Social Indicators Research

, Volume 115, Issue 3, pp 933–943 | Cite as

On the Predictive Effect of Multidimensional Importance-Weighted Quality of Life Scores on Overall Subjective Well-Being

  • Chia-Huei WuEmail author
  • Cheng-Ta Yang
  • Li-Na Huang


This study aimed to examine the effectiveness of importance weighting in predicting outcome variables in a hierarchical and multidimensional measurement context. A total of 146 undergraduate students (female = 76; mean age = 20.25) from two universities in Taiwan and China participated in this study. They evaluated their quality of life on 22 facets from the WHOQOL-BREF scale, which covers four domains (i.e., physical health, psychological health, social relationships, and environmental health). They were also asked to rate the importance of these 22 facets and items for three general subjective well-being indices, including overall quality of life, general health, and life satisfaction. A multiplicative formula was used to create importance-weighted scores for each facet, and four domain scores were obtained by averaging facet scores under specific domains. Results of regression analysis revealed that after applying the weighting procedure, the four domain scores did not account for more variances in the three indices for overall subjective well-being, and predictive effects of the four domain scores became less differential. Our findings suggest that importance weighting did not have its expected benefits but instead may negatively impact the predictive effects.


Weighting Importance Quality of life Subjective well-being 



This research was supported by grants from National Science Council (NSC 98-2410-H-006-118-MY2), Taiwan (R.O.C.), to the second author.


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.University of Western AustraliaCrawley, PerthAustralia
  2. 2.National Cheng Kung UniversityTainan CityTaiwan, ROC
  3. 3.Jiangxi University of Traditional Chinese MedicineWanli, Nanchang CityChina

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