Dear SAS experts,   I use SAS for many years, but recently I meet following issue related to %str and cannot explain. Please see my SAS codes below:   data abc_101; a=3; run; %macro test1(id= ); %put abc_&id.; data a; set abc_&id.; run; %mend test1; %test1(id=%str(101));   MLOGIC(TEST1): Beginning execution. MLOGIC(TEST1): Parameter ID has value
101 MLOGIC(TEST1): %PUT abc_&id. abc_101 MPRINT(TEST1): data a; MPRINT(TEST1): set abc_101; ERROR: File WORK.ABC_.DATA does not exist. MPRINT(TEST1): run;   SAS log shows error that no WORK.ABC_.DATA found. It seems like there is a blank in the front of &id which cause SAS cannot find ABC_ data. Why %put statement shows correct string, but set statement cannot. I also tried different solutions below:   %macro test2(id= ); %let id=%trim(&id); %put abc_&id.; data a; set abc_&id.; run; %mend test2; %test2(id=%str(101));   %macro test3(id= ); %put abc_&id.; data a; set abc_&id.; run; %mend test3; %test3(id=101);   Both works. I use %str function all the time to pass macro parameters, but now I am kind of confused. Does any experts can help me explain why we need to use %trim in the macro program or not use %str function. Thank you so much.                ... View more

I am learning generalized linear mixed models using Proc Glimmix in SAS. I use an example from SAS website:   http://support.sas.com/documentation/cdl/en/statug/65328/HTML/default/viewer.htm#statug_glimmix_gettingstarted01.htm     data multicenter;    input center group$ n sideeffect;    datalines;  1  A  32  14  1  B  33  18  2  A  30   4  2  B  28   8  3  A  23  14  3  B  24   9  4  A  22   7  4  B  22  10  5  A  20   6  5  B  21  12  6  A  19   1  6  B  20   3  7  A  17   2  7  B  17   6  8  A  16   7  8  B  15   9  9  A  13   1  9  B  14   5 10  A  13   3 10  B  13   1 11  A  11   1 11  B  12   2 12  A  10   1 12  B   9   0 13  A   9   2 13  B   9   6 14  A   8   1 14  B   8   1 15  A   7   1 15  B   8   0 ; run;   data multicenter2;         set multicenter;         do i=1 to sideeffect;                y=1; output;         end;         do i=1 to n-sideeffect;                y=0; output;         end; run;   proc glimmix data=multicenter;    class center group;    model sideeffect/n = group / solution;    random intercept / subject=center; run;   proc glimmix data=multicenter2;         class center group;         model y = group /link=logit dist=binomial solution;         random intercept / subject=center; run;     The example uses events/trials syntax to run logistic regression with random effects. Since I am not familiar with events/trials syntax, I made an experiment. I generated standard 0/1 data and use GLMM with no events/trials syntax to run. I believed that the program produces exactly same results because both are logistic random effects model. However, results show that estimators and SD from two methods are same, but degree of freedom for group are different, which leads to different P-values. It looks like both are right. I don’t know which P-value I need to use.  Thank you in advance.         ... View more