsq / selection=rsquare b best=1;
      MPM11: model rp=rm rm_pred_mean rmrsq / selection=rsquare b best=1;
proc print data=est;
   run;

proc reg data=modelization outest=est; /*11*/
	  MCFG1: model rp=rm zdy ztbl ztms zdfy rm_zdy rm_ztbl rm_ztms rm_zdfy / selection=rsquare b best=1;
	  MPM20: model rp=pred_mean rm rm_pred_mean / selection=rsquare b best=1;
proc print data=est;
   run;

   proc reg data=modelization outest=est; /*12*/
	  MCFG2: model rp=rm zdy ztbl ztms zdfy rm_zdy rm_ztbl rm_ztms rm_zdfy rmrsq / selection=rsquare b best=1;
      MPM21: model rp=pred_mean rm rm_pred_mean rmrsq / selection=rsquare b best=1;    
   proc print data=est;
   run;&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;I hope that you can help me to write the codes relative to my goals.&lt;/P&gt;&lt;P&gt;Thank you,&lt;/P&gt;</description>
    <pubDate>Tue, 28 Jan 2020 16:27:55 GMT</pubDate>
    <dc:creator>pmorel3</dc:creator>
    <dc:date>2020-01-28T16:27:55Z</dc:date>
    <item>
      <title>Significance test of intercepts difference_more details</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Significance-test-of-intercepts-difference-more-details/m-p/620554#M182358</link>
      <description>&lt;P&gt;Hello everyone,&lt;/P&gt;&lt;P&gt;I'm a beginner in sas and I'm wondering a question.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I have 10 models to estimate in order to say which is the correct one to predict returns (rp). Consequently, I decided to make 12 main comparisons (2 by 2) of my regression models by statistically comparing each time only my 2 intercepts (not the other betas coefficients) with tests. The trouble is I do not want to do this only with one returns serie but ultimately with around 2,000 (returns series). However, for now, I would like to make it as easy as I can. If I can do this on 1 serie, I can do it on 2,000.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;So ultimately, I would like firstly to save on a distinct database all the parameters of my 10 regressions models (intercepts, bêtas coefficients, p-value, F-test, etc.). Secondly, I would like, for each model,to&amp;nbsp;compute intercepts mean,&amp;nbsp;intercepts percentiles,&amp;nbsp;intercepts distribution, etc. Secondly, to know which model is correct to predict returns, I would like to compare 2 by 2 all of my 10 models by testing each time whether the 2 intercepts are statistically the same or not.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Please find below my 12 comparisons:&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;proc reg data=modelization outest=est; /*1*/
      M1: model rp=rm / selection=rsquare b best=1;
	  MFS1: model rp=rm rm_zdy rm_ztbl rm_ztms rm_zdfy / selection=rsquare b best=1;
   proc print data=est;
   run;

proc reg data=modelization outest=est; /*2*/
      M2: model rp=rm rmrsq / selection=rsquare b best=1;
      MFS2: model rp=rm rm_zdy rm_ztbl rm_ztms rm_zdfy rmrsq / selection=rsquare b best=1;
   proc print data=est;
   run;

proc reg data=modelization outest=est; /*3*/
	  M1: model rp=rm / selection=rsquare b best=1;
	  MPM10: model rp=rm rm_pred_mean / selection=rsquare b best=1;
proc print data=est;
   run;

proc reg data=modelization outest=est; /*4*/
	  M2: model rp=rm rmrsq / selection=rsquare b best=1;
	  MPM11: model rp=rm rm_pred_mean rmrsq / selection=rsquare b best=1;
proc print data=est;
   run;

proc reg data=modelization outest=est; /*5*/
	  M1: model rp=rm / selection=rsquare b best=1;
	  MCFG1: model rp=rm zdy ztbl ztms zdfy rm_zdy rm_ztbl rm_ztms rm_zdfy / selection=rsquare b best=1;
proc print data=est;
   run;

proc reg data=modelization outest=est; /*6*/
	  M2: model rp=rm rmrsq / selection=rsquare b best=1;
      MCFG2: model rp=rm zdy ztbl ztms zdfy rm_zdy rm_ztbl rm_ztms rm_zdfy rmrsq / selection=rsquare b best=1;
proc print data=est;
   run;

proc reg data=modelization outest=est; /*7*/
      M1: model rp=rm / selection=rsquare b best=1;
	  MPM20: model rp=pred_mean rm rm_pred_mean / selection=rsquare b best=1;
proc print data=est;
   run;

proc reg data=modelization outest=est; /*8*/
      M2: model rp=rm rmrsq / selection=rsquare b best=1;
      MPM21: model rp=pred_mean rm rm_pred_mean rmrsq / selection=rsquare b best=1;
proc print data=est;
   run;

proc reg data=modelization outest=est; /*9*/
	  MFS1: model rp=rm rm_zdy rm_ztbl rm_ztms rm_zdfy / selection=rsquare b best=1;
      MPM10: model rp=rm rm_pred_mean / selection=rsquare b best=1;
proc print data=est;
   run;

proc reg data=modelization outest=est; /*10*/
      MFS2: model rp=rm rm_zdy rm_ztbl rm_ztms rm_zdfy rmrsq / selection=rsquare b best=1;
      MPM11: model rp=rm rm_pred_mean rmrsq / selection=rsquare b best=1;
proc print data=est;
   run;

proc reg data=modelization outest=est; /*11*/
	  MCFG1: model rp=rm zdy ztbl ztms zdfy rm_zdy rm_ztbl rm_ztms rm_zdfy / selection=rsquare b best=1;
	  MPM20: model rp=pred_mean rm rm_pred_mean / selection=rsquare b best=1;
proc print data=est;
   run;

   proc reg data=modelization outest=est; /*12*/
	  MCFG2: model rp=rm zdy ztbl ztms zdfy rm_zdy rm_ztbl rm_ztms rm_zdfy rmrsq / selection=rsquare b best=1;
      MPM21: model rp=pred_mean rm rm_pred_mean rmrsq / selection=rsquare b best=1;    
   proc print data=est;
   run;&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;I hope that you can help me to write the codes relative to my goals.&lt;/P&gt;&lt;P&gt;Thank you,&lt;/P&gt;</description>
      <pubDate>Tue, 28 Jan 2020 16:27:55 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Significance-test-of-intercepts-difference-more-details/m-p/620554#M182358</guid>
      <dc:creator>pmorel3</dc:creator>
      <dc:date>2020-01-28T16:27:55Z</dc:date>
    </item>
    <item>
      <title>Re: Significance test of intercepts difference_more details</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Significance-test-of-intercepts-difference-more-details/m-p/620556#M182360</link>
      <description>&lt;P&gt;This is a duplication of a question asked in another thread, which I have attempted to answer (partially).&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Let's keep all discussion in that other thread at&amp;nbsp;&lt;A href="https://communities.sas.com/t5/SAS-Programming/Significance-test-of-intercepts-difference/td-p/619947" target="_blank" rel="noopener"&gt;https://communities.sas.com/t5/SAS-Programming/Significance-test-of-intercepts-difference/td-p/619947&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;STRONG&gt;DO NOT REPLY HERE.&lt;/STRONG&gt;&lt;/P&gt;</description>
      <pubDate>Tue, 28 Jan 2020 16:34:30 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Significance-test-of-intercepts-difference-more-details/m-p/620556#M182360</guid>
      <dc:creator>PaigeMiller</dc:creator>
      <dc:date>2020-01-28T16:34:30Z</dc:date>
    </item>
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