Table 5. LSAC data analysis for analysis model (1) i.e., longitudinal data scenario.

Regression Parameters	Available data	JM-MVN	JM-MLMM	JM-FJ	JM-FJ-het	JM-SMC	JM-SMC-het	FCS-standard	FCS-LMM	FCS-LMM-het
cbmi, $\widehat{{\beta }_1}$	-0.043	-0.043	-0.042	-0.047	-0.042	-0.042	-0.045	-0.044	-0.043	-0.047
$\text{se}\left(\widehat{{\beta }_1}\right)$	0.008	0.008	0.008	0.007	0.008	0.008	0.008	0.008	0.007	0.010
95% CI	(-0.058, -0.029)	(-0.058, -0.027)	(-0.058, -0.026)	(-0.061, -0.033)	(-0.058, -0.029)	(-0.058, -0.026)	(-0.061, -0.029)	(-0.059, -0.029)	(-0.057, -0.029)	(-0.067, -0.027)
cage, $\widehat{{\beta }_2},$ years	-0.020	-0.022	-0.021	-0.019	-0.020	-0.021	-0.021	-0.022	-0.021	-0.018
$\text{se}\left(\widehat{{\beta }_2}\right)$	0.002	0.002	0.002	0.002	0.002	0.002	0.002	0.002	0.002	0.002
95% CI	(-0.024, -0.016)	(-0.026, -0.018)	(-0.025, -0.017)	(-0.023, -0.015)	(-0.024, -0.016)	(-0.025, -0.017)	(-0.025, -0.017)	(-0.026, -0.018)	(-0.025, -0.017)	(-0.022, -0.014)
Variance components
Ĝ 00	0.431	0.518	0.473	0.419	0.432	0.443	0.450	0.520	0.472	0.441
Ĝ 01	-0.016	-0.021	-0.020	-0.007	-0.016	-0.016	-0.017	-0.022	-0.020	-0.016
Ĝ 11	0.004	0.004	0.005	0.002	0.004	0.004	0.004	0.005	0.005	0.004
${\hat{\sigma }}_{\epsilon }^2$	0.434	0.436	0.434	0.460	0.434	0.438	0.437	0.436	0.434	0.465