Table 2.
Model 1 Unconditional Model |
Model 2 Basic Growth Curve |
Model 3 Dichotomous Age10 Term |
||||
---|---|---|---|---|---|---|
Estimate | SE | Estimate | SE | |||
Fixed Effects | ||||||
Intercept | 1.814*** | 0.052 | 1.946** | 0.304 | 1.781*** | 0.099 |
Race (1=Caucasian) | 0.071 | 0.107 | 0.070 | 0.108 | ||
Age | -0.085 | 0.090 | 0.349*** | 0.073 | ||
Age2 | 0.010 | 0.006 | ||||
Sex (1 = Male) | -0.920* | 0.422 | -0.144 | 0.103 | ||
Age by Sex | 0.265* | 0.127 | -0.330** | 0.102 | ||
Age2 by Sex | -0.021* | 0.008 | ||||
Random Effects | ||||||
Intercept | 0.848** | 0.074 | 1.050** | 0.164 | 0.825*** | 0.074 |
Age | 0.011** | 0.003 | 0.213** | 0.079 | ||
Residual | 0.539** | 0.025 | 0.440** | 0.025 | 0.474*** | 0.027 |
ICC | .61 | |||||
Model Fit | ||||||
REML Deviance | 3608.6 | 3579.6 | 3559.3 | |||
AIC | 3612.6 | 3587.6 | 3567.3 | |||
BIC (smaller is better) | 3620.5 | 3603.4 | 3583.1 |
p < .001
p < .01
p < .05,
p < .10
Acronyms: REML = Restricted Maximum Likelihood; AIC = Akaike's information criterion; BIC = Bayesian information criterion; ICC = Intraclass correlation.
ICC was calculated as follows: Intercept random effect/(Intercept random effect + Residual Random Effect)