Hi everybody, I am trying to run zip model in proc nlmixed (SAS 9.4): proc nlmixed data=migraine maxiter=10000; parms b0 =1 b1 = 0 b2= 0 c0 =1 c1 = 0 c2= 0 z0= 0 z1= 0 z2= 0 z3= 0 rho=-0.2 s2u =1 s2v=1; /*linear predictor for mixture probability of zero part*/ linp_pi = b0 + b1*time+ b2*group*time+ u; pi = exp(linp_pi)/(1+exp(linp_pi)); /*linear predictor for mean of counts (poisson part)*/ linp_mu = c0 + c1*time+ c2*group*time+ v; mu = exp(linp_mu); logsigu2 = z0 + z1*group; logsigv2 = z2 + z3*group; s2u=exp(logsigu2); suv=rho*sqrt(exp(logsigu2)*exp(logsigv2)); s2v=exp(logsigv2); if attack=0 then ll = log((pi) + (1-pi)*exp(-mu)); else ll = log((1-pi)) + attack*log(mu) - lgamma(attack+1)- mu; model attack ~ general(ll); random u v ~ normal([0,0],[s2u,suv,s2v]) subject=id; run; I am attaching longitudinal data. While running my model for "cov hess, tech=newrap, method= gauss, maxiter, qmax noad, seed=12345", Unfortunately, I always face this warning and have some large SE or no SE . WARNING1: The final Hessian matrix is full rank but has at least one negative eigenvalue. Second-order optimality condition violated. WARNING2: The final Hessian matrix is not positive definite, and therefore the estimated covariance matrix is not full rank and may be unreliable. The variance of some parameter estimates is zero or some parameters are linearly related to other parameters. I changed initial values, method, qmax...again and again. Sometimes I have Error: Optimization cannot be completed. I don't know what to do. I have a principal question: How do I find appropriate initial values? Thank you for your time. Parameter Estimates Parameter Estimate Standard Error DF t Value Pr > |t| 95% Confidence Limits Gradient b0 -2.6089 0.4103 64 -6.36 <.0001 -3.4285 -1.7893 6.81751 b1 -1.5772 14.2856 64 -0.11 0.9124 -30.1160 26.9617 0.071280 b2 -2.5369 12.5514 64 -0.20 0.8405 -27.6111 22.5373 0.078330 c0 0.7799 0.1335 64 5.84 <.0001 0.5133 1.0466 -25.8045 c1 -0.4147 0.09284 64 -4.47 <.0001 -0.6002 -0.2292 19.9297 c2 0.09872 0.05501 64 1.79 0.0775 -0.01118 0.2086 -37.4677 z0 0.2445 2.2688 64 0.11 0.9145 -4.2881 4.7770 4.09923 z1 0.4000 1.5060 64 0.27 0.7914 -2.6087 3.4087 6.45820 z2 -0.9555 1.6735 64 -0.57 0.5700 -4.2988 2.3877 -1.27785 z3 -1.3047 1.0613 64 -1.23 0.2234 -3.4249 0.8155 -3.62090 rho 0.07197 2.0419 64 0.04 0.9720 -4.0072 4.1512 0.76599 s2u 2.8419 . 64 . . . . 1.73494 s2v 0.02830 0.06871 64 0.41 0.6818 -0.1090 0.1656 -73.7197
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