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How to simulate correlated data with random effects?

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How to simulate correlated data with random effects?

I'm trying to create a simulation of drug concentration based on the dose of a drug given. I have some preliminary data and I used a random effects model to analyze the relationship between log(dose), predicting log(drug concentration), modelling subject as a random effect.

The results of that analysis are below (output from R mixed model)o. I want to take these results and simulate similar data in SAS, so I can look at the effect of changing doses on the resulting concentration of drug in the body. I know that when I simulate the data, I need to ensure the random slope is correlated with the random intercept, but I'm unsure exactly how to do that. Any example code would be appreciated.

Random effects:

Formula: ~LDOS | RANDID Structure: General positive-definite, Log-Cholesky parametrization StdDev Corr (Intercept) 0.15915378 (Intr) LDOS 0.01783609 0.735 Residual 0.05790635 

Fixed effects:

LCMX ~ LDOS Value Std.Error DF t-value p-value (Intercept) 3.340712 0.04319325 16 77.34339 0 LDOS 1.000386 0.01034409 11 96.71090 0 

Correlation:

(Intr) LDOS -0.047
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