Hello everyone,   I am trying to use SAS (SAS University Edition) to fit a nonlinear mixed-effects model to my data. Before fitting the model, I first import the data into SAS. This data consists in repeated measurements (over time) for a group of individuals (the dataset is attached). To distinguish between individuals, I use a grouping variable grp. This dataset is not a 'synthetic dataset' (ie. the data was not generated using the model itself or another model).   Here is the code to import the data :   filename mydata '/folders/myfolders/data_for_nlmixed_procedure.txt'; data datagen; infile mydata delimiter=','; input X Y grp; run;   Once the data is imported into SAS, here is the code I use (and the model I want to fit to my data) :   proc nlmixed data=datagen tech=quanew linesearch=6 method=gauss qpoints=1 maxfunc=100000 maxiter=6000; parms p0=1.33301 t0=71.7015 v0=-0.0002 s2gamma=0.48836 s2tau=40.5372 s2e=0.02251; model Y ~ normal( p0 + exp(gamma)*v0*(X-t0-tau) , s2e); random gamma tau ~ normal([0, 0], [s2gamma, 0, s2tau]) subject=grp out=eb_rh_insula; run;   When using this code, I often encounter the following error : "No valid parameter points were found". For example, this happens by choosing as initial values : p0=3.33 t0=51 v0=-0.002 s2gamma=0.48 s2tau=40 s2e=0.02. To deal with this error message, I assumed I had to try different starting values. Once I found correct starting values, the procedure NLMIXED often has difficulties to converge. For example, running the code above gives me :   ERROR: QUANEW Optimization cannot be completed. NOTE: The gradient of the objective function cannot be computed during the optimization process.   I have tried other optimization techniques (tech=newrap, trureg,...) but I keep getting error messages.  I would like to understand what is causing these difficulties. Is it a problem with the model itself ? I believe the model is identifiable. Is it a problem with my NLMIXED procedure ? I would really appreciate new ideas here !   Thank you ! ... View more