Effect Size Strengths in Subjective Well-Being Research

Abstract

Subjective well-being (SWB) research is characterized by many large samples, which often results in virtually all variables being significantly related to well-being, even if the associations are small. In this article we explore the strengths of associations between various predictors and SWB outcomes. In addition to standard effect-size statistics, we also examined the range of the SWB scale covered in the distribution of the predictor, allowing us to estimate the strength of influence of each variable, independent of variability in the sample. We analyzed just a few variables to illustrate what our approach reveals. Our analyses included a representative sample of both the world and the United States, and our data included three types of SWB (life satisfaction (LS), positive affect (PA), and negative affect (NA)). The largest effect sizes emerged for societal characteristics, such as between-nations differences, as well as personal characteristics, such as perceived social support. Small or very small effect sizes were consistently found for demographic characteristics, such as sex, age, and marital status. Other effect sizes varied by the type of SWB being considered. For example, income resulted in a large effect size for LS, but small to medium effect sizes for PA and NA. We suggest that when scholars report and interpret the associations of predictor variables with SWB, they consider the strengths of their significant associations.