Do Institutional Characteristics Predict Markers of Adulthood?: A Close Replication of Fosse and Toyokawa (2016)

Abstract

Recent research reveals that some variability in personality differences can be explained by contextual factors such as location. Although little research has systematically evaluated how such variables predict individual differences in Emerging Adulthood, Fosse and Toyokawa (2016) revealed that characteristics of one’s university such as selectivity and liberal arts classification did predict respondents’ perceived importance and attainment of milestones associated with adulthood. As a close replication of Fosse and Toyokawa (2016), the present findings supported our preregistered hypotheses that liberal arts status predicted decreased perceived importance and lower attainment of some constructs of markers of adulthood but did not support predictions that selectivity would also predict such differences. Our findings provide further evidence of the institutional effects that emerge in multisample individual difference studies and extend those findings with a broader and more diverse sample than was considered previously.

Emerging Adulthood in Russia: Class and Educational Disparities

“…It has also been found that people with higher education are more prone to perceive EA as a time for identity exploration and experimentation (Ismyrlis, 2021; Mattys et al, 2021). Differences in education fields may also influence income opportunity as well as lifestyle, contributing to observed differences in the perception of EA between people with different types of degrees (Fosse & Toyokawa, 2016; Grahe et al, 2020).…”

Emerging Adulthood MoA/IDEA-8 Scale Characteristics From Multiple Institutions

“…When data have a hierarchical structure (e.g., individuals nested within institutions), residuals within statistical analyses may be dependent due to institution-level variability (Geldhof, Preacher, & Zyphur, 2014). This issue arises because participants within a particular institution may have similarities to one another leading to confounding by institution (a question addressed from a theoretical perspective by Grahe et al (2020).…”

Registered Reports With Developmental and Secondary Data: Some Brief Observations and Introduction to the Special Issue

“…Although there were certainly some bumps along the road, the project generally indicated to us that registered reports with secondary data are not only possible but that they are desirable. Some of the considerations that arose in the five papers in this collection included how to fit measurement models (Faas et al, 2020), conducting power analyses when using subgroups of unknown size (Chalk et al, 2020), analyses based on multilevel models when the amount of variance at each level is not known (Grahe et al, 2020), creating a reasonable set of alternative models to compare to the target model (Barlett et al, 2020), and creating indices from items without knowing how well they will hang together (Leighton et al, 2020). In all cases, authors needed not only to rely on the best possible prior information to make informed decisions but also to think through different contingency plans if that prior information did not comport with reality.…”