Table 3.
Unstandardized path and moderator estimates in the best-fitting models for Aggressive (AGG) and Rule-Breaking (RB) Antisocial Behavior.
| Measure | PATHS | LINEAR | QUADRATIC | ||||||
|---|---|---|---|---|---|---|---|---|---|
| a | c | e | A1 | C1 | E1 | A2 | C2 | E2 | |
| AGG | .699 (.463, .896) | .468 (−.696, .696) | .537 (.478, .609) | ---- | ---- | ---- | ---- | ---- | ---- |
| RB | .705 (.412, .963) | .417 (−.668, .668) | .471 (.420, .534) | −.034 (−.268, .170) | --- | ---- | .021 (−.022, .068) | ---- | ---- |
Note. Paths and moderators are presented; their 95% confidence intervals are presented below them in brackets. A, C, and E (both upper and lower case) represent genetic, shared, and non-shared environmental parameters, respectively. In the left portion of the table, the path estimates (i.e., a, c, and e) are presented. Because we subtracted 10 from each age prior to data analysis (setting the floor to 0), these path estimates function as intercepts. Accordingly, the genetic and environmental variance components at age 10 can be obtained simply by squaring these path estimates. At each subsequent age, significant linear (i.e., A1, C1, E1) and non-linear (i.e., A2, C2, E2) moderators are added to these genetic and environmental paths using the following equation: Unstandardized VarianceTotal = (a + A1(age) + A2(age2))2 + (c + C1(age) + C2(age2))2 + (e + E1(age) + E2(age2))2. The variance component estimates calculated in this way are then presented in Figure 1, separately by sub-type. Bold font indicates that estimate is significant at p<.05.