We used Mplus statistical software (Muthén & Muthén, 1998–2010) to fit a longitudinal correlated factors model (Figure 2, described above) for each outcome from each study individually using the summary data option that allowed us to estimate the parameters based on the extracted group correlation matrices. To obtain accurate standard errors, we input the sample size that each group contained in terms of complete sibling pairs that were present at least at two time points. In practice, this approach proved difficult as the reporting of sample size varied across study. The current analysis uses the sibling pair as the unit of analysis, but sample size was often reported in terms of individuals. Additionally, some studies continued to recruit new participants as the study progressed rendering it difficult to interpret how many twin pairs had complete longitudinal data. Because of this uncertainty, we chose to take a conservative approach to estimating sample size. When sample size was only reported in terms of individuals, we took half the number to represent the number of pairs. When available, we used the number of
