Hello, I have a problem in fitting the following joint model for binary and longitudinal outcome using NLMIXED, the concept that I want to predict the probability of developing a medical condition (which is HT in this model ) based on a set of weekly measuremnts of a biomarker (Y). the joint model consists of two parts the first one is a mixed model to summarize the biomarker and a logistic model to obtain the predicted probabilties . proc nlmixed data=data qpoints=1; parameters beta0= 2.5 beta1= -0.22 a11= 0.34 a12= -0.01 a22=0.03 alpha0=10 alpha1=10 alpha2=10 s2=0.03; *the variance covariance matrix; v11 = a11*a11; v12 = a11*a12; v22 = a12*a12 + a22*a22; *The longitudinal model ; linplong = (beta0 + u1) + (beta1 + u2)*time; resid = (y-linplong); lllong = -0.5*(1.837876 + resid**2 / s2 + log(s2)); *The binary model; xb=alpha0+alpha1*u1+alpha2*u2; prob = exp(xb)/(1+exp(xb)); liklhd = (prob**HT)*((1-prob)**(1-HT)); llbin = log(liklhd); model HT ~ general(lllong + llbin); random u1 u2 ~ normal([0, 0],[v11,v12,v22]) subject=id; run; The above model fails to converge and I get the following error msg ERROR: No valid parameter points were found any ideas of what might be wrong in the above code ! Thanks in advance The first 5 subjects in the data id y HT time 9 2,1 0 2 9 1,42 0 3 9 1,08 0 4 9 0,95 0 5 9 0,73 0 6 9 0,34 0 7 10 NA 0 2 10 NA 0 3 10 NA 0 4 10 NA 0 5 10 NA 0 6 10 2,15 0 7 11 NA 0 2 11 NA 0 3 11 NA 0 4 11 NA 0 5 11 NA 0 6 11 NA 0 7 12 NA 0 2 12 NA 0 3 12 1,67 0 4 12 1,6 0 5 12 1,51 0 6 12 1,04 0 7 13 NA 0 2 13 NA 0 3 13 NA 0 4 13 0,11 0 5 13 NA 0 6 13 NA 0 7 14 2,56 1 2 14 2,08 1 3 14 1,88 1 4 14 1,79 1 5 14 1,74 1 6 14 NA 1 7 15 NA 1 2 15 NA 1 3 15 NA 1 4 15 2,41 1 5 15 2,43 1 6 15 NA 1 7
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