Multilevel Twin Models: Geographical Region as a Third Level Variable.

The classical twin model can be reparametrized as an equivalent multilevel model. The multilevel parameterization has underexplored advantages, such as the possibility to include higher-level clustering variables in which lower levels are nested. When this higher-level clustering is not modeled, its variance is captured by the common environmental variance component. In this paper we illustrate the application of a 3-level multilevel model to twin data by analyzing the regional clustering of 7-year-old children's height in the Netherlands. Our findings show that 1.8%, of the phenotypic variance in children's height is attributable to regional clustering, which is 7% of the variance explained by between-family or common environmental components. Since regional clustering may represent ancestry, we also investigate the effect of region after correcting for genetic principal components, in a subsample of participants with genome-wide SNP data. After correction, region no longer explained variation in height. Our results suggest that the phenotypic variance explained by region might represent ancestry effects on height.

Testing sampling bias in estimates of adolescent social competence and behavioral control.

In 5 of the 6 large Dutch developmental cohorts investigated here, lower SES adolescents are underrepresented and higher SES adolescents overrepresented. With former studies clearly revealing differences between SES strata in adolescent social competence and behavioral control, this misrepresentation may contribute to an overestimation of normative adolescent competence. Using a raking procedure, we used national census statistics to weigh the cohorts to be more representative of the Dutch population. Contrary to our expectations, in all cohorts, little to no differences between SES strata were found in the two outcomes. Accordingly, no differences between weighted and unweighted mean scores were observed across all cohorts. Furthermore, no clear change in correlations between social competence and behavioral control was found. These findings are most probably explained by the fact that measures of SES in the samples were quite limited, and the low SES participants in the cohorts could not be considered as representative of the low SES groups in the general population. Developmental outcomes associated with SES may be affected by a raking procedure in other cohorts that have a sufficient number and sufficient variation of low SES adolescents.

Robust longitudinal multi-cohort results: The development of self-control during adolescence.

Longitudinal data from multiple cohorts may be analyzed by Bayesian research synthesis. Here, we illustrate this approach by investigating the development of self-control between age 13 and 19 and the role of sex therein in a multi-cohort, longitudinal design. Three Dutch cohorts supplied data: the Netherlands Twin Register (NTR; N = 21,079), Research on Adolescent Development and Relationships-Young (RADAR-Y; N = 497), and Tracking Adolescents' Individual Lives Survey (TRAILS; N = 2229). Self-control was assessed by one measure in NTR and RADAR-Y, and three measures in TRAILS. In each cohort, we evaluated evidence for competing informative hypotheses regarding the development of self-control. Subsequently, we aggregated this evidence over cohorts and measures to arrive at a robust conclusion that was supported by all cohorts and measures. We found robust evidence for the hypothesis that on average self-control increases during adolescence (i.e., maturation) and that individuals with lower initial self-control often experience a steeper increase in self-control (i.e., a pattern of recovery). From self-report, boys have higher initial self-control levels at age 13 than girls, whereas parents report higher self-control for girls.