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openatom · ‎12-08-2020

Thank you, this is helpful. I noticed that LIFEREG will also output something it calls "shape" and "scale," but they appear to be inverses and not directly related to the Weibull PDF in SAS (https://documentation.sas.com/?cdcId=pgmsascdc&cdcVersion=9.4_3.5&docsetId=fedsqlref&docsetTarget=p1q5wrhpvsgt1pn1dswx95zo2i4p.htm&locale=en) where a=shape and lambda=scale. In LIFEREG, I assume that the "scale" is lambda? (shape) a = exp(Intercept) ? (scale) lambda = lambdac ? Does this seem correct?

openatom · ‎12-05-2020

I am trying to do a simple simulation where I create several different replication datasets (replicating a known dataset I have). I'm using SAS 9.4 and here is the code I'm trying to use for simulation (found on: http://sas-and-r.blogspot.com/2010/03/example-730-simulate-censored-survival.html😞 data simcox; beta1 = 2; lambdat = 0.002; *baseline hazard; lambdac = 0.004; *censoring hazard; do i = 1 to 1000; x1 = rand("Bernoulli",0.5); linpred = exp(-beta1*x1); t = rand("WEIBULL", 1, lambdaT * linpred); * time of event; c = rand("WEIBULL", 1, lambdaC); * time of censoring; time = min(t, c); * which came first?; censored = (c lt t); output; end; run; I am having trouble figuring out the values to use (bold in red). How do I know what to specify beta and lambdas as? Is there a way to find estimates of these values by running a Cox model on my known data, then using these estimated values of beta and lambdas for my simulation? If so, please explain in detail how to find these. Thank you.

openatom · ‎03-22-2020

HR= hazard ratio I would like the percentile of a hazard ratio for a continuous variable (blood pressure). My understanding is that when I run a proc phreg if HR=1.06, with a continuous predictor, the HR tells me for every one unit increase in that variable (blood pressure), the HR increases by 1.06. I need a way to find percentiles of this HR since it is a continuous variable.

openatom · ‎03-22-2020

I'm using SAS 9.4. I ran a proc phreg with a continuous predictor (bp) and I am trying to get a percentile for this HR. It looks like phreg has a "percent=" option, but I can't figure out how to use it correctly. Could anyone advise? Here is the basic phreg code I'm working with: proc phreg data=new; model date*censor(0)=bp; run;

openatom · ‎08-03-2019

I'm using SAS 9.4. I'm new to IML and a little unfamiliar. I have a code that works, however, I am trying to create an X matrix with over 1000 variables (all named the same thing with corresponding numbers at the end). I can't figure out how to enter this in proc iml, as I tried var1-var1000 and var1:var1000 and proc iml does not like the hyphen or colon. Here is my code: proc iml; use dataset; read ALL var {var1-var1000} into x; read all var {yvar} into y; close dataset; xBar = mean(x); /* save row vector of means */ yBar = mean(y); /* save mean of Y */ x = x - xBar; /* center X and y; do not add intercept */ y = y - yBar; . . . The rest of the code is irrelevant to my question. If I run the code with just a few x variables and state: read ALL var {var1 var2 var3} into x; Then my code runs fine. However, I can't type over 1000 variables. How can I include ALL variables at once into this matrix X?

openatom · ‎05-28-2019

I am trying to run a power simulation for a mixed effects model, however I do not have the data. I have the variances, difference in slope to detect, corr(Y_ij, Y_ik), and sample variance of time. The only examples I have found for power simulation are for t tests. How do I incorporate mixed effects model? I'm using SAS 9.4. d=4 alpha=0.05 between variance = 5 within variance = 45 t=1, 2, 3, 4 (equally spaced) n=100

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Re: Simulate data for PHREG Cox Model

Simulate data for PHREG Cox Model

Re: Percentile of continuous hazard ratio

Percentile of continuous hazard ratio

Proc IML creating X matrix with over 1000 variables from dataset

Power simulation for Mixed effects model