Variable ρ Parameter Bias MCMC efficiency MCMC bias GS a0=0.0 Efficiency GSa0=0.0 bias GSa0=â0.0 Efficiency GS a0=â0.0 Bias GS a0=0.50 Efficiency GS a0=0.50 Bias GS a0=0.95 efficiency GS a0=0.95  Intercept 0.25 β0  0.0018 2.1771 0.0015 0.9713 0.0011 0.9548 0.0003  0.9263 0.0007  0.7511  Time 0.25 β1 0.0015 4.2531 0.0019 0.9910 0.0015 0.9625 0.0013 0.9226 0.0004  0.8162 Age 0.25 β2 0.0052 3.6621 0.0008 1.0007 0.0013 0.9162 0.0003 0.8541 0.0000  0.7381 Center 0.25 β3 0.0031 4.1954 0.0037 0.9568 0.0025 0.9417 0.0011 0.9771 0.0007 0.8572 Treat 0.25 β4 0.0028 2.3718 0.0021 0.9936 0.0017 0.8611 0.0009  0.8819 0.0003  0.8338 Visit  Group 0.25 β5 -0.0033 3.6931 0.0013 1.0125 0.0009 0.9352 0.0008  0.8926 0.0011  0.8811 Intercept 0.50 β0 0.0082 1.6416 0.0005 1.0173 0.0003 0.9812 0.0001  0.8115 0.0004  0.7739  Time 0.50 β1 0.0071 1.4358 0.0012 0.9972 0.0012  0.8714 0.0009  0.8909 0.0000  0.8162 Age 0.50 β2 -0.0018 1.8871 0.0007 0.9615 0.0012 0.8759 0.0000  0.7791 0.0005 0.7150 Center 0.50 β3 -0.0021 2.2701 0.0009 0.9926 0.0004 0.9157 0.0008  0.8183 0.0001  0.7962 Treat 0.50 β4  0.0033 1.3277 0.0013 0.9732 0.0010  0.9456 0.0010 0.8317 0.0006  0.8110 Visit  Group 0.50 β5 -0.0041 2.7140 0.0011 1.1704 0.0011  0.9627 0.0007  0.9122 0.0003  0.7155 Intercept 0.75 β0 0.0015 3.1147 0.0009 1.0063 0.0011 0.8931 0.0004 0.8102 0.0009  0.7107  Time 0.75 β1 0.0027 3.8031 0.0016  1.126 0.0010 0.8825 0.0010  0.8339 0.0006  0.7263 Age 0.75 β2 0.0017 2.5731 0.0021 1.0286 0.0023  0.9345 0.0006  0.8513 0.0015  0.6610 Center 0.75 β3 -0.0019 5.1703 0.0024 1.1351 0.0019 0.9132 0.0017  0.7959 0.0008  0.7289 Treat 0.75 β4 -0.0014 2.3319 0.0009 0.9938 0.0012  0.8627 0.0005  0.8208 0.0002 0.7338 Visit  Group 0.75 β5 0.0026 3.4265 0.0014 1.0346 0.0016 0.8236 0.0009 0.7107 0.0005  0.6619

Table 3: Estimated bias and relative efficiency by using Gibbs sampler GS and Bayesian MCMC for the real data.