Application of Seemingly Unrelated Regression in Medical Data with Intermittently Observed Time-Dependent Covariates

Table 2

Simulation results (summary of estimated parameters, bias, and MSE) for complete observation of time-dependent covariates with different sample sizes (𝑛=20,60,120, and 240).

Parameter; (true value)	Method	Sample size = 20			Sample size = 60			Sample size = 120			Sample size = 240
		^↼𝛽	Bias	MSE	^↼𝛽	Bias	MSE	^↼𝛽	Bias	MSE	^↼𝛽	Bias	MSE
𝛽2	REML	−1.01	.12	7.24	−1.14	−.009	1.89	−1.12	.01	.828	−1.14	−.006	.42
(−1.13)	ITSUR	−1.003	.13	7.37	−1.14	−.009	1.89	−1.12	.01	.829	−1.14	−.006	.42
𝛽3	REML	.18	−.04	7.33	.14	−.09	1.90	.21	−.02	.864	.25	.02	.42
(.23)	ITSUR	.18	−.05	7.40	.14	−.09	1.89	.21	−.02	.863	.25	.02	.42
𝛽4	REML	.03	.04	3.32	−.01	−.004	.82	−.02	−.009	.39	−.02	−.009	.18
(−.01)	ITSUR	.02	.03	3.39	−.009	.0004	.83	−.02	−.008	.39	−.02	−.009	.18
𝛽5	REML	−1.11	.006	2.25	−1.12	−.003	.57	−1.08	.04	.26	−1.10	.02	.13
(−1.12)	ITSUR	−1.11	.01	2.36	−1.12	−.005	.58	−1.09	.03	.27	−1.10	.02	.13

*Note: REML represents the estimated parameters from MRM, and ITSUR represents that of the SUR model.