topic Re: Combining LSMEANS Output in Statistical Procedures

Combining LSMEANS Output

lansoprazole — Mon, 27 Jan 2025 20:39:11 GMT

Hi,

I need help with combining the LSMEANS output of PROC GLIMMIX using PROC MIANALYZE.

This is LSMEANS output table:

I want to combine each pairwise comparison's odds ratio and adjusted CL.

I tried

PROC MIANALYZE parms=lsestim ;

MODELEFFECTS induction ;

RUN;

but it ended up with one combined estimate, as shown:

I tried other PROC MIANALYZE statements but did not get anything.

I wonder if I can get something similar to:

Induction _induction OR LCL UCL

A B 123 123 123

Thanks,

Re: Combining LSMEANS Output

SAS_Rob — Tue, 28 Jan 2025 00:55:45 GMT

The approach should be the same as it is in Proc MIXED. See the example in the usage note below.
https://support.sas.com/kb/30/715.html

Re: Combining LSMEANS Output

lansoprazole — Tue, 28 Jan 2025 03:12:55 GMT

Thanks for your help.

Re: Combining LSMEANS Output

lansoprazole — Tue, 28 Jan 2025 03:38:58 GMT

This is helpful. Hoewever, these steps only combine the estimate and the unadjusted stnd error and unadjusted CL. Do you know how to pool the adjusted lower and upper CL?

Re: Combining LSMEANS Output

SAS_Rob — Tue, 28 Jan 2025 13:15:15 GMT

The theory behind multiply imputed data only takes estimates and their standard errors and gives combined estimates. It does not lend itself to combining confidence intervals or p-values (adjusted or unadjusted). My suggestion would be to combine the estimates using MIANALYZE like shown and then save the p-values to a SAS data set. You could then use on the p-value adjustment methods available in Proc MULTTEST.

Note that not all the p-value adjustment methods are available in MULTTEST that are in GLIMMIX.

SAS Help Center: PROC MULTTEST Statement

 data outmi;
      do _imputation_=1 to 3;
      do trt='test','trt1','trt2','trt3';
      do rep=1 to 10;
         trtn+1;
         y=1.3+.18*trtn+rannor(123);
         output;
      end; end; end;
      run;
   
   proc glimmix data=outmi;
      by _imputation_;
      class trt;
      model y=trt;
      lsmeans trt/diff;
      ods output diffs=diff;
      run;
   
   data diff2;
      set diff;
      comparison=trt||' vs '||left(_trt);
      run;
   
   proc sort data=diff2;
      by comparison _imputation_;
      run;
   
   proc mianalyze data=diff2;
      by comparison;
      modeleffects estimate;
      stderr stderr;
	  ods output ParameterEstimates=estimate_ds(rename=(probt=raw_p comparison=test));
      run;
	  proc multtest inpvalues=estimate_ds holm hoc fdr bon;
	  run;