When and how to use set-exploratory structural equation modelling to test structural models: A tutorial using the R package lavaan.

Exploratory structural equation modelling (ESEM) is an alternative to the well-known method of confirmatory factor analysis (CFA). ESEM is mainly used to assess the quality of measurement models of common factors but can be efficiently extended to test structural models. However, ESEM may not be the best option in some model specifications, especially when structural models are involved, because the full flexibility of ESEM could result in technical difficulties in model estimation. Thus, set-ESEM was developed to accommodate the balance between full-ESEM and CFA. In the present paper, we show examples where set-ESEM should be used rather than full-ESEM. Rather than relying on a simulation study, we provide two applied examples using real data that are included in the OSF repository. Additionally, we provide the code needed to run set-ESEM in the free R package lavaan to make the paper practical. Set-ESEM structural models outperform their CFA-based counterparts in terms of goodness of fit and realistic factor correlation, and hence path coefficients in the two empirical examples. In several instances, effects that were non-significant (i.e., attenuated) in the CFA-based structural model become larger and significant in the set-ESEM structural model, suggesting that set-ESEM models may generate more accurate model parameters and, hence, lower Type II error rate.

School socioeconomic status context and social adjustment in children.

Social adjustment is critical to educational and occupational attainment. Yet little research has considered how the school's socioeconomic context is associated with social adjustment. In a longitudinal sample of Australian 4- to 8-year-olds (N = 9369; 51% boys) we tested the association between school average socioeconomic status and social skills (parent and teacher reported). Models controlled for age 4 social adjustment and additional covariates. Results showed that children from more advantaged schools are more likely to have better prosocial behavior and fewer peer and conduct problems. An interaction between family and school average socioeconomic status (SES) suggested that this association was mainly present for children from lower SES backgrounds. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Dimensional comparison theory.

Although social comparison (Festinger, 1954) and temporal comparison (Albert, 1977) theories are well established, dimensional comparison is a largely neglected yet influential process in self-evaluation. Dimensional comparison entails a single individual comparing his or her ability in a (target) domain with his or her ability in a standard domain (e.g., "How good am I in math compared with English?"). This article reviews empirical findings from introspective, path-analytic, and experimental studies on dimensional comparisons, categorized into 3 groups according to whether they address the "why," "with what," or "with what effect" question. As the corresponding research shows, dimensional comparisons are made in everyday life situations. They impact on domain-specific self-evaluations of abilities in both domains: Dimensional comparisons reduce self-concept in the worse off domain and increase self-concept in the better off domain. The motivational basis for dimensional comparisons, their integration with recent social cognitive approaches, and the interdependence of dimensional, temporal, and social comparisons are discussed.