also influence the home environment, and it is predominantly within this context that parents observe the child’s behavior. Multiple assessments of aggression by teachers, fathers, and mothers, by different instruments and at different ages, provide information that may be unique to a specific context and therefore may capture context-dependent expression of AGG. These considerations support an approach in which all AGG data are simultaneously analyzed, while retaining the ability to analyze the data by rater. Our analyses include repeated observations on the same subject, which requires appropriate modeling of the clustered data, since the covariance between test statistics becomes a function of a true shared genetic signal and the phenotypic correlation among outcomes [29]. We developed an approach that allowed inclusion of all measures for a child—e.g., from multiple raters at multiple ages—and resolved issues of sample overlap at the level of the meta-analysis. By doing so we make full use of all data and maximize statistical power for gene discovery. At the same time, by aggregating data at the level of the meta-analysis, we retain the flexibility to estimate rgs between AGG at different ages, by different raters and instruments, and test how AGG assessed by multiple raters differ
