Hi all, Output from [proc glm] includes [estimate and standard error], can we get standard deviation instead? Thanks! Hao   https://communities.sas.com/t5/ODS-and-Base-Reporting/output-tables-from-proc-glm/m-p/239152  ... View more

You know that best, thank you! Hao ... View more

Hi all, I would like to exam effect of two kinds of treatment (A, B) on health outcome (death vs non), stratified by a third variable (level 1, level 2, level 3). The problem is that % by level in treatment A is so different from that in B. For example: 89% level 1, 5% level 2, and 6% level 3 in treatment A, while 35% level 1, 50% level 2, and 15% level 3 in treatment B. If I conduct the analyses among level 1 group, meaning 89% of the treatment A and only 35% of the treatment B. Do you think this may cause any bias? if so, can you please share some references about it? Thanks! ... View more

Hi all, I need your help. I want to have the adjusted Kaplan Meier by treatment group – a time varying covariate, adjusting for gender, race, crea, fib, alb. Of the covariates: gender, race, and crea (continuous variable) are fixed variables, and fib (categorical variable) and alb (continuous variable) are time varying covariates. For ‘crea’ I can get means by group, but I am not sure how to deal with alb as it is time varying covariate. The link below has some guidance for doing it but it is all about fixed variables. https://stats.idre.ucla.edu/sas/seminars/sas-survival/   I really appreciate any comments/guidance.   Hao   proc phreg data=TOTAL; class treatment (ref='0') gender(ref='0') race(ref='0') FIB (ref='0'); model (start_final,stop_final)*outcome (0)= treatment gender race crea FIB alb/RL; run;   ID Treatment outcome start_final stop_final gender race crea FIB alb 1 0 0 0 1 0 999 0.98 2 4 1 0 0 1 2 0 999 0.98 1 3.7 1 0 0 2 3 0 999 0.98 999 3.7 1 0 0 3 3.617 0 999 0.98 2 3.8 1 1 0 3.617 4 0 999 0.98 2 3.8 1 1 0 4 5 0 999 0.98 2 3.8 1 1 0 5 6 0 999 0.98 2 3.8 1 1 0 6 6.245 0 999 0.98 2 3.8 2 0 0 0 1 0 0 0.9 2 3.6 2 0 0 1 2 0 0 0.9 1 4.3 2 0 0 2 3 0 0 0.9 0 4 2 0 0 3 3.047 0 0 0.9 0 4.4 3 0 0 0 1 0 3 0.98 2 4.1 3 0 0 1 2 0 3 0.98 2 4 3 0 0 2 3 0 3 0.98 2 4.1 3 0 0 3 4 0 3 0.98 2 4 3 0 0 4 5 0 3 0.98 1 4.2 3 0 0 5 6 0 3 0.98 1 4.9 3 0 1 6 6.486 0 3 0.98 1 4.6       ... View more