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

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 wi...

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Detalles Bibliográficos
Autores principales: Webb, Edward J. D., O’Dwyer, John, Meads, David, Kind, Paul, Wright, Penny
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7366608/
https://www.ncbi.nlm.nih.gov/pubmed/32180068
http://dx.doi.org/10.1007/s10198-020-01173-0
Descripción
Sumario: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.