SAS Support Communities

Dear all,   I would like to use the PROC BGLIMM to model a logistic regression with  non informative prior.  However I would like firstly to compare PROC BGLIMM with PROC LOGISTIC without any information about the prior. My concern is that I do not obtain same results. Is there something I do incorrectly?   proc logistic data=ANcount8(where=(AVISIT="Visit 10" and HiSCR50 ne "")) ; class TRT(ref='0') FASTRESC(ref='STAGE II') / param=ref; model HiSCR50(event="Y") = TRT FASTRESC / link=logit; run; Estimation of TRT1: -0.6750   proc bglimm data=ANcount8(where=(AVISIT="Visit 10" and HiSCR50 ne "")) seed=1235841 nbi=1000 nmc=100000 thin=20 plots=all; class TRT(ref='0') FASTRESC(ref='STAGE II')/ param=ref; model HiSCR50(event="Y") = TRT FASTRESC / dist=binary link=logit ; run; Estimation TRT1: -1.0248    Thank you in advance ... View more

Dear all,   I would like to create a Bayesian linear mixed model for repeated measurements (visits) with a random intercept for subjects. I have 2 treatments (Placebo and Active).  I have also interaction between treatment and visits and I would like to add a prior distribution for the placebo effect.   I am using the proc mcmc but I am not sure how to add the prior distribution for the placebo effect.  I should create one indicator variable for treatment (1=active, 0=placebo) but for which beta I should specify the prior distribution?  Y=B0 + B1*treatment+ B2*Visit + B3*Visit*treatment Is it for B0 only in this case? or should I create 2 indicator variables: placebo (1, otherwise 0) and active (1, otherwise 0) and then add the prior distribution for the beta related to placebo indicator variable and for the beta related to the placebo indicator*visit variable?   Thank you in advance,   Best regards, Clemence ... View more

Dear all,   I would like to run a Bayesian linear mixed model by adding historical data to amend the prior distribution of the placebo arm. Therefore, I would like to specify a conditional prior distribution for the placebo effect with a normal distribution.  Is it possible to do this with PROC BGLIMM or should I use PROC MCMC?  In my model I don't have a variable Placebo but I have a variable for Treatment (with Placebo and Active treatment as modalities).    Thank you in advance,   Regards, Clemence   ... View more

Dear all,   I would like to compare PROC GLM and PROC MIXED for one model and I was wondering if it was possible to get the correspondance of "covtest" in proc mixed with the prog glm?   My model with proc mixed is:   proc mixed data=ADPP covtest cl method=type3 alpha=0.1; by PARAMN PARAMCD; class TRTAN SEX USUBJID; model AVAL = TRTAN SEX / solution ddfm=kr; random USUBJID(SEX) / type=vc; run;   My model with prog glm is:   proc glm data=ADPP ; class TRTAN SEX USUBJID; model AVAL = TRTAN SEX USUBJID(SEX) ; random USUBJID(SEX) / test ; run;   I obtain the same Mean Squares with the two models but with the proc GLM I don't have the covariance parameters with the interval of confidence.   Is-it possible to obtain these parameters with the proc glm ? If yes, how I can get them ?   Thank you in advance.   Best regards; Clg ... View more