The five primary conditional http://www.selleckchem.com/products/Sorafenib-Tosylate.html models built on each other. The first included the variables and their interactions characterizing the family, peer, and school contexts (microsystems). The second added the set of variables and their interactions characterizing the neighborhood (exosystem). The final three models added between-context interactions involving family and peers, family and school, and peers and school (mesosystems). In addition to the hypothesized interactions between smoking modeling and social bond variables, for all three mesosystem models, we also included the between-context interaction between the two indicators of smoking modeling because of the possible risk associated with accumulated exposure (Bricker et al., 2006).

For each conditional model, we report the coefficients for the fixed effects of the variables and, if included in the model, their interactions. We also report the F statistic for testing the significance of the set of variables and interactions added to each successive model. Because the social context variables were time varying, a significant effect means that the relationship between the social context variable (or interaction between context variables) and adolescent smoking was significant on average over the ages examined. For ease of interpretation, we refer throughout to each contextual attribute by the construct name (e.g., peer strain) rather than the specific indicator (e.g., intransitive friendships triads). All analyses were conducted using SAS v. 9.1.3., using PROC MIXED and PROC MIANALYZE (SAS, 2002�C2003).

Results Unconditional model The best-fitting unconditional model was a linear growth model with random individual and neighborhood intercepts and slopes. The model demonstrated significant individual (Z-score = 5.54, p < .001) and between-neighborhood (Z-score = 3.14, p < .01) variation around the mean intercept centered at age 12 years and significant individual (Z-score = 5.08, p < .001) and between-neighborhood (Z-score = 3.48, p < .001) variation around the slope. The model also showed significant fixed effects such that the mean intercept for smoking was significantly different from zero (B = ?.02, SE = 0.01, p < .05), and there was significant growth in smoking through age 17 years (B = .08, SE = 0.004, p < .001). The linear model was a better fit than a quadratic model; the spline model did not converge.

Preliminary conditional models Demographics model In the preliminary model including only the demographic variables, both age (B = .07, SE = 0.01, p < .001) and high school enrollment (B = .03, SE = 0.01, p < .05) significantly predicted Carfilzomib increased smoking. Because the remaining demographics were time invariant, their relationships with both the intercept and slope of the growth curves were modeled.