@jiltao @SteveDenham Thank you for the insights, I am following. However, based on the posted G and R matrices, I have further questions: 1. How do I calculate the percentage contribution of each estimated variance component? 2. How do we get the overall error variance when heterogeneous error variance for each subject is displayed? ... View more

@jiltao Thank you for the material. You are very correct. Does the non-positive definite matrix impact negatively on the covariance parameters estimated by the model, or it is just a warning that something in not right? I relised that the more I include some random parameters the more i get problems with convergence as well. ... View more

I think I figured it out. Does it mean "Based on the off-diagonals, we estimate a covariance of 0.9730 between two measurements on the same Flask, regardless of time lapsed?" ... View more

Dear Rick Thank you for the reading by Gibbs and Kiernan (2020), "Simulating Data for Complex Linear Models." I see its full of wonderful sample simulation programs for linear models that I need time to grasp on. I appreciate the assistance. ... View more

Dear Rick   May you kindly try to give the code using dummy variables and parameters. Here is what I want to achieve:   Simulate a LMM in SAS as what I achieve in R when I follow the following steps after generating ANOVA F-tests results: set.seed(123) set out parameters of the model simulate the random errors in the model fit a model of simulated response store the variables and simulated data fit simulated model functionize the data simulating and fitting process (to test if the function works properly, it must produce similar results as in 6.) use the working function to simulate, say 10000 samples and note the simulation results. ... View more

Hi Ballardw May you kindly try to give the code using dummy variables and parameters. Here is what I want to achieve: Simulate a LMM in SAS as what I achieve in R when I follow the following steps after generating ANOVA F-tests results: 1. set.seed(123) 2. set out parameters of the model 3. simulate the random errors in the model 4. fit a model of simulated response 5. store the variables and simulated data 6. fit simulated model 7. functionize the data simulating and fitting process (to test if the function works properly, it must produce similar results as in 6.) 8. use the working function to simulate, say 10000 samples and note the simulation results. ... View more

Yes I got it. Thanks Steve.   ... View more

Is there a known procedure or formula that Proc mixed uses to calculate the F values? ... View more

@PaigeMiller  Thank you so much. I am following the discussion. I have already started to pick some useful facts from the discussion. I do appreciate your assistance and the team's deliberations. Thank you all ... View more