Table 4.

Analysis of the hypertension data under three scenarios of the within-subject measurement error covariance: (a) IID with same σ² for SBP and BMI: Σ_i = σ²I for ${\widehat{\sigma }}^2=9.2552$; (b) Independent with different σ² for SBP and BMI: Σ_i = block (σ^{2 SBP}I, σ^{2 BMI}I) for ${\widehat{\sigma }}^{2\mathit{SBP}}=61.8480$ and ${\widehat{\sigma }}^{2\mathit{BMI}}=0.7813$; (c) Following a structure preferred by information criteria: Σ_i = block (${\Omega }_i^{\mathit{SBP}}$, ${\Omega }_i^{\mathit{BMI}}$) where ${\Omega }_i^{\mathit{SBP}}$ has Markov structure with ${\widehat{\rho }}^{\mathit{SBP}}=0.4220$ and ${\widehat{\sigma }}^{2\mathit{SBP}}=68.7562$, and ${\Omega }_i^{\mathit{BMI}}$ has Markov structure with ${\widehat{\rho }}^{\mathit{BMI}}=0.6278$ and ${\widehat{\sigma }}^{2\mathit{BMI}}=1.0212$. Estimated standard errors are in parentheses below each estimate.

	Intercept		SBPyoung adulthood		BMIintercept		BMIslope
	Estimate	p-value	Estimate	p-value	Estimate	p-value	Estimate	p-value
(a) Σi = σ2I
SS	−28.30 (7.62)	0.00	0.28 (0.07)	0.00	−0.35 (0.26)	0.17	49.17 (11.98)	0.00
CS	−103.20 (15.51)	0.00	0.63 (0.15)	0.00	1.73 (0.23)	0.00	82.78 (11.23)	0.00
(b) Σi = block (σ2 SBPI, σ2 BMII)
GSS	−18.03 (2.86)	0.00	0.12 (0.02)	0.00	0.08 (0.05)	0.07	6.81 (1.76)	0.00
GCS	−18.36 (2.94)	0.00	0.13 (0.03)	0.00	0.08 (0.05)	0.09	6.80 (1.77)	0.00
(c) Σi = block (${\Omega }_i^{\text{SBP}}$,${\Omega }_i^{\text{BMI}}$) where both ${\Omega }_i^{\text{SBP}}$ and ${\Omega }_i^{\text{BMI}}$ have preferred Markov structures
GSS	−20.84 (3.72)	0.00	0.16 (0.03)	0.00	0.04 (0.06)	0.46	6.94 (1.99)	0.00
GCS	−21.96 (4.25)	0.00	0.17 (0.04)	0.00	0.03 (0.06)	0.61	7.03 (2.11)	0.00