Transforming discrete choice experiment latent scale values for EQ-5D-3L using the visual analogue scale

Edward J. D. Webb (), John O’Dwyer, David Meads, Paul Kind and Penny Wright
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Edward J. D. Webb: University of Leeds
John O’Dwyer: University of Leeds
David Meads: University of Leeds
Paul Kind: University of Leeds
Penny Wright: University of Leeds

The European Journal of Health Economics, 2020, vol. 21, issue 5, No 11, 787-800

Abstract: Abstract Background Discrete choice experiments (DCEs) are widely used to elicit health state preferences. However, additional information is required to transform values to a scale with dead valued at 0 and full health valued at 1. This paper presents DCE-VAS, an understandable and easy anchoring method with low participant burden based on the visual analogue scale (VAS). Methods Responses from 1450 members of the UK general public to a discrete choice experiment (DCE) were analysed using mixed logit models. Latent scale valuations were anchored to a full health = 1, dead = 0 scale using participants’ VAS ratings of three states including the dead. The robustness of results was examined. This included a filtering procedure with the influence each individual respondent had on valuation being calculated, and those whose influence was more than two standard deviations away from the mean excluded. Results Coefficients in all models were in the expected direction and statistically significant. Excluding respondents who self-reported not understanding the VAS task did not significantly influence valuation, but excluding a small number who valued 33333 extremely low did. However, after eight respondents were removed via the filtering procedure, valuations were robust to removing other participants. Conclusion DCE-VAS is a feasible way of anchoring DCE results to a 0–1 anchored scale with low additional respondent burden.

Keywords: EQ-5D; Discrete choice experiment; Anchoring; Visual analogue scale; Valuation (search for similar items in EconPapers)
JEL-codes: D7 I10 I30 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s10198-020-01173-0

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