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    In the nal model with this sample size [50]. Predictors were entered in chronological order, beginning with demographic characteristics. Next, DP status at ages 6 and 10 was entered into the equation. e DOXO-EMCH price following steps were peer substance use at age 10 and depression scores at age 10. Age 14 covariates in the next step included depression scores, authoritative parenting, and pubertal timing. In the last step, we tested for interaction effects between race and each predictor, because of evidence that there may be different risk factors for healthrisk behavior in White and African-American children (e.g., [51?3]).3. Results3.1. Bivariate Analyses. Descriptive statistics for the predictors of recent cannabis use are presented in Table 1, including the mean, standard deviation, and range of continuous variables. Percentages are provided for dichotomous variables. Intercorrelations among DP at ages 6 and 10, the other predictors, and cannabis use at age 14 are presented in Table 2. e behavioral dysregulation proles at ages 6 and 10 were not highly correlated ( = .24), and their coefficients in the regression analysis were not correlated highly enough to indicate multicollinearity ( = -.47). erefore, both variables were used in j.cub.2015.05.021 the multivariate analysis predicting adolescent recent cannabis use. Younger maternal age, older adolescent age, lower childhood family income, less authoritative parenting, and concurrent adolescent depressive symptoms were signicantly correlated with cannabis use at age 14. Neither race nor sex was associated with cannabis use in this cohort. 3.2. Multivariate Analysis. e results of the hierarchical logistic regression analysis predicting recent cannabis use in the 14-year-old offspring are presented in Table 3, which illustrates the nal step of the equation (2 = 49.5, < .001, Cox Snell 2 = .19). DP at age 6, older adolescent age, and higher depression scores were signicant predictors of recent cannabis use. ere was also a signicant interaction of race and pubertal timing (Figure 1). ere was a linear effect of pubertal timing on recent cannabis use for the White offspring, such that those who matured earlier wereISRN AddictionTABLE 1: Descriptive statistics: predictors of recent adolescent cannabis use. (1) Race of mother (White) 1940-0640-8-15 (2) Age of mother at time 1 (years) (3) Sex of adolescent (male) (4) Age of adolescent (5) Childhood family income1 (6) Dysregulation prole (DP) at age 6 (7) Dysregulation prole (DP) at age 10 (8) Peer cigarette use at age 10 (9) Depression scores at age 10 (10) Depression scores at age 14 (11) Authoritative parenting at age 14 (12) Pubertal timing Percentage 29 50 14.5 (0.6) 1569 (1154) 4 6 36 46.2 (9.3) 44.4 (8.5) 1.4 (0.9) 2.9 (0.9) 35?4 34?3 0? 1? Mean (standard deviation) 16.3 (1.2) Range 12?13?6 158?,1 Mean< .05, < .01. monthly family income from age 6 and age 10 assessments.TABLE 2: Intercorrelations among predictors and recent adolescent cannabis use. 1 (1) Race of mother (White) — (2) Age of mother at time 1 — (3) Sex of adolescent (male) — (4) Age of adolescent — (5) Childhood family income1 — (6) Dysregulation prole (DP) at age 6 — (7) Dysregulation prole (DP) at age 10 — (8) Peer cigarette use at age 10 — (9) Depression scores at age 10 — (10) Depression scores at age 14 — (11) Authoritative parenting at age 14 — (12) Pubertal timing — (13) Recent adolescent cannabis use — 2 .14 — — — — — — — — — — — — 3 -.05 -.02 — — — — — — — — — — -.