Multicollinearity is a potential problem in all regression analyses. However, the examination of multicollinearity is rarely reported in primary studies. In this article we discuss and show several post hoc methods for assessing multicollinearity. One such multicollinearity diagnostic is the variance inflation factor. We outline the post hoc variance inflation factor method, which computes the variance inflation factor from the standardized regression coefficient and semi-partial correlation, both of which can be calculated from commonly reported regression results. Three examples of computing multicollinearity diagnostics using data from published studies are shown. We conclude with a discussion and practical implications.

In this article we focus on three partial effect sizes for the correlation (r) family of effects: the standardized slope (b), the partial correlation (rp), and the semi-partial correlation (rsp). These partial effect sizes are useful for meta-analyses in two common situations: when primary studies reporting regression models do not report bivariate correlations, and when it is of specific interest to partial out the effects of other variables. We clarify the use of these three indices in the context of meta-analysis and describe how the indices can be estimated and analyzed. We provide examples of syntheses of these partial effect sizes using a published social work meta-analysis. Finally, we share practical recommendations for meta-analysts wanting to use such indices.

While existing evidence strongly suggests that immigrant students underperform relative to their native counterparts on measures of mathematics, science, and reading, country-level analyses assessing the homogeneity of the immigrant achievement gap across different factors have not been systematically conducted. Beyond finding a statistically significant average achievement gap, existing findings show considerable variation. The goal of this quantitative synthesis was to analyze effect sizes which compared immigrants to natives on international mathematics, reading, and science examinations.

A meta-analytic review of studies that experimentally elicited awe and compared the emotion to other conditions (84; 487 effects; 17,801 participants) examined the degree to which experimentally elicited awe (1) affects outcomes relative to other positive emotions (2) affects experience, judgment, behaviour, and physiology, and (3) differs in its effects if the awe state was elicited through positive or threatening contexts. The efficacy of methods that have been used to experimentally elicit awe and the possibility of assessing changes in the state of the self with experimental awe elicitations were also examined. Meta-analyses with robust variance estimation revealed that awe affected outcomes compared to other positive emotions and control conditions; affected experience, judgment, and behaviour; and had similar effects if elicited through positive or threatening contexts. The ability to compare awe to negative emotion states and its effects on physiology was limited by a small number of available effects. Images, videos, autobiographical recall, and naturalistic exposure were effective in eliciting awe. Exploratory analyses suggested that some processes involved in changes in the self can be related to experimental awe elicitations. These findings suggest awe is a discrete emotion and identifies areas for future investigation.