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Elimination and selection by aspects in health choice experiments: Prioritising health service innovations

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  • Erdem, Seda
  • Campbell, Danny
  • Thompson, Carl

Abstract

Priorities for public health innovations are typically not considered equally by all members of the public. When faced with a choice between various innovation options, it is, therefore, possible that some respondents eliminate and/or select innovations based on certain characteristics. This paper proposes a flexible method for exploring and accommodating situations where respondents exhibit such behaviours, whilst addressing preference heterogeneity. We present an empirical case study on the public's preferences for health service innovations. We show that allowing for elimination-by-aspects and/or selection-by-aspects behavioural rules leads to substantial improvements in model fit and, importantly, has implications for willingness to pay estimates and scenario analysis.

Suggested Citation

  • Erdem, Seda & Campbell, Danny & Thompson, Carl, 2014. "Elimination and selection by aspects in health choice experiments: Prioritising health service innovations," Journal of Health Economics, Elsevier, vol. 38(C), pages 10-22.
  • Handle: RePEc:eee:jhecon:v:38:y:2014:i:c:p:10-22
    DOI: 10.1016/j.jhealeco.2014.06.012
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    Cited by:

    1. Danny Campbell & Seda Erdem, 2019. "Including Opt-Out Options in Discrete Choice Experiments: Issues to Consider," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 12(1), pages 1-14, February.
    2. Broberg, Thomas & Daniel, Aemiro Melkamu & Persson, Lars, 2021. "Household preferences for load restrictions: Is there an effect of pro-environmental framing?," Energy Economics, Elsevier, vol. 97(C).
    3. Erlend Dancke Sandorf & Danny Campbell, 2019. "Accommodating satisficing behaviour in stated choice experiments," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 46(1), pages 133-162.
    4. Sandorf, Erlend Dancke & Crastes dit Sourd, Romain & Mahieu, Pierre-Alexandre, 2018. "The effect of attribute-alternative matrix displays on preferences and processing strategies," Journal of choice modelling, Elsevier, vol. 29(C), pages 113-132.
    5. Damien Jourdain & Juliette Lairez & Bruno Striffler & François Affholder, 2020. "Farmers’ preference for cropping systems and the development of sustainable intensification: a choice experiment approach," Review of Agricultural, Food and Environmental Studies, Springer, vol. 101(4), pages 417-437, December.
    6. Enni Ruokamo & Mikołaj Czajkowski & Nick Hanley & Artti Juutinen & Rauli Svento, 2016. "Linking perceived choice complexity with scale heterogeneity in discrete choice experiments: home heating in Finland," Working Papers 2016-30, Faculty of Economic Sciences, University of Warsaw.
    7. Damien Jourdain1,2,3 & Juliette Lairez4,5 & Bruno Striffler & François Affholder, 2020. "Farmers’ preference for cropping systems and the development of sustainable intensification: a choice experiment approach," Review of Agricultural, Food and Environmental Studies, INRA Department of Economics, vol. 101(4), pages 417-437.
    8. Dan Rigby & Caroline Vass & Katherine Payne, 2020. "Opening the ‘Black Box’: An Overview of Methods to Investigate the Decision-Making Process in Choice-Based Surveys," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 13(1), pages 31-41, February.
    9. John Buckell & Vrinda Vasavada & Sarah Wordsworth & Dean A. Regier & Matthew Quaife, 2022. "Utility maximization versus regret minimization in health choice behavior: Evidence from four datasets," Health Economics, John Wiley & Sons, Ltd., vol. 31(2), pages 363-381, February.
    10. Logar, Ivana & Brouwer, Roy & Campbell, Danny, 2020. "Does attribute order influence attribute-information processing in discrete choice experiments?," Resource and Energy Economics, Elsevier, vol. 60(C).
    11. Contu, Davide & Strazzera, Elisabetta, 2022. "Testing for saliency-led choice behavior in discrete choice modeling: An application in the context of preferences towards nuclear energy in Italy," Journal of choice modelling, Elsevier, vol. 44(C).
    12. Jourdain, Damien & Lairez, Juliette & Striffler, Bruno & Affholder, François, 2020. "Farmers’ preference for cropping systems and the development of sustainable intensification: a choice experiment approach," Review of Agricultural, Food and Environmental Studies, Institut National de la Recherche Agronomique (INRA), vol. 101(4), March.
    13. Börger, Tobias & Ngoc, Quach Thi Khanh & Kuhfuss, Laure & Hien, Tang Thi & Hanley, Nick & Campbell, Danny, 2021. "Preferences for coastal and marine conservation in Vietnam: Accounting for differences in individual choice set formation," Ecological Economics, Elsevier, vol. 180(C).
    14. Mo Zhou & Winter Maxwell Thayer & John F. P. Bridges, 2018. "Using Latent Class Analysis to Model Preference Heterogeneity in Health: A Systematic Review," PharmacoEconomics, Springer, vol. 36(2), pages 175-187, February.
    15. David A. J. Meester & Stephane Hess & John Buckell & Thomas O. Hancock, 2023. "Can decision field theory enhance our understanding of health‐based choices? Evidence from risky health behaviors," Health Economics, John Wiley & Sons, Ltd., vol. 32(8), pages 1710-1732, August.
    16. Jourdain, Damien & Lairez, Juliette & Striffler, Bruno & Lundhede, Thomas, 2022. "A choice experiment approach to evaluate maize farmers’ decision-making processes in Lao PDR," Journal of choice modelling, Elsevier, vol. 44(C).
    17. Kim Pauwels & Isabelle Huys & Minne Casteels & Yvonne Denier & Martina Vandebroek & Steven Simoens, 2019. "What Does Society Value About Cancer Medicines? A Discrete Choice Experiment in the Belgian Population," Applied Health Economics and Health Policy, Springer, vol. 17(6), pages 895-902, December.
    18. Danny Campbell & Seda Erdem, 2015. "Position Bias in Best-worst Scaling Surveys: A Case Study on Trust in Institutions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(2), pages 526-545.
    19. Mesfin G. Genie & Nicolas Krucien & Mandy Ryan, 2021. "Weighting or aggregating? Investigating information processing in multi‐attribute choices," Health Economics, John Wiley & Sons, Ltd., vol. 30(6), pages 1291-1305, June.
    20. Daniel, Aemiro Melkamu, 2020. "Towards Sustainable Energy Consumption Electricity Demand Flexibility and Household Fuel Choice," Umeå Economic Studies 971, Umeå University, Department of Economics.
    21. Wuyang Hu & Shan Sun & Jerrod Penn & Ping Qing, 2022. "Dummy and effects coding variables in discrete choice analysis," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(5), pages 1770-1788, October.
    22. Campbell, Danny & Boeri, Marco & Doherty, Edel & George Hutchinson, W., 2015. "Learning, fatigue and preference formation in discrete choice experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 345-363.
    23. Damien Jourdain & Juliette Lairez & Bruno Striffler & François Affholder, 2020. "Farmers’ preference for cropping systems and the development of sustainable intensification: a choice experiment approach," Post-Print hal-02995632, HAL.

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    More about this item

    Keywords

    Discrete choice experiments; Elimination by aspects; Selection by aspects; Latent class logit model; Health service innovations;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • D0 - Microeconomics - - General
    • I1 - Health, Education, and Welfare - - Health

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