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Marsh and Scalas (2018) proposed a taxonomic structural equation modelling approach to test the individually importance weighted‐average models (IWAMs) in their article published in Structural Equation Modeling: A Multidisciplinary Journal 25: 137–158. As Marsh and Scalas (2018) pointed out, IWAMs could be found in many research areas, including self‐concept, job satisfaction and quality of life (QOL) research. Based on the findings of their proposed approach, Marsh and Scalas (2018) argued that importance weights do not make a difference. The purpose of this paper is to assess the applicability of the approach developed by Marsh and Scalas (2018) and their conclusion that importance weights do not make a difference in the area of QOL, specifically subjective well‐being, research. In the research area of QOL, IWAMs have been discussed often under the topic of domain importance weighting. Findings from an analysis of the Panel Study of Income Dynamics' Wellbeing and Daily Life Supplement data show that different domain importance weighting methods, based on different underlying (within‐domain vs between/across‐domain) perspectives, produced different results leading to different conclusions. Although the approach for testing IWAMs developed by Marsh and Scalas (2018) offered several methodological advances and strengths, its applicability to the evaluation of domain importance weighting in QOL studies is limited by its underlying (within‐domain) perspective, its assumption that domain importance can be accurately and precisely measured, and the possibility of the small effect size of domain importance. Marsh and Scalas' (2018) findings that importance weights do not make a difference should be interpreted with caution. [ABSTRACT FROM AUTHOR]

Using Australian data, this paper proposes a three‐tiered model of overall life satisfaction as a function of socio‐economic characteristics and satisfaction with areas of life and personality traits. Mediation analysis through structural equation modelling is employed using data from the 17th wave of the Household, Income and Labour Dynamics in Australia (HILDA) survey. The findings provide evidence for the interconnectedness of the three tiers of the model and their joint contribution to overall life satisfaction. Personality traits have significant direct and even stronger indirect effects on life satisfaction, mediated by their effects on satisfaction with areas of life, which has been previously overlooked. Socio‐economic characteristics have significant indirect effects on life satisfaction, which are most often omitted in analyses of life satisfaction. Satisfaction with areas of life remain strong predictors of overall life satisfaction, but only alongside personality traits and socio‐economic characteristics. The findings provide new methodological insights into the factors contributing to the measurement of life satisfaction, "all things considered". Furthermore, results may support policy makers to target vulnerable groups and identify approaches to improve their well‐being. [ABSTRACT FROM AUTHOR]