Thomas, When you got variable names like COL1, COL2 coming out of PROC TRANSPOSE, that's a result of failing to create _NAME_ first.  PROC TRANSPOSE uses _NAME_ to determine the variable names in the output. I just wanted to confirm, when you have variable names like Q.2.Med1 and Q.2.Med0 ... SAS will not let you use a dot as part of a variable name.  It will use underscores instead (and PROC TRANSPOSE will do that automatically).  I assume that's OK. The "1" or "0" at the end of the variable names ... is that the value of SP_vs_MD?  If so, is SP_vs_MD character or numeric? I think we're in the home stretch here ... not much more to do to wrap this up. ... View more

Thomas, I'm afraid that work beckons, and I won't be able to give you a complete answer here, just a few notes. First, it should be possible to run all 7 STs at once.  You might skip this at first, getting it to work for a single ST as a starting point.  But it would certainly be possible to code statements like these at the proper points: _name_ = 'st' || put(st,1.) || compress(question, ' .'); class st idnum question; But without attempting that hurdle, first, in the PROC SUMMARY, modify the OUTPUT statement to get both statistics: output out=temp (keep=idnum question mean std) mean=mean std=std; Then in the DATA step that is needed anyway, construct the combination variable: data temp;    set temp;    _name_ = 'st1' || compress(question, ' .');    new_response = put(mean, 3.1) || '+-' || put(std, 3.1); run; Then use new_response instead of response within PROC TRANSPOSE. Good luck.  ... View more

PROC MEANS can generate standard deviations in the output data set, as well as means. Part of the answer depends on what you want your report to look like.  Should the standard deviations form a second row for each IDNUM, or should they form additional columns on the existing row? Also note, you will have a lot of missing standard deviations when there is only one response. ... View more

Art, Looks like our solutions are converging. Those duplicate ids must have come from a test that didn't use PROC SUMMARY first. ... View more

If you combine our solutions, it should work. First, apply Tom's summary. Then use Art's code (or my revised code with the updated assignment for _name_), using the output data set from PROC SUMMARY as the input to PROC TRANSPOSE. Here's a more complete version: proc summary data=before nway missing;    class idnum question;    var response;    where question ne 'CanM';    output out=temp (keep=idnum question response) mean=; run; data temp;    set temp;    _name_ = 'st1' || compress(question, ' .'); run; proc transpose data=before out=after;    by idnum;    var response; run; ... View more

Art, Yes, depending on what is really needed as output I probably should have used: _name_ = 'st1' || compress(question, ' .'); It's not 100% clear to me whether the new variable names should start with "st1" or whether the 3rd character should vary depending on the response.  Given the follow-up information, it should probably remain "st1". ... View more

Ahh, much better now that you fixed the output structure.  This utilizes a neat feature that Art used last week: data before;    set before;    _name_ = compress( 'st' || put(response,1.) || question, ' .'); run; proc transpose data=before out=after;    by idnum;    var response; run; If you have responses that could be 2 digits long, replace the 1. format with the z2. format. Good luck. ... View more