The Metrics of Subjective Wellbeing Data: An Empirical Evaluation of the Ordinal and Cardinal Comparability of Life Satisfaction Scores
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This paper is motivated by the lack of consensus on the metrics of subjective wellbeing measurement scales. Subjective wellbeing data are frequently treated as though they are cardinally comparable both across and within individuals, though very little evidence exists to support these assumptions. Because wellbeing cannot be observed directly, cardinality must remain an assumption, which is usually imposed based on statistical convenience rather than on reason. The premise of this paper is that it is both possible and useful to make this assumption more informed. The analysis applies the principle of simultaneous conjoint measurement to improve our understanding of what information is contained within subjective wellbeing scores. Specifically, the metrics of the eleven-point numeric life satisfaction scale is evaluated using the MH5 mental health survey instrument. Under the assumption that the response function for MH5 is identifiable by the Rasch model, the shape of the response function for life satisfaction is potentially observable indirectly via the association between life satisfaction and MH5. The results presented here suggest life satisfaction scores are ordinally distinct, in terms of these mental health data, which supports the assumption of ordinal comparability. Under the aforementioned assumption, these scores are also approximately equidistant, which supports cardinal comparability. This pattern is found both across individuals and within individuals across time.
KeywordsLife satisfaction Subjective wellbeing Mental health Cardinality Ordinality Response functions Methodology
This paper is dedicated to the memory of Paul W. Miller, who encouraged me to pursue this work on the metrics of subjective wellbeing. Several other scholars have provided valuable comments and guidance in the various developmental stages of this paper, including Robert Cummings, Stephen Pudney, Juerg Weber, Peter Robertson, David Butler, Paul Gerrans and David Andrich. I also wish to thank three anonymous referees for considered and valuable comments and suggestions. The study uses unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) survey. The HILDA project was initiated and funded by the Australian Government Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA) and is managed by the Melbourne Institute of Applied Economic and Social Research (MIAESR). The findings and views reported in this paper, as well as any mistakes or errors, are those of the author, and should not be attributed to any of the scholars listed in these acknowledgements or to FaHCSIA or MIAESR.
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