Table 2.

Multi-level model parameters from univariate models predicting self-rated health

Predictor	Model parameter	Estimate (SE)	p <
Null model (no predictors)	Variance components
	Intercept (τ2)	0.57 (0.08)	.0001
	Residual (ε2)	0.27 (0.01)	.0001
Age	Random effects
	Intercept	3.56 (0.24)	.0001
	Age (years > 60)	0.04 (0.03)	.15
	Fixed effects
	Quadratic age (years > 60 2)	−.002 (.0009)	.02
	Variance components
	Intercept (τ2)	0.58 (0.32)	.04
	Linear age slope	0.002 (0.001)	.06
	Intercept-slope covariance	−0.02 (0.02)	.34
	Residual (ε2)	0.26 (0.01)	.0001
	Change in -2LL from null model	7.3 (df = 4)	.12
Chronic disease	Random effects
	Intercept	3.62 (0.06)	.0001
	Fixed effects
	Within-person	−0.03 (0.04)	.44
	Between-person	−0.32 (0.06)	.0001
	Variance components
	Intercept (τ2)	0.47 (0.06)	.0001
	Residual (ε2)	0.27 (0.01)	.0001
	Change in -2LL from null model	17.0 (df = 2)	.0002
Negative affect	Fixed effects
	Intercept	3.64 (0.06)	.0001
	Within-person	−0.14 (0.03)	.0001
	Between-person	−0.37 (0.06)	.0001
	Variance components
	Intercept (τ2)	0.44 (0.06)	.0001
	Residual (ε2)	0.26 (0.01)	.0001
	Change in -2LL from null model	54.6 (df = 2)	.0001
Positive affect	Fixed effects
	Intercept	3.64 (0.06)	.0001
	Within-person	0.13 (0.03)	.0001
	Between-person	0.46 (0.06)	.0001
	Variance components
	Intercept (τ2)	0.40 (0.05)	.0001
	Residual (ε2)	0.26 (0.01)	.0001
	Change in -2LL from null model	66.7 (df = 2)	.0001