Please, I need help converting character variables from wide to long. The MED1-MED8 variables are names of medication. I tried the following code but it it did not work. I only get the number of the medication but no MED variable. Please. kindly help. Below are my SAS code and the output.   Thank you DATA long_subset; SET subset; ARRAY aMED(1:8) MED1 - MED8 ; DO number = 1 to 8 ; MED = aMED(number); OUTPUT; END; DROP MED1 - MED8 ; RUN;   ... View more

Hello, I am struggling with codes for  multinomial ordinal(4 levels) longitudinal regression and its interpretation. The outcome variable has 4 levels which are ordered.  I used proc GENMOD and Proc GEE and the results are very different. I also need help with the interpretation. Initially I was hoping to get the differences of least squares means for each level of the outcome and predictor variable but it does not appear to give such results or am I doing it wrong. Please, I need help. Thank you       PROC GENMOD DATA=COVERED.Demographics ; CLASS complete_adherence2(ref='1') record_id ethnicity (ref='1'); MODEL complete_adherence2 = ethnicity / DIST=MULTINOMIAL LINK=CUMLOGIT; REPEATED SUBJECT=record_id/ corr=indep; lsmeans ethnicity/ ILINK diff e cl oddsratio ; RUN; PROC GEE DATA=COVERED.Demographics DESCENDING; CLASS complete_adherence2(ref='1') week record_id ethnicity (ref='1'); MODEL complete_adherence2 = ethnicity/ DIST=MULTINOMIAL; REPEATED SUBJECT=record_id / TYPE =indep WITHIN=week LOGOR=EXCH; lsmeans ethnicity/ ILINK diff e cl oddsratio ; RUN; Result from PROC GENMOD Result from PROC GEE     ... View more

Hello,   Please, I need help plotting this survival sample size calculation. The problem is with the plot x=effect. Please, what is the right thing? Below is my code. Thank you   ods listing style=htmlbluecml; ods graphics on; proc power; twosamplesurvival test=logrank curve("Standard") = 90 : 0.7 curve("Proposed") = (10 to 90 by 10):(0.95 0.9 0.85 0.8 0.75 0.7 0.65 0.60 0.55) groupsurvival = "Standard" | "Proposed" accrualtime = 0 followuptime = 90 power = 0.8 npergroup = .; plot x=effect min=0 max=90;run; ... View more