Three structural equation (SEM) models (Kaplan, 2000) were used to examine 1) mother-child, 2) father-child, and 3) parent-child relationships, respectively. The latter model was run if data from either parent (or both) were available, and a parent exposure (e.g., depression) was coded present if it were observed in either parent (or both). SEM is an extension of regression models to address limitations of the latter when applied to relationships involving multiple variables over time (Kaplan, 2000). In a regression model, there exists a clear distinction between dependent and independent variables and the model relates the dependent to a set of independent variables. SEM is designed to handle the fact that a variable may serve as both an independent and a dependent variable in an analysis; SA at T1 is an example in our study (see Figure 1). In all models, parents were assumed to influence their children rather than vice-versa and, among children, the prospective influences of T1 variables on T2 were also examined. For each SEM model, we assessed model fit using the Chi-square and Root Mean Square Error
