Hi again SAS communities   i'm working on a KM curve plotting gender (female vs male survival) and for the life of me I cannot figure out how to get my lines to be different colors     They're both blue here, and I'd like the female line to be red--and have that shown in the legend label. I feel like I've looked all over the internet and SAS communities to figure it out, and I see absolutely nothing. I'd also like to stay away from Macros if possible. I don't know how to use it.    This is what I have currently:  libname Hetal "\\tuftsmc\home\hpatel3\SAS Datasets"; run; ods graphics on/attrpriority=color; ods select all; ods output survivalplot=genderobs; proc lifetest data=hetal.gender_obskm conftype=loglog plot=(s) plots=(survival(CL strata=panel)) timelist=(1 5 10) outs=Survival_Rates reduceout alpha=.05; /* Surival_rates gives you confidence intervals in "output data" tab*/ time FU_time*NYHA_stat(0); strata gender / test= logrank; by gender; where NYHA_Stat=1 AND Obst_Stat=1; Title "Male patients with obstructive HCM in NYHA Stage III/IV"; run; proc sgplot data=genderobs noborder nowall cycleattrs; step x=Time y=Survival/ group=gender lineattrs=(color=darkblue thickness=2 pattern=solid) name="s" legendlabel="obstructive"; format gender genfmt.; xaxis display=(noticks) label="Years" values=(0 to 10 by 5) min=0 max=10 labelattrs=(size=10 weight=bold ); yaxis label='Survival Probability' values=(0 to 1.0 by 0.2) min=0 max=1.0 labelattrs=(size=10 weight=bold); run; ods graphics off; I think what's wrong is the specific line I've bolded above, but I really don't know at this point what to change. I would settle for females being a dashed line if that's easier. Really just something to differentiate.    Here is what my curve currently looks like:    ... View more

Hello, I have been asked to calculate odds ratios and confidence intervals using Proc Univariate (and then calculate the odds ratio,  Pvals, and confidence limits using a multivariate analysis for the variables with significant P-values )   Honestly, this whole process of why doesn't make a whole lot of sense to me. Does anyone have any useful resources that would help me understand   why I need to calculate univariate before multivariate?   For reference, I have my disease status (1= alive, 0=dead) and then 7 risk factors (2 are continuous and 5 are categorical binary)   my code looks like:   libname Hetal "\\tuftsmc\home\hpatel3\SAS Datasets"; run;     proc logistic data=hetal.es_regre desc plots(only)=(effect oddsratio(type=horizontalstat)) desc; model adv_hf (event="1")= age_diag ; run;     I've got the multivariate analysis figured out, but am I correct in assuming I would have to do proc logistic 7 times for each risk factor being set to the disease status to get odds ratios for each variable? I've been trying to find any resources on how to do this in SAS, but have had no luck. Any resources or help understanding would be great!   ... View more

Hi Guys,   I've posted a bit on this topic, so sorry if you've seen this before but I figured this might be a better board to get my specific question asked.   I am honestly fairly new to SAS and was thrown in the deep end, so a bunch of the technical jargon goes over my head, FYI.   I'm trying to run a Multivariable Analysis that wants to see if there is a correlation between status of disease (1= they have it 0= they don't) and 7 risk factors (symptoms). 5 of them  are categorical (1= yes 0-no)  2 of them are continuous    I've dug it down to the fact that  I need to use Proc Corr ( I think)   but do I use Kendall's Tau as my R2 and P value or Pearson's for my my R2 and P-value? ..or both depending on whether it's continuous or categorical?       ---- But HONESTLY, wouldn't it be easier to use proc logistic since it doesn't worry about categorical or continuous and the outcome is binary? ... View more