Morrison M, Bennett J, Blamey R. Valuing improved wetland quality using choice modeling. Water Resour Res. 1999;35(9):2805–14. https://doi.org/10.1029/1999WR900020.

Article  Google Scholar 

Gillespie R, Bennett J. Valuing the environmental, cultural and social impacts of open-cut coal mining in the Hunter Valley of New South Wales, Australia. J Environ Econ Policy. 2012;1(3):276–88. https://doi.org/10.1080/21606544.2012.714970.

Article  Google Scholar 

Beresniak A, Medina-Lara A, Auray JP, et al. Validation of the underlying assumptions of the quality-adjusted life-years outcome: results from the ECHOUTCOME European Project. Pharmacoeconomics. 2015;33(1):61–9. https://doi.org/10.1007/s40273-014-0216-0.

Article  PubMed  Google Scholar 

Broome J. QALYs. J Public Econ. 1993;50(2):149–67.

Article  Google Scholar 

Miyamoto JM, Wakker PP, Bleichrodt H, Peters HJM. The zero-condition: a simplifying assumption in QALY measurement and multiattribute utility. Manag Sci. 1998;44(6):839–49.

Article  Google Scholar 

Pliskin JS, Shepard DS, Weinstein MC. Utility functions for life years and health status. Oper Res. 1980;28:206–24.

Article  Google Scholar 

Bootman JL, McGhan WF, Townsend RJ. Pharmacoeconomics: historical perspective. Ann Pharmacother. 2006;40(3):518–9. https://doi.org/10.1345/aph.1G390.

Article  PubMed  Google Scholar 

Drummond M, Jonsson B, Rutten F. The role of economic evaluation in the pricing and reimbursement of medicines. Health Policy. 1997;40(3):199–215. https://doi.org/10.1016/s0168-8510(97)00901-9.

Article  CAS  PubMed  Google Scholar 

Lipscomb J, Drummond M, Fryback D, Gold M, Revicki D. Retaining, and enhancing, the QALY. Value Health. 2009;12(s1):S18-26. https://doi.org/10.1111/j.1524-4733.2009.00518.x.

Article  PubMed  Google Scholar 

Nord E, Daniels N, Kamlet M. QALYs: some challenges. Value Health. 2009;12(s1):S10-15. https://doi.org/10.1111/j.1524-4733.2009.00516.x.

Article  PubMed  Google Scholar 

Johnson FR, Hauber B, Ozdemir S. Conjoint-analysis QALYs for acute conditions. Value Health. 2006;9(6):A258.

Article  Google Scholar 

Mankiw NG. Principles of microeconomics. Boston: Cengage Learning; 2017. p. 528.

Google Scholar 

Johnson FR, Gonzalez JM, Sheehan JJ, Reed SD. How much better is faster? Value adjustments for health improvement sequences. Pharmacoeconomics. 2023;41(8):845–56. https://doi.org/10.1007/s40273-023-01266-7.

Article  PubMed  Google Scholar 

Manski CF. The structure of random utility models. Theory Decis. 1977;8(3):229.

Article  Google Scholar 

Kjaer T. A review of the discrete choice experiment-with emphasis on its application in health care. Syddansk Universitet, Odense, Denmark; 2005.

Norman R, Viney R, Brazier J, et al. Valuing SF-6D health states using a discrete choice experiment. Med Decis Mak. 2014;34(6):773–86.

Article  Google Scholar 

Viney R, Norman R, Brazier J, et al. An Australian discrete choice experiment to value EQ-5D health states. Health Econ. 2014;23(6):729–42.

Article  PubMed  Google Scholar 

Fenwick EK, Ozdemir S, Man RE, et al. Development and validation of a preference-based glaucoma utility instrument using discrete choice experiment. JAMA Ophthalmol. 2021;139(8):866–74.

Article  PubMed  PubMed Central  Google Scholar 

van den Broek-Altenburg EM, Atherly AJ. Patient preferences for provider choice: a discrete choice experiment. Am J Manag Care. 2020;26(7):e219–24.

Article  PubMed  Google Scholar 

Ozdemir S, Yeo SWJ, Lee JJ, Bhaskar A, Finkelstein E, Tong L. Patient medication preferences for managing dry eye disease: the importance of medication side effects. Patient. 2022;15(6):679–90.

Article  PubMed  PubMed Central  Google Scholar 

Roy AN, Madhavan SS, Lloyd A. A discrete choice experiment to elicit patient willingness to pay for attributes of treatment-induced symptom relief in comorbid insomnia. Manag Care. 2015;24(4):42.

PubMed  PubMed Central  Google Scholar 

Norman R, Viney R, Aaronson N, et al. Using a discrete choice experiment to value the QLU-C10D: feasibility and sensitivity to presentation format. Qual Life Res. 2016;25:637–49.

Article  CAS  PubMed  Google Scholar 

Wasserman D, Rihmer Z, Rujescu D, et al. The European Psychiatric Association (EPA) guidance on suicide treatment and prevention. Eur Psychiatry. 2012;27(2):129–41.

Article  CAS  PubMed  Google Scholar 

Bridges JF, Hauber AB, Marshall D, et al. Conjoint analysis applications in health—a checklist: a report of the ISPOR Good Research Practices for Conjoint Analysis Task Force. Value Health. 2011;14(4):403–13.

Article  PubMed  Google Scholar 

Johnson FR, Lancsar E, Marshall D, et al. Constructing experimental designs for discrete-choice experiments: report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force. Value Health. 2013;16(1):3–13. https://doi.org/10.1016/j.jval.2012.08.2223.

Article  Google Scholar 

Montgomery SA, Asberg M. A new depression scale designed to be sensitive to change. Br J Psychiatry. 1979;134:382–9. https://doi.org/10.1192/bjp.134.4.382.

Article  CAS  PubMed  Google Scholar 

Snaith RP, Harrop FM, Newby DA, Teale C. Grade scores of the Montgomery-Asberg Depression and the Clinical Anxiety Scales. Br J Psychiatry. 1986;148:599–601. https://doi.org/10.1192/bjp.148.5.599.

Article  CAS  PubMed  Google Scholar 

Kanninen BJ. Optimal design for multinomial choice experiments. J Mark Res. 2002;39(2):214–27.

Article  Google Scholar 

Whitty JA, Walker R, Golenko X, Ratcliffe J. A think aloud study comparing the validity and acceptability of discrete choice and best worst scaling methods. PLoS ONE. 2014;9(4): e90635.

Article  PubMed  PubMed Central  Google Scholar 

Jonker MF. The garbage class mixed logit model: accounting for low-quality response patterns in discrete choice experiments. Value Health. 2022;25(11):1871–7. https://doi.org/10.1016/j.jval.2022.07.013.

Article  Google Scholar 

Krinsky I, Robb AL. On approximating the statistical properties of elasticities. Rev Econ Stat. 1986;68(4):715–9.