Table 4.

Estimated Within- and Between-Person Variances and Covariances of the Quadratic Growth Models (n = 606)

	Model 1		Model 2
Within-person variance	MLE(SE)	95% CI	MLE(SE)	95% CI
${\tau }_0$	2.31(0.03)	[2.25, 2.37]	2.11(0.06)	[1.98, 2.23]
maxyear, ${\tau }_1$	−0.08(0.02)	[−0.11, −0.05]	−0.045(0.016)	[−0.076, −0.013]
sex, ${\tau }_2$			0.15(0.065)	[0.023, 0.28]
DD, ${\tau }_3$			0.009(0.004)	[0.001, 0.017]
age, ${\tau }_4$			−0.001(0.003)	[−0.006, 0.004]
Between-person variances
Intercept, ${\beta }_{0i}$
${\alpha }_{00}$	4.47(0.06)	[4.35, 4.59]	4.5(0.14)	[4.2, 4.8]
maxyear, ${\alpha }_{01}$			−0.069(0.019)	[−0.11, −0.03]
sex, ${\alpha }_{02}$			−0.099(0.15)	[−0.40, 0.20]
DD, ${\alpha }_{03}$			0.02(0.01)	[−0.003, 0.035]
age, ${\alpha }_{04}$			−0.010.01	[−0.025, 0.003]
Linear slope, ${\beta }_{1i}$
${\alpha }_{10}$	−0.96(0.08)	[−1.13, −0.80]	−0.61(0.21)	[−1.02, −0.20]
maxyear, ${\alpha }_{11}$			−0.24(0.05)	[−0.34, −0.14]
sex, ${\alpha }_{12}$			−0.004(0.22)	[−0.45, 0.44]
DD, ${\alpha }_{13}$			−0.02(0.01)	[−0.05, 0.01]
age, ${\alpha }_{14}$			0.02(0.01)	[−0.004, 0.033]
Quadratic slope, ${\beta }_{2i}$
${\alpha }_{20}$	−4.7(0.16)	[−5.0, −4.4]	−3.2(0.35)	[−3.9, −2.6]
maxyear, ${\alpha }_{21}$			−0.61(0.10)	[−0.82, −0.41]
sex, ${\alpha }_{22}$			−0.50(0.35)	[−1.2, 0.18]
DD, ${\alpha }_{23}$			0.002(0.028)	[−0.05, 0.06]
age, ${\alpha }_{24}$			−0.041(0.018)	[−0.078, −0.006]
Calculated variance estimates
Within-person variance, ${\sigma }_{\epsilon i}^2$	10.1		8.2
Intercept variance, ${\varphi }_{b0}^2$	87		91
Linear slope variance, ${\varphi }_{b1}^2$	0.38		0.54
Quadratic slope variance, ${\varphi }_{b2}^2$	0.009		0.039
−lnL	5836.6		29775
AIC	5864.6		29851
BIC	5926.3		30019

Notes: AIC = Akaike information criterion; BIC = Bayesian information criterion; DD= diagnosis duration. The calculated variance estimates are obtained by exponentiating the intercept of the corresponding variance model. For example, ${\sigma }_{\epsilon i}^2=\mathrm{e}\mathrm{x}\mathrm{p}\left\{{\tau }_0\right\}$.