We opened up a ticket about this issue with SAS technical support. The underlying distribution is the 3 parameter Generalized Gamma, and technical support wrote back and said that it is not possible to estimate all three parameters at the same time in SAS 9.4, and the only solution was to fix one of them. They also wrote: "So, you would have to have your site license our SAS Viya product with release cadence of at least 2020.0.3 (like the release number) in order to have the fix that would allow LIFEREG to keep running when it encounters a floating point error in one BY group. The fix will probably also should be available in our next maintenance to SAS9.4 which should be out late this year or early next year according to my manager. All of our new development work and fixes are all in SAS Viya." I was excited to see that SAS Viya for Learners is available for students and educators, so I went back to this code at the beginning of December to see if it would run on that platform. The full code is a clinical trial design and has features for data generation and adaptions such as arms dropping and response adaptive randomization. Right now I'm generating the data in SAS, moving it over to R to complete the Bayesian part with a try-catch error in place, and then moving back to SAS for the post analysis. The reason I looked at SAS Viya is because I've been trying to see if I could somehow save the code that I wrote in SAS last year. ... View more

Yes, these are the current values for the macro variables.   ods output PosteriorSample=PosteriorSample11; proc lifereg data = IGamma1 noprint; by SimulID; class arm ; model Y1*L_evt1(0)= arm/dist = Gamma; bayes seed=1729 nmc=2500 thinning=1 coeffprior=normal(var=1E6) scaleprior=gamma(shape=86.9, iscale=65.4) gammashapeprior=normal(mean=0.49675, var=0.12051) nbi = 3000; run; ... View more

You are right. Thank you. This is the code that I used to produce that error.   ods output PosteriorSample=PosteriorSample11; proc lifereg data = IGamma1 noprint; by SimulID; class arm ; model Y1*L_evt1(0)= arm/dist = Gamma; bayes seed=&seed nmc = &mcmc thinning=&thinning coeffprior=normal(var=1E6) scaleprior=gamma(shape=&gamma_shape, iscale=&gamma_iscale) gammashapeprior=normal(mean=&gamma_mean, var=&gamma_var) nbi = &burn; run; ... View more

Yes, this is what it looks like:   ods output PosteriorSample=PosteriorSample; proc lifereg data = IGamma; class arm ; model Y*L_evt(0)= arm/dist = Gamma; bayes seed=1729 nmc = 2500 thinning=1 coeffprior=normal(var=1E6) scaleprior=gamma(shape=0.001, iscale=0.001) gammashapeprior=normal(mean=0, var=100) nbi = 2000; run; ... View more