Implementation of a multiverse approach in developmental research: The longitudinal relation between self-esteem and peer victimization

Research in social sciences has been questioned in the past decade due to the failure to replicate earlier work. To improve the trust in results, best practices that reduce data-analytical flexibility have been proposed, such as preregistration. Another more recent such development regards the multiverse approach. The current study sought to demonstrate the benefits of applying the multiverse approach within developmental psychology. Using the relation between self-esteem and peer victimization in adolescence as an example, we examined how both the concurrent as well as longitudinal association was impacted by data-analytical decisions, such as the operationalization of variables, treatment of outliers, inclusion of covariates, and paths estimated in the model. Indeed, through the multiverse approach, we showed that and how these decisions matter for the model fit and estimates of the associations. We were thus able to illustrate that the multiverse approach increases transparency, makes it possible to examine the robustness of effects and can help advance theory building. Limitations of this approach as well as recommendations for other researchers are discussed.