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ertising needs to be adjusted to account for the context of social networking sites. Copyright © 2020 Hendriks, Wilmsen, van Dalen and Gebhardt.[This corrects the article DOI 10.3389/fpsyg.2019.01018.]. Copyright © 2020 Brügger and Höchli.In mediation analysis, conditions necessary for commonly recommended tests, including the confidence interval (CI)-based tests, to produce an accurate Type I error, do not generally hold for finite sample sizes and non-normally distributed model residuals. This is typically the case because of the complexity of testing a null hypothesis about indirect effects. To remedy these issues, we propose two extensions of the recently developed asymptotic Model-based Constrained Optimization (MBCO) likelihood ratio test (LRT), a promising new model comparison method for testing a general function of indirect effects. selleck inhibitor The proposed tests, semi-parametric and parametric bootstrap MBCO LRT are shown to yield a more accurate Type I error rate in smaller sample sizes and under various degrees of non-normality of the model residuals compared to the asymptotic MBCO LRT and the CI-based methods. We provide R script in the Supplemental Materials to perform all three MBCO LRTs. Copyright © 2020 Tofighi.Graphs are useful tools to communicate meaningful patterns in data, but their efficacy varies considerably based on the figure's construction and presentation medium. Specifically, a digital format figure can be dynamic, allowing the reader to manipulate it and little is known about the efficacy of dynamic figures. This present study compared how effectively static and dynamic graphical formats convey relationship information, and in particular variable interactions. Undergraduates (N = 128, 56% female, M age = 18.9) were given a brief tutorial on main effects and interactions in data and then answered 48 multiple-choice questions about specific graphs. Each question involved one of four figure types and one of four relationship types (main effect only, interaction only, main effect and interaction, or no relationship), with relationship types and graphical formats fully crossed. Multilevel logistic regression analysis revealed that participants were fairly accurate at detecting main effects and null relationships but struggled with interaction effects. Additionally, the static 3D graph lowered performance for detecting main effects, although this negative effect disappeared when participants were allowed to rotate the 3D graph. These results suggest that dynamic figures in digital publications are a potential tool to effectively communicate data, but they are not a panacea. Undergraduates continued to struggle with more complicated relationships (e.g., interactions) regardless of graph type. Future studies will need to examine more experienced populations and additional dynamic graph formats, especially ones tailored for demonstrating interactions (e.g., profiler plots). Copyright © 2020 Hood, Graber and Brase.The aim of this study was to identify the influences of psychological capital (PC) on students' entrepreneurial intention (EI) in China's universities. The mediating effects of Entrepreneurial Capitals were also examined. Based on the analysis of the traditional capital and PC, the paper proposes that traditional capital is the direct factor to drive the behavior of entrepreneurship, while psychological factors do not directly affect EI, but improve EI by influencing traditional capital. A total of 1914 responses from universities in southeast China were analyzed using the structural equation modeling (SEM) approach to test study hypotheses. Results show that PC has a significant indirect impact on students' EI only through traditional financial, human, and social capital (SC). These results support the mediating role of the traditional entrepreneurial capitals in explaining the relationship between PC and EI. Additionally, the impact of SC on EI is higher than that of financial and human capital (HC). Finally, research limitations and implications are discussed and future research directions are suggested. Copyright © 2020 Zhao, Wei, Chen and Yien.The purpose of this study was to identify trends in the representation of female authorship regarding the topic of the status of women in science, technology, engineering, and mathematics (STEM) in higher education in the United States from 2007 to 2018 in prominent interdisciplinary journals. We conducted a comprehensive search for articles and collected the genders of the first and senior authors from 647 citations. We assessed the number of male versus female authors, the percentages of female first authors and senior authors, and the percentage of female corresponding authors for each year. Additionally, we also analyzed the citations to determine the journals and publishers who produced the most literature in this area. Women constituted 59% overall authorship and 34% first authorship. The top publishers in this area include Sage Publications, Springer/Nature, and Elsevier. Women constituted 60% of the first authors in STEM literature on the status of women and 38% of senior authors. Although there was growth over time in first authorship in STEM literature written by women, they continue to remain a minority in senior authorship. We suggest it is women that are leading this discussion, highlighting the additional lift that women in STEM in higher education must make; researching and publishing on their own experiences as part of their self-advocacy. Copyright © 2020 Blackburn and Heppler.The study investigates effects of the implementation of a law authorizing educational leave in Germany on individual participation in adult learning and education (ALE). In 2015, the federal state of Baden-Württemberg introduced the so-called Bildungszeitgesetz, legitimating an exemption for eligible employees of up to 5 days per year with continued payment of salary. Explaining participation in ALE is a central subject of educational research at national and international level. Current theoretical assumptions of rational choice and empirical findings of educational and socio-statistical research suggest that within the general population, individuals' availability of time affects the decision to participate and therefore lastly determines participation in ALE. However, current academia mainly discusses time as either a prerequisite for learning activities or as an observable outcome of participation and not as an explanatory factor. Furthermore, since recent studies remain on a descriptive level regarding influences of time on participation in ALE, no causal effects of the availability of time on participation are estimated.