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

Abstract

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.

Bayesian evidence synthesis in case of multi-cohort datasets: An illustration by multi-informant differences in self-control

“…A major advantage of Bayesian evidence synthesis is that it provides the degree of support for a set of competing hypotheses both at the within-study level and across studies. This highlights inconsistencies between cohorts and allows one to address the robustness of the overall findings (see also, Zondervan-Zwijnenburg et al, 2020 ). Moreover, the Bayesian approach answers the focal question of which hypothesis is most plausible given the data.…”

“…We illustrated that this method can be used if the information in cohorts is limited to partial hypotheses, while the synthesized information for all cohorts did address the (complete) hypotheses of interest. In previous studies that used Bayesian research synthesis to combine results over cohorts, all aspects of the hypotheses were tested in all cohorts, even though the measurement instrument might differ ( Veldkamp et al, 2020 ; Zondervan-Zwijnenburg et al, 2019 , 2020 ). Statistically, Bayesian research synthesis is suitable to assess and combine the support for partial hypothesis.…”

“…Bayesian evidence synthesis can be used to combine results by aggregating their evidence for competing hypotheses (Kuiper, Buskens, Raub & Hoijtink, 2012; Zondervan-Zwijnenburg et al, 2019 ). In this manner, studies covering various contexts and measurement instruments can be combined ( Zondervan-Zwijnenburg et al, 2019 , 2020 ). This approach is also suitable to combine the results of structural equation modelling ( Zondervan-Zwijnenburg et al, 2019 , 2020 ).…”

“…In this manner, studies covering various contexts and measurement instruments can be combined ( Zondervan-Zwijnenburg et al, 2019 , 2020 ). This approach is also suitable to combine the results of structural equation modelling ( Zondervan-Zwijnenburg et al, 2019 , 2020 ). The main assumptions of Bayesian evidence synthesis are that all sources of information provided by individual studies contribute to the overarching research question, and that all samples are representative of the population of interest ( Veldkamp et al, 2020 ).…”

The building blocks of social competence: Contributions of the Consortium of Individual Development

“…Whereas the SDQ measures key underlying skills such as prosocial behavior and friendship behaviors, the CBCL focuses on atypical (problematic) behavior in social interactions. Because all our cohorts employ at least one of these two questionnaires, CID is eventually able to collapse indices of social competence across cohorts that share the same indices (see also Zondervan-Zwijnenburg et al, 2020 for a similar approach to combining multiple cohort data on questionnaires related to behavioral control).…”