Table 3 Estimated fixed effects and random effects as well as error model parameters for the best fitting nonlinear model. Both fixed and random effects are estimated using the SAEM algorithm.
Parameter | Estimate | Std. Error |
|---|---|---|
Fixed Effects Estimates | ||
\(r_{10}\) | 0.089 | 0.015 |
\(\beta _{11}\) | −3.670 | 1.100 |
\(\beta _{12}\) | −0.905 | 0.236 |
\(r_{20}\) | 0.028 | 0.041 |
\(\beta _{21}\) | −5.860 | 8.070 |
\(\beta _{22}\) | 1.760 | 1.490 |
\(r_{30}\) | 0.002 | 0.001 |
\(\beta _{31}\) | −1.440 | 1.390 |
\(\beta _{32}\) | −0.862 | 1.110 |
\(r_{40}\) | 0.010 | 0.002 |
\(\beta _{41}\) | −2.100 | 0.431 |
\(A_{00}\) | 0.00003 | 0.002 |
\(\beta _{01}\) | 16.500 | 72.500 |
Random Effects Estimates | ||
\(\omega _{1}\) | 0.345 | 0.089 |
\(\omega _{2}\) | 0.611 | 0.215 |
\(\omega _{3}\) | 0.323 | 4.460 |
\(\omega _{4}\) | 0.675 | 0.207 |
\(\omega _{0}\) | 3.630 | 1.320 |
Correlation Estimates | ||
\(\rho _{r_2, r_1}\) | −0.260 | 0.473 |
\(\rho _{r_3, r_1}\) | 0.662 | 10.500 |
\(\rho _{r_4, r_1}\) | −0.145 | 0.559 |
\(\rho _{r_3, r_2}\) | 0.151 | 4.930 |
\(\rho _{r_4, r_2}\) | 0.841 | 0.258 |
\(\rho _{r_4, r_3}\) | 0.346 | 1.710 |
Model Error Estimates | ||
a | 0.348 | 0.0266 |
b | 0.206 | 0.0263 |
