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This is my code so far proc report data=report nowindows headline headskip SPANROWS split='|' spacing=4 style(header)={ just=center asis=on} style(column)={asis=on} style(report)={width=9 in}; by pageno; column pageno Varlab PACT_MNGT PACT_SEEKDR PACT_RESP PACT_OTPTS PACT_MED PACT_VIT PACT_INFRMDR PACT_ADHERE PACT_OPTIONS PACT_FACTR PACT_RESRCH; define pageno / order order=data noprint; define Varlab /order display "Item" group order = data style(header)=[just=left fontweight=bold asis=on] style(column)=[just=left fontweight=bold asis=on cellwidth=0.5in]; define PACT_MNGT /order display order = data style(header)=[just=left fontweight=bold asis=on] style(column)=[just=left asis=on cellwidth=.25in]; define PACT_SEEKDR /order display order = data style(header)=[just=left fontweight=bold asis=on] style(column)=[just=left asis=on cellwidth=.25in]; define PACT_RESP /order display order = data style(header)=[just=left fontweight=bold asis=on] style(column)=[just=left asis=on cellwidth=.25in]; define PACT_OTPTS /order display order = data style(header)=[just=left fontweight=bold asis=on] style(column)=[just=left asis=on cellwidth=.25in]; define PACT_MED /order display order = data style(header)=[just=left fontweight=bold asis=on] style(column)=[just=left asis=on cellwidth=.25in]; define PACT_VIT /order display order = data style(header)=[just=left fontweight=bold asis=on] style(column)=[just=left asis=on cellwidth=.25in]; define PACT_INFRMDR /order display order = data style(header)=[just=left fontweight=bold asis=on] style(column)=[just=left asis=on cellwidth=.25in]; define PACT_ADHERE /order display order = data style(header)=[just=left fontweight=bold asis=on] style(column)=[just=left asis=on cellwidth=.25in]; define PACT_OPTIONS /order display order = data style(header)=[just=left fontweight=bold asis=on] style(column)=[just=left asis=on cellwidth=.25in]; define PACT_FACTR /order display order = data style(header)=[just=left fontweight=bold asis=on] style(column)=[just=left asis=on cellwidth=.25in]; define PACT_RESRCH /order display order = data style(header)=[just=left fontweight=bold asis=on] style(column)=[just=left asis=on cellwidth=.25in]; compute PACT_MNGT; if PACT_MNGT GE 0.80 AND PACT_MNGT LT 1 then call define(_col_,"style","style={background=red}"); else if PACT_MNGT LE 0.40 then call define(_col_,"style","style={background=yellow}"); endcomp; compute PACT_SEEKDR; if PACT_SEEKDR GE 0.80 AND PACT_SEEKDR LT 1 then call define(_col_,"style","style={background=red}"); else if PACT_SEEKDR NE . AND PACT_SEEKDR LE 0.40 then call define(_col_,"style","style={background=yellow}"); endcomp; run; Towards the end, I am applying the same code (in red) to highlight correlations that are GE 0.80 OR LE 0.40 for all 11 item variables. Is there an easy way to do this without copying and pasting each comp/endcomp block and changing the variable within each block in proc report?  Basically I am asking, is there a way I can write one comp/endcomp block and apply the same conditional formatting for all 11 PACT variables?     ... View more

I am working on my doctoral dissertation right now. I have my dataset *wide format, 12,000 subjects) which contains Subject ID, race age and sex for my research study. My goal is to randomize the Subject Ids in my dataset into 2 equal groups (1:1 ratio) and assign each subject to a treatment arm (Group A or Group B) for each subject in my dataset. I would like to have the treatment arm to be closely balanced in  race (White, Black, Asian, Other), age (continuous variable) and sex (binary).  I assume I need to recode age into age groups of some sort to help with the balance. I have been reading up on randomization methods in SAS and looks like PROC PLAN or PROC SURVEYSELECT is the way to do it. At the moment, I can't figure out the differences between the two approaches, which approach fits would get this task done correctly and how exactly to write my code to create this treatment arm variable. So I was wondering if someone can help me figure out how to do this? I haven't done any type of randomizations before, so I am completely lost here.   Screenshot below is my example, I have the dataset, I want to randomize 12,000 subjects into either group A or Group B and have a that as variable treatment arm. When comparing the group A vs group B: t-test (age) or chi-square (Race/sex), p-value are non-significant.  The goal is to make the 2 groups as comparable as possible (e.g. Non-Sig). I know it won't be a perfect non-sig P-value, but overall want it as P>0.05.     ... View more