To introduce a parsimonious modelling approach that enables the estimation of interaction effects in health state valuation studies.
Instead of supplementing a main effects model with interactions between each and every level, a more parsimonious optimal scaling approach is proposed. This approach is based on the mapping of health-state levels onto domain-specific continuous scales. The attractiveness of health states is then determined by the importance-weighted optimal scales (i.e. main effects) and the interactions between these domain-specific scales (i.e. interaction effects). The number of interaction terms only depends on the number of health domains. As a result, interactions between dimensions can be included with only a few additional parameters.
The proposed models with and without interactions are fitted on three valuation datasets from two different countries, i.e. a Dutch latent-scale discrete choice experiment (DCE) dataset with N=3,699 respondents, an Australian time-trade-off (TTO) dataset with N=400 respondents, and a Dutch DCE with duration dataset with N=788 respondents.
Important interactions between health domains were found in all three applications. The results confirm that the accumulation of health problems within health states has a decreasing marginal effect on health state values. A similar effect is obtained when so-called N3 or N5 terms are included in the model specification, but the inclusion of two-way interactions provides superior model fits.
The proposed interaction model is parsimonious, produces estimates that are straightforward to interpret, and accommodates the estimation of interaction effects in health state valuation studies with realistic sample size requirements. Not accounting for interactions is shown to result in profoundly biased value sets, particularly in stand-alone DCE with duration studies.
Received in revised form:
Publication stageIn Press Accepted Manuscript
❑ Concept and design: Jonker and Donkers
❑ Obtaining funding: Jonker
❑ Acquisition of data: Jonker
❑ Statistical analysis: Jonker and Donkers
❑ Drafting of the manuscript: Jonker and Donkers
❑ Critical revision of paper for important intellectual content: Jonker and Donkers
Conflict of Interest Disclosures
Dr. Jonker reported being a member of the EuroQol Group and the EuroQol Valuation Working Group. No other disclosures were reported.
Funding/Support: This work was supported by a grant (EQ Project 415-RA) from the EuroQol Research Foundation.
Role of Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review, or approval of the manuscript, and decision to submit the manuscript for publication.
Acknowledgments: The authors gratefully acknowledge financial support from the EuroQol Research Foundation and emphasize that the views as expressed in this article do not necessarily reflect those of the EuroQol Group.
© 2022 International Society for Pharmacoeconomics and Outcomes Research, Inc. Published by Elsevier Inc.