Abstract
Most people consider health (quality and duration of life) as important but since we rarely choose between health states, our preferences are often not well-formed; moreover, the quality of life is frequently defined using imprecise terms (e.g. moderate difficulties doing usual activities). Therefore, we propose to model preferences towards health states (precisely: disutilities of worsening health dimensions in the EQ-5D-5L descriptive system) as fuzzy: each worsening is assigned an interval instead of a crisp number. We elicit such preferences with discrete choice experiment (DCE) data, using a maximum likelihood approach and bootstrapping to assess the estimation error. For example, the disutility of moderate difficulties doing usual activities was estimated as lying in the interval (0.018; 0.206). Pain/discomfort and anxiety/depression are associated with greatest upper bounds of disutilities and largest fuzziness (longest ranges). Our approach dispenses with one of the non-intuitive features of the standard approach to DCE, where even a clearly dominated alternative has a positive probability of being chosen; in our model, if the disutility ranges do not overlap, the worse alternative will never be chosen. Also, our model is more consistent regarding the constant proportional trade-off condition: the probability of a given health state being chosen in a pair will not change if durations are scaled proportionally; something that is not true in the standard DCE model.
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Notes
- 1.
The general idea is presented. The original formulas and notation are slightly changed.
- 2.
In a degenerate case \(L(Q)=H(Q)\), the membership function jumps discontinuously from 1 to 0.
- 3.
This model is originally meant for decisions under uncertainty, but we can confine attention to sure alternatives, because they constitute a subset of all alternatives.
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The research was financed by the funds obtained from National Science Centre, Poland, granted following the decision number DEC-2015/19/B/HS4/01729.
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Jakubczyk, M., Kamiński, B., Lewandowski, M. (2018). Eliciting Fuzzy Preferences Towards Health States with Discrete Choice Experiments. In: Berger-Vachon, C., Gil Lafuente, A., Kacprzyk, J., Kondratenko, Y., Merigó, J., Morabito, C. (eds) Complex Systems: Solutions and Challenges in Economics, Management and Engineering. Studies in Systems, Decision and Control, vol 125. Springer, Cham. https://doi.org/10.1007/978-3-319-69989-9_9
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