Social Indicators Research

, Volume 127, Issue 2, pp 777–792 | Cite as

Domain Importance in Subjective Well-Being Measures

Article

Abstract

In subjective well-being (SWB) studies, domain importance typically refers to the relative importance of various life domains. Although there appears to be a consensus that domain importance is an important topic, whether or not domain importance should be incorporated into measures of SWB remains contentious. Even though recent studies that examined the claims against incorporating domain importance, also known as domain importance weighting, into SWB measures found that both conceptual and empirical arguments have been far from sufficient, insufficient evidence against importance weighting does not mean there is evidence to support importance weighting. Conducting a secondary analysis, the current study investigates the role of domain importance in SWB measures without making any arbitrary assumptions regarding how domain importance weighting should function. Results of the study show that the relationship between global life satisfaction and the sum of domain satisfaction scores did not remain constant across groups of different domain importance rating patterns. The findings suggest that, when the research objective is to study variability of responses at the level of homogeneous subgroups, it is important to consider domain importance when using domain satisfaction to construct global SWB measures.

Keywords

Importance weighting Domain weighting Latent class analysis Cluster analysis Relative domain importance 

References

  1. Aldenderfer, M. S., & Blashfield, R. K. (1984). Cluster analysis. Beverly Hills, CA: Sage.Google Scholar
  2. Bergman, L. R., & Magnusson, D. (1997). A person-oriented approach in research on developmental psychopathology. Development and Psychopathology, 9, 291–319.CrossRefGoogle Scholar
  3. Campbell, A., Converse, P. E., & Rodgers, W. L. (1971). Quality of American Life, 1971 (Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 1992-02-16. doi:10.3886/ICPSR03508.v1).
  4. Campbell, A., Converse, P. E., & Rogers, W. L. (1976). The quality of American Life: Perceptions, evaluations, and satisfactions. New York: Russel Sage.Google Scholar
  5. Cummins, R. A. (1995). On the tale of gold standard for life satisfaction. Social Indicators Research, 35, 179–200.CrossRefGoogle Scholar
  6. Cummins, R. A. (1996). The domains of life satisfaction: An attempt to order chaos. Social Indicators Research, 38, 303–328.CrossRefGoogle Scholar
  7. Ferrans, C. E. (1990). Development of a quality of life index for patients with cancer. Oncology Nursing Forum, 17(3), 15–19.Google Scholar
  8. Ferrans, C., & Powers, M. (1985). Quality of life index: Development and psychometric properties. Advances in Nursing Science, 8, 15–24.CrossRefGoogle Scholar
  9. Frisch, M. B., Cornell, J., Villanueva, M., & Retzlaff, P. J. (1992). Clinical validation of the Quality of Life Inventory: A measure of life satisfaction for use in treatment planning and outcome assessment. Psychological Assessment, 4, 92–101.CrossRefGoogle Scholar
  10. Hagerty, M. R., Cummins, R. A., Ferris, A. L., Land, K. C., Michalos, A. C., Peterson, M., et al. (2001). Quality of life indexes for national policy: Review and agenda for research. Social Indicators Research, 55, 1–96.CrossRefGoogle Scholar
  11. Hagerty, M. R., & Land, K. C. (2007). Constructing summary indices of quality of life: A model for the effect of heterogeneous importance weights. Sociological Methods and Research, 35, 455–496.CrossRefGoogle Scholar
  12. Hsieh, C. M. (2003). Counting importance: The case of life satisfaction and relative domain importance. Social Indicators Research, 61, 227–240.CrossRefGoogle Scholar
  13. Hsieh, C. M. (2004). To weight or not to weight: The role of domain importance in quality of life measurement. Social Indicators Research, 68, 163–174.CrossRefGoogle Scholar
  14. Hsieh, C. M. (2012a). Importance is not unimportant: The role of importance weighting in QoL measures. Social Indicators Research, 109, 206–278.CrossRefGoogle Scholar
  15. Hsieh, C. M. (2012b). Should we give up domain importance weighting in QoL measures? Social Indicators Research, 108, 99–109.CrossRefGoogle Scholar
  16. Hsieh, C. M. (2013). Issues in evaluating importance weighting in quality of life measures. Social Indicators Research, 110, 681–693.CrossRefGoogle Scholar
  17. Hsieh, C. M. (2014). Throwing the baby out with the bathwater: Evaluation of domain importance weighting in quality of life measurements. Social Indicators Research, 119, 483–493.CrossRefGoogle Scholar
  18. Hsieh, C. M., & Kenagy, G. P. (2014). Measuring quality of life: A case for re-examining the assessment of domain importance weighting. Applied Research in Quality of Life, 9, 63–77.CrossRefGoogle Scholar
  19. Inglehart, R. (1978). Value priorities life satisfaction, and political dissatisfaction among western publics. Comparative Studies in Sociology, 1, 173–202.Google Scholar
  20. Locke, E. A. (1969). What is job satisfaction? Organizational Behavior and Human Performance, 4, 309–336.CrossRefGoogle Scholar
  21. Locke, E. A. (1976). The nature and causes of job satisfaction. In M. D. Dunnette (Ed.), Handbook of industrial and organizational psychology (pp. 1297–1349). Chicago: Rand McNally.Google Scholar
  22. Magidson, J., & Vermunt, J. (2002a). Latent class cluster analysis. In J. A. Hagenaars & A. L. McCutcheon (Eds.), Applied latent class analysis (pp. 89–106). Cambridge: Cambridge University Press.Google Scholar
  23. Magidson, J., & Vermunt, J. K. (2002b). Latent class models for clustering: A comparison with K-means. Canadian Journal of Marketing Research, 20, 37–44.Google Scholar
  24. Magidson, J., & Vermunt, J. K. (2004). Latent class models. In D. Kaplan (Ed.), Sage handbook of quantitative methodology for social sciences (pp. 175–198). Thousand Oaks, CA: Sage.Google Scholar
  25. Mastekaasa, A. (1984). Multiplicative and additive models of job and life satisfaction. Social Indicators Research, 14, 141–163.CrossRefGoogle Scholar
  26. McCutcheon, A. L. (2002). Basic concepts and procedures in single- and multiple-group latent class analysis. In J. A. Hagenaars & A. L. McCutcheon (Eds.), Applied latent class analysis (pp. 56–85). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  27. Milligan, G. W., & Cooper, M. C. (1985). An examination of procedures determining the number of clusters in a data set. Psychometrika, 50, 159–179.CrossRefGoogle Scholar
  28. Milligan, G. W., & Cooper, M. C. (1987). Methodology review: Clustering methods. Applied Psychological Measurement, 11, 329–354.CrossRefGoogle Scholar
  29. Muthén, B. O. (2001). Latent variable mixture modeling. In G. A. Marcoulides & R. E. Schuniaker (Eds.), New developments and techniques in structural equation modeling (pp. 1–33). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
  30. Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling, 14, 535–569.CrossRefGoogle Scholar
  31. Philip, E. J., Merluzzi, T. V., Peterman, A., & Cronk, L. B. (2009). Measurement accuracy in assessing patient’s quality of life: To weight or not to weight domains of quality of life. Quality of Life Research, 18, 775–782.CrossRefGoogle Scholar
  32. Rojas, M. (2006). Life satisfaction and satisfaction in domains of life: Is it a simple relationship? Journal of Happiness Studies, 7, 467–497.CrossRefGoogle Scholar
  33. Russell, L. B., & Hubley, A. M. (2005). Importance ratings and weighting: Old concerns and new perspectives. International Journal of Testing, 5, 105–130.CrossRefGoogle Scholar
  34. Russell, L. B., Hubley, A. M., Palepu, A., & Zumbo, B. D. (2006). ‘Does weighting capture what’s important? Revisiting subjective importance weighting with a quality of life measure. Social Indicators Research, 75, 146–167.CrossRefGoogle Scholar
  35. Ryff, C. D., & Essex, M. J. (1992). The interpretation of life experience and well-being: The sample case of relocation. Psychology and Aging, 7, 507–517.CrossRefGoogle Scholar
  36. Snedecor, G. W., & Cochran, W. G. (1989). Statistical methods. Ames, IA: Iowa State University Press.Google Scholar
  37. Trauer, T., & Mackinnon, A. (2001). ‘Why are we weighting? The role of importance ratings in quality of life measurement. Quality of Life Research, 10, 579–585.CrossRefGoogle Scholar
  38. Vermunt, J. K., & Magidson, J. (2013). Latent GOLD 5.0 upgrade manual. Belmont, MA: Statistical Innovations Inc.Google Scholar
  39. Ward, J. H. (1963). Hierarchical grouping to optimize and objective function. Journal of the American Statistical Association, 58, 236–244.CrossRefGoogle Scholar
  40. Wu, C. H. (2008a). Examining the appropriateness of importance weighting on satisfaction score from range-of-affect hypothesis: Hierarchical linear modeling for within-subject data. Social Indicators Research, 86, 101–111.CrossRefGoogle Scholar
  41. Wu, C. H. (2008b). Can we weight satisfaction score with importance ranks across life domains? Social Indicators Research, 86, 468–480.CrossRefGoogle Scholar
  42. Wu, C. H., Chen, L. H., & Tsai, Y. M. (2009). Investigating importance weighting of satisfaction scores from a formative model with partial least squares analysis. Social Indicators Research, 90, 351–363.CrossRefGoogle Scholar
  43. Wu, C. H., & Yao, G. (2006a). Do we need to weight item satisfaction by item importance? A perspective from Locke’s range-of-affect hypothesis. Social Indicators Research, 79, 485–502.CrossRefGoogle Scholar
  44. Wu, C. H., & Yao, G. (2006b). Do we need to weight satisfaction scores with importance ratings in measuring quality of life? Social Indicators Research, 78, 305–326.CrossRefGoogle Scholar
  45. Wu, C. H., & Yao, G. (2007). Importance has been considered in satisfaction evaluation: An experimental examination of Locke’s range-of-affect hypothesis. Social Indicators Research, 81, 521–541.CrossRefGoogle Scholar
  46. Zabinski, M. F., Norman, G. J., Sallis, J. F., & Calfas, K. J. (2007). Patterns of sedentary behavior among adolescents. Health Psychology, 26, 113–120.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Jane Addams College of Social WorkUniversity of Illinois at ChicagoChicagoUSA

Personalised recommendations