One way to get what you wanted is to run PROC MIXED twice. Once with the (ref="1") option in the CLASS statement so you get what you want for the parameter estimates, and no STORE statement is needed. Then you can run PROC MIXED the second time, with no (ref="1") option in the CLASS statement. Use the STORE statement this time. Then your PROC PLM output should display the time in the order as you wanted. To speed up the second PROC MIXED, you might add NOTEST option in the MODEL statement, also add NOINFO NOITPRINT NOCLPRINT options in the PROC MIXED statement. Alternatively, you might define a format for your variable  time_dichotomous_number, such that the format for "1" comes first alphabetically, and assign this format to the variable  time_dichotomous_number. Yes, the values being plotted are the predicated values from your PROC MIXED model.   Hope this helps, Jill ... View more

TYPE=AR(1) does not account for unequal time spacings. TYPE=SP(POW)(time) does.  You might do both and compare the fit statistics to see which model fits your data better. When using TYPE=SP(POW)(time), you might want to use the original time values -- repeated/ type=sp(pow)(time)   SUBJECT = record_id;   For the plot, you might add OUTP=PREDDATA option in the MODEL statement in PROC MIXED. Then use PROC SGPPLOT later -- proc sort data=preddata; by site time; run; proc sgplot data=preddata; series y=pred x=time / group=site; run;   Hope this helps, Jill ... View more

It sounds to me that you need to perform a perspective power analysis (not a retrospective (post hoc) power analysis). PROC POWER and PROC  GLMPOWER perform perspective power analysis. You need to start with an exemplary data set that represents the conjectured values for your data (for PROC GLMPOWER and CUSTOM analysis in PROC POWER), or use other appropriate statement in PROC POWER for your analysis with conjectured parameter values. Thanks, Jill ... View more